Let's Know Things

This week we talk about neural networks, AGI, and scaling laws.

We also discuss training data, user acquisition, and energy consumption.

Recommended Book: Through the Grapevine by Taylor N. Carlson

Transcript

Depending on whose numbers you use, and which industries and types of investment those numbers include, the global AI industry—that is, the industry focused on producing and selling artificial intelligence-based tools—is valued at something like a fifth to a quarter of a trillion dollars, as of halfway through 2024, and is expected to grow to several times that over the next handful of years, that estimate ranging from two or three times, to upward of ten or twenty-times the current value—again, depending on what numbers you track and how you extrapolate outward from those numbers.

That existing valuation, and that projected (or in some cases, hoped-for growth) is predicated in part on the explosive success of this industry, already.

It went from around $10 billion in global annual revenue in 2018 to nearly $100 billion in global revenue in 2024, and the big players in this space—among them OpenAI, which kicked off the most recent AI-related race, the one focusing on large-language models, or LLMs, when it released its ChatGPT tool at the tail-end of 2022—have been attracting customers at a remarkable rate, OpenAI hitting a million users in just five days, and pulling in more than 100 million monthly users by early 2023; a rate of customer acquisition that broke all sorts of records.

This industry’s compound annual growth rate is approaching 40%, and is expected to maintain a rate of something like 37% through 2030, which basically means it has a highly desirable rate of return on investment, especially compared to other potential investment targets.

And the market itself, separate from the income derived from that market, is expected to grow astonishingly fast due to the wide variety of applications that’re being found for AI tools; that market expanded by something like 50% year over year for the past five years, and is anticipated to continue growing by about 25% for at least the next several years, as more entities incorporate these tools into their setups, and as more, and more powerful tools are developed.

All of which paints a pretty flowery picture for AI-based tools, which justifies, in the minds of some analysts, at least, the high valuations many AI companies are receiving: just like many other types of tech companies, like social networks, crypto startups, and until recently at least, metaverse-oriented entities, AI companies are valued primarily based on their future potential outcomes, not what they’re doing today.

So while many such companies are already showing impressive numbers, their numbers five and ten years from now could be even higher, perhaps ridiculously so, if some predictions about their utility and use come to fruition, and that’s a big part of why their valuations are so astronomical compared to their current performance metrics.

The idea, then, is that basically every company on the planet, not to mention governments and militaries and other agencies and organizations will be able to amp-up their offerings, and deploy entirely new ones, saving all kinds of money while producing more of whatever it is they produce, by using these AI tools. And that could mean this becomes the industry to replace all other industries, or bare-minimum upon which all other industries become reliant; a bit like power companies, or increasingly, those that build and operate data centers.

There’s a burgeoning counter-narrative to this narrative, though, that suggests we might soon run into a wall with all of this, and that, consequently, some of these expectations, and thus, these future-facing valuations, might not be as solid as many players in this space hope or expect.

And that’s what I’d like to talk about today: AI scaling walls—what they are, and what they might mean for this industry, and all those other industries and entities that it touches.

—

In the world of artificial intelligence, artificial general intelligence, or AGI, is considered by many to be the ultimate end-goal of all the investment and application in and of these systems that we’re doing today.

The specifics of what AGI means varies based on who you talk to, but the idea is that an artificial general intelligence would be “generally” smart and capable in the same, or in a similar way, to human beings: not just great at doing math and not just great at folding proteins, or folding clothes, but pretty solid at most things, and trainable to be decent, or better than decent at potentially everything.

If you could develop such a model, that would allow you, in theory, to push humans out of the loop for just about every job: an AI bot could work the cash register at the grocery store, could drive all the taxis, and could do all of our astronomy research, to name just a few of the great many jobs these systems could take on, subbing in for human beings who would almost always be more expensive, but who—this AI being a generalist and pretty good at everything—wouldn’t necessarily do any better than these snazzy new AI systems.

So AGI is a big deal because of what it would represent in terms of us suddenly having a potentially equivalent intelligence, an equivalent non-human intelligence, to deal with and theorize over, but it would also be a big deal because it could more or less put everyone out of work, which would no doubt be immensely disruptive, but it would also be really, really great for the pocketbooks of all the companies that are currently burdened with all those paychecks they have to sign each month.

The general theory of neural network-based AI systems, which basically means software that is based in some way on the neural networks that biological entities, like mice and fruit flies and humans have in our brains and throughout our bodies, is that these networks should continue to scale as the number of factors that go into making them scale: and usually those factors include the size of the model—which in the case of most of these systems means the number of parameters it includes—the size of the dataset it trains on—which is the amount of data, written, visual, audio, and otherwise, that it’s fed as it’s being trained—and the amount of time and resources invested in its training—which is a variable sort of thing, as there are faster and slower methods for training, and there are more efficient ways to train that use less energy—but in general, more time and more resources will equal a more girthy, capable AI system.

So scale those things up and you’ll tend to get a bigger, up-scaled AI on the other side, which will tend to be more capable in a variety of ways; this is similar, in a way, to biological neural networks gaining more neurons, more connections between those neurons, and more life experience training those neurons and connections to help us understand the world, and be more capable of operating within it.

That’s been the theory for a long while, but the results from recent training sessions seem to be pouring cold water on that assumption, at least a bit, and at least in some circles.

One existing scaling concern in this space is that we, as a civilization, will simply run out of novel data to train these things on within a couple of years.

The pace at which modern models are being trained is extraordinary, and this is a big part of why the larger players, here, don’t even seriously talk about compensating the people and entities that created the writings and TV shows and music they scrape from the web and other archives of such things to train their systems: they are using basically all of it, and even the smallest payout would represent a significant portion of their total resources and future revenues; this might not be fair or even legal, then, but that’s a necessary sacrifice to build these models, according to the logic of this industry at the moment.

The concern that is emerging, here, is that because they’ve already basically scooped up all of the stuff we’ve ever made as a species, we’re on the verge of running out of new stuff, and that means future models won’t have more music and writing and whatnot to use—it’ll have to rely on more of the same, or, and this could be even worse, it’ll have to rely on the increasing volume of AI-generated content for future iterations, which could result in what’s sometimes called a “Habsburg AI,” referring to the consequences of inbreeding over the course of generations: and future models using AI-generated content as their source materials may produce distorted end-products that are less and less useful (and even intelligible) to humans, which in turn will make them less useful overall, despite technically being more powerful.

Another concern is related to the issue of physical infrastructure.

In short, global data centers, which run the internet, but also AI systems, are already using something like 1.5-2% of all the energy produced, globally, and AI, which use an estimated 33% more power to generate a paragraph of writing or an image, than task-specific software would consume to do the same, is expected to double that figure by 2025, due in part to the energetic costs of training new models, and in part to the cost of delivering results, like those produced by the ChatGPTs of the world, and those increasingly generated in lieu of traditional search results, like by Google’s AI offerings that’re often plastered at the top of their search results pages, these days.

There’s a chance that AI could also be used to reduce overall energy consumption in a variety of ways, and to increase the efficiency of energy grids and energy production facilities, by figuring out the optimal locations for solar panels and coming up with new materials that will increase the efficiency of energy transmission. But those are currently speculative benefits, and the current impact of AI on the energy grid is depletionary, not additive.

There’s a chance, then that we’ll simply run out of energy, especially on a local basis, where the training hubs are built, to train the newest and greatest and biggest models in the coming years. But we could also run out of other necessary resources, like the ginormous data centers required to do said training, and even the specific chips that are optimized for this purpose that are in increasingly short supply because of how vital this task has become for so many tech companies, globally.

The newest concern in this space, related to future growth, though, is related to what are called scaling laws, which refer to a variety of theories—some tested, some not yet fully tested—about how much growth you can expect if you use the same general AI system structure, and just keep pumping it up with more resources, training data, and training time.

The current batch of most powerful and, for many use-cases, most useful AI systems are the result of scaling basically the same AI system structure so that it becomes more powerful and capable over time. There’s delay between new generations because tweaks are made, all that training and feeding has to be done, but also because there are adjustments required afterward to optimize the system for different purposes and for stability.

But a slew of industry experts have been raising the alarm about a possible bubble in this space, not because it’s impossible to build more powerful AI, but because the majority of resources that have been pumped into the AI industry in recent years are basically just inflating a giant balloon predicated on scaling the same things over and over again, every company doing this scaling hoping to reach AGI or something close to AGI before their competitors, in order to justify those investments and their sprawling valuations.

In other words, it’s a race to a destination that they might not be able to reach, in the near-future, or ever, using the current batch of technologies and commonly exploited approaches, but they can’t afford to dabble in too many alternatives, at least not thoroughly, because there’s a chance if they take their eyes off the race they’re running, right now, one of their many also-super-well-funded opponents will get there first, and they’ll be able to make history, while also claiming the lion’s share of the profits, which could be as substantial as the entire economy, if you think of those aforementioned benefits of being able to replace a huge chunk of the world’s total employee base with equally capable bots.

The most common version of this argument, that the current generation of AI systems are hitting a point of diminishing returns—still growing and becoming more powerful as they scale, but not as much as anticipated, less growth and power per unit of resource, training time, size of dataset, and so on, compared to previous generations—and that diminishment means, according to this argument, we’ll continue to see a lot of impressive improvements, but should not longer expect the doubling of capability every 5 to 14 months that we’ve seen these past few years.

We’ve picked the low-hanging fruit, in other words, and everything from this point forward will be more expensive, less certain, and thus, less appealing to investors—while also potentially being less profitable, and thus, the money that’s been plowed into these businesses, thus far, might not payout, and we could see some large-scale collapses due to the disappearance of those resources that are currently funding this wave of AI-scaling, as a consequence.

If true, this would be very bad in a lot of ways, in part because these are resources that could have been invested in other things, and in part because a lot of hardware and know-how and governmental heft have been biased toward these systems for years now; so the black hole left behind, should all of that disappear or prove to be less than many people assumed, would be substantial, and could lead to larger-scale economic issues; that gaping void, that gravity well made worse because of those aforementioned sky-high valuations, which are predicated mostly on what these companies are expected to do in the future, not what they’re doing, today—so that would represent a lot of waste, and a lot of unrealized, but maybe never feasible in the first place, potential.

This space is maybe propped up by hype and outlandish expectations, in other words, and the most recent results from OpenAI and their upcoming model seem to lend this argument at least some credibility: the publicly divulged numbers only show a relatively moderate improvement over their previous core model, GPT4, and it’s been suggested, including by folks who previously ran OpenAI, that more optimizing after the fact, post-training, will be necessary to get the improvements the market and customers are expecting—which comes with its own unknowns and additional costs, alongside a lack of seemingly reliable, predictable scaling laws.

For their part, the folks currently at the top of the major AI companies have either ignored this line of theorizing, or said there are no walls, nothing to see here, folks, everything is going fine. 

Which could be true, but they’re also heavily motivated not to panic the market, so there’s no way to really know at this point how legit their counter-claims might be; there could be new developments we’re not currently, publicly aware of, but it could also be that they’re already working those post-training augmentations into their model of scaling, and just not mentioning that for financial reasons.

AI remains a truly remarkable component of the tech world, right now, in part because of what these systems have already shown themselves capable of, but also because of those potential, mostly theorized, at this point, benefits they could enable, across the economy, across the energy grid, and so on.

The near-future outcomes, though, will be interesting to watch, as it could be we’ll see a lot of fluffed-up models that roughly align with anticipated scaling-laws, but which didn’t get there by the expected, training-focused paths, which would continue to draw questions from investors who had specific ideas about how much it would cost to get what sorts of outcomes, which in turn would curse this segment of the economy and technological development with more precarious footing than it currently enjoys.

We might also see a renewed focus on how these systems are made available to users: a rethinking of the interfaces used, and the use-cases they’re optimized for, which could make the existing (and near-future) models ever more useful, despite not becoming as powerful as anticipated, and despite probably not getting meaningfully closer to AGI, in the process.

Show Notes

https://arxiv.org/abs/2311.16863

https://www.weforum.org/stories/2024/07/generative-ai-energy-emissions/

https://epochai.org/blog/will-we-run-out-of-ml-data-evidence-from-projecting-dataset

https://www.semafor.com/article/11/13/2024/tiktoks-new-trademark-filings-suggest-its-doubling-down-on-its-us-business

https://arxiv.org/abs/2001.08361

https://archive.ph/d24pA

https://www.fastcompany.com/91228329/a-funny-thing-happened-on-the-way-to-agi-model-supersizing-has-hit-a-wall

https://futurism.com/the-byte/openai-research-best-models-wrong-answers

https://en.wikipedia.org/wiki/Neural_network_(machine_learning)

https://en.wikipedia.org/wiki/Neural_scaling_law

https://futurism.com/the-byte/openai-research-best-models-wrong-answers

https://futurism.com/the-byte/ai-expert-crash-imminent

https://www.theverge.com/2024/10/25/24279600/google-next-gemini-ai-model-openai-december

https://ourworldindata.org/artificial-intelligence?insight=ai-hardware-production-especially-cpus-and-gpus-is-concentrated-in-a-few-key-countries

https://blogs.idc.com/2024/08/21/idcs-worldwide-ai-and-generative-ai-spending-industry-outlook/

https://explodingtopics.com/blog/chatgpt-users

https://explodingtopics.com/blog/ai-statistics

https://www.aiprm.com/ai-statistics/

https://www.forbes.com/advisor/business/ai-statistics/

https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai

https://www.researchgate.net/profile/Gissel-Velarde-2/publication/358028059_Artificial_Intelligence_Trends_and_Future_Scenarios_Relations_Between_Statistics_and_Opinions/links/61ec01748d338833e3895f80/Artificial-Intelligence-Trends-and-Future-Scenarios-Relations-Between-Statistics-and-Opinions.pdf

https://www.statista.com/outlook/tmo/artificial-intelligence/worldwide

https://en.wikipedia.org/wiki/Artificial_intelligence#Applications

This week we talk about the Double Reduction Policy, gaokao, and Chegg.

We also discuss GPTs, cheating, and disruption.

Recommended Book: Autocracy, Inc by Anne Applebaum

Transcript

In July of 2021, the Chinese government implemented a new education rule called the Double Reduction Policy.

This Policy was meant, among other things, to reduce the stress students in the country felt related to their educational attainment, while also imposing sterner regulations on businesses operating in education and education-adjacent industries.

Chinese students spend a lot of time studying—nearly 10 hours per day for kids ages 12-14—and the average weekly study time for students is tallied at 55 hours, which is substantially higher than in most other countries, and quite a lot higher than the international average of 45 hours per week.

This fixation on education is partly cultural, but it’s also partly the result of China’s education system, which has long served to train children to take very high-stakes tests, those tests then determining what sorts of educational and, ultimately, employment futures they can expect. 

These tests are the pathway to a better life, essentially, so the kids face a whole lot of pressure from society and their families to do well, because if they don’t, they’ve sentenced themselves to low-paying jobs and concomitantly low-status lives; it’s a fairly brutal setup, looked at from elsewhere around the world, but it’s something that’s kind of taken for granted in modern China.

On top of all that in-class schoolwork, there’s abundant homework, and that’s led to a thriving private tutoring industry. Families invest heavily in ensuring their kids have a leg-up over everyone else, and that often means paying people to prepare them for those tests, even beyond school hours and well into the weekend.

Because of all this, kids in China suffer abnormally high levels of physical and mental health issues, many of them directly linked to stress, including a chronic lack of sleep, high levels of anxiety, rampant obesity and everything that comes with that, and high levels of suicide, as well; suicide is actually the most common cause of death amongst Chinese teenagers, and the majority of these suicides occur in the lead-up to the gaokao, or National College Entrance Exam, which is the biggest of big important exams that determine how teens will be economically and socially sorted basically for the rest of their lives.

This recent Double Reduction Policy, then, was intended to help temper some of those negative, education-related consequences, reducing the volume of homework kids had to tackle each week, freeing up time for sleep and relaxation, while also putting a cap on the ability of private tutoring companies to influence parents into paying for a bunch of tutoring services; something they’d long done via finger-wagging marketing messages, shaming parents who failed to invest heavily in their child’s educational future, making them feel like they aren’t being good parents because they’re not spending enough on these offerings.

This policy pursued these ends, first, by putting a cap on how much homework could be sent home with students, limiting it to 60 minutes for youngsters, and 90 minutes for middle schoolers.

It also provided resources and rules for non-homework-related after-school services, did away with bad rankings due to poor test performance that might stigmatize students in the future, and killed off some of those fear-inducing, ever-so-important exams altogether.

It also provided some new resources and frameworks for pilot programs that could help their school system evolve in the future, allowing them to try some new things, which could, in theory, then be disseminated to the nation’s larger network of schools if these experiments go well.

And then on the tutoring front, they went nuclear on those private tutoring businesses that were shaming parents into paying large sums of money to train their children beyond school hours.

The government instituted a new system of regulators for this industry, ceased offering new business licenses for tutoring companies, and forced all existing for-profit businesses in this space to become non-profits.

This market was worth about $100 billion when this new policy came into effect, which is a simply staggering sum, but the government basically said you’re not businesses anymore, you can’t operate if you try to make a profit.

This is just one of many industries the current Chinese leadership has clamped-down on over the past handful of years, often on cultural grounds, as was the case with limiting the amount of time children can play video games each day. But like that video game ban, which has apparently shown mixed results, the tutoring ban seems to have led to the creation of a flourishing black market for tutoring services, forcing these sorts of business dealings underground, and thus increasing the fee parents pay for them each month.

In late-October of 2024, the Chinese government, while not formally acknowledging any change to this policy, eased pressure on private tutoring services—the regulators in charge of keeping them operating in accordance with nonprofit structures apparently giving them a nudge and a wink, telling them surreptitiously that they’re allowed to expand again—possibly because China has been suffering a wave of economic issues over the past several years, and the truncation of the tutoring industry led to a lot of mass-firings, tens of thousands of people suddenly without jobs, and a substantial drop in tax revenue, as well, as the country’s stock market lost billions of dollars worth of value basically overnight.

It’s also worth noting here that China’s youth unemployment rate recently hit 18.8%, which is a bogglingly high number, and something that’s not great for stability, in the sense that a lot of young people, even very well educated young people, can’t find a job, which means they have to occupy themselves with other, perhaps less productive things.

But high youth unemployment is also not great for the country’s economic future, as that means these are people who aren’t attaining new skills and experience—and they can’t do that because the companies that might otherwise hire them can’t afford to pay more employees because folks aren’t spending enough on their offerings.

So while it was determined that this industry was hurting children and their families who had to pay these near-compulsory tutoring fees, they also seemed to realize that lacking this industry, their unemployment and broader economic woes would be further inflamed—and allowing for this gray area in the rules seems to be an attempt to have the best of both worlds, though it may leave them burdened with the worst of both worlds, as well.

What I’d like to talk about today is another facet of the global tutoring industry, and how new technologies seem to be flooding into this zone even more rapidly than in other spaces, killing off some of the biggest players and potentially portending the sort of collapse we might also see in other industries in the coming years.

—

Chegg, spelled c-h-e-g-g, is a US-based, education-focused tech company that has provided all sorts of learning-related services to customers since 2006.

It went public on the NYSE in 2013, and in 2021 it was called the “most valuable edtech company in America” by Forbes, due in part to the boom in long-distance education services in the early days of the Covid-19 pandemic; like Peloton and Zoom, Chegg was considered to be a great investment for a future in which more stuff is done remotely, as seemed likely to be the case for a good long while, considering all the distancing and shut-downs we were doing at the time.

In early 2020, before that boom, the company was already reporting that it had 2.9 million subscribers to its Chegg Services offering, which gave users access to all sorts of school-related benefits, including help with homework, access to Q&As with experts, and a huge database of solutions for tests and assignments.

The company then released a sort of social-publishing platform called Uversity in mid-2021, giving educators a place to share their own content, and they acquired a language-learning software company called Busuu, which is a bit like Duolingo, that same year for $436 million.

In May of 2023, though, the company’s CEO said, on an earnings call, that ChatGPT—the incredibly popular, basically overnight-popular large-language-model-powered AI chatbot created by OpenAI—might hinder Chegg’s near-future growth.

The day after that call, Chegg’s stock price dropped by about 48%, cutting the company’s market value nearly in half, and though later that same month he announced that Chegg would partner with OpenAI to launch its own AI platform called Cheggmate, which was launched as a beta in June, by early November the following year, 2024, the company had lost about 99% of its market valuation, dropping from a 2021 high of nearly $100 per share, down to less than $2 per share as of early November.

This isn’t a unique story: LLM-based AI tools, those made by OpenAI but also its competitors, including big tech companies like Google and Microsoft, which have really leaned into this seeming transition, have been messing with market valuations left and right, as this collection of tools and technologies have been evolving really fast—a recent five-year plan for Chegg indicated they didn’t believe something like ChatGPT would exist until 2025 at the earliest, for instance, which turned out to be way off—but they’ve also been killing off high-flying company valuations because these sorts of tools are by definition multi-purpose, and a lot of the low-hanging fruit in any industry is basically just providing information that’s already available somewhere in a more intuitive and accessible fashion; which is something a multi-purpose, bot-interfaced software tool is pretty good at doing, as it turns out.

Chegg’s services were optimized to provide school-related stuff to students—including test and homework answers those students could quickly reference if they wanted to study or cheat—and serving up these resources in a simple manner is what allowed them to pay the bills.

ChatGPT and similar AI tools, though, can do the same, and for practically or literally—for the end-user, at least—free. And it can sometimes do so in a manner that’s even more intuitive than the Cheggs of the world, even if these AI offerings are sometimes jumbled along the way; the risk-reward math is still favorable to a lot of people, because of just how valuable this kind of information provided in this way can be.

Other companies and entire industries are finding themselves in the same general circumstances, also all of a sudden, because their unique value proposition has been offering some kind of information intuitively, or in some cases they’ve provided human interfaces that would do various things for customers: they would look up deals on a particular model of car, they would write marketing copy, they would commentate on sporting events.

Some of these entities are trying to get ahead of the game, like Chegg did, by basically plugging their existing services into AI versions of the same, replacing their human commentators with bots that can manage a fair approximation of those now-unemployed humans, but at a fraction of the cost. Others are facing a huge number of new competitors, as smaller businesses or just individuals are realizing they can pay a little money for AI tokens and credits, plug an API into a website, which allows that AI to populate content on their site automatically, and they can then run the same sort of service with little or no effort, and vitally, little or no overhead.

This creates a race-to-the-bottom situation in many such cases, and often the bots are nowhere near as good as the humans they’re replacing, but especially in situations where human jobs have been optimized so that one human can be replaced with another human relatively simply, it has proven to be fairly easy to fire people and then replace them with non-humans that seem human-enough most of the time.

So blog-writing and video-making and inventory-organizing and, yes, school-tutoring and similar services are increasingly being automated in this way, and while, sure, you could pay a premium to stick with Chegg and access these AI tools via their portal for $20 a month, the bet many investors are making is that folks will probably prefer to get what amounts to the same thing cheaper, or even free, directly from the source, or via one of those other lower-end intermediaries with fewer overhead costs.

Chegg has lost about $14.5 billion in market value since early 2021, and the company is now expected to collapse under the weight of its debts sometime in the near-future; the shift in fortunes brought about by the deployment of generally capable, if not perfectly capable, chat-interface accessible AI tools has been that sudden.

None of which means this is a permanent thing, as entities in industries currently being challenged by AI equivalent or near-equivalent tools might push back with their own, difficult to replicate offerings, and there’s a chance that the small but burgeoning wave of vehemently non-AI tools—those that wave their human-made-ness, their non-AI-ness like a flag, or like an organic, cruelty-free label—might carve out their own sustainable, growable niche. That becomes their unique value proposition in place of what these AI-focused companies stole from them.

But this kind of disruption sometimes leads to an extinction-level event for the majority of operators in a formerly flourishing space.

Chegg, for their part, decided to revamp their AI offering, moving away from the Cheggmate name and working with Scale AI instead of OpenAI, to build a few dozen AI systems optimized for different academic focuses; which could prove to be a valuable differentiator for them, but it could also fall flat in the face of OpenAI’s own re-skinned versions of ChatGPT, called GPTs, which allow users to do basically the same thing, coming up with their own field focused experts and personalities, rather than using the vanilla model of the bot.

There’s a chance this will also help Chegg deal with another AI-related issue—specifically, that ChatGPT was providing better answers to some students’ questions than Chegg’s human-derived offerings; they’re trying to out-bot OpenAI, essentially, doing the homework-AI thing better than ChatGPT, and there’s a chance that offering a demonstrably higher quality of answers might also serve as a survival-enabling differentiator; though their ability to consistently provide better answers in this way is anything but certain.

It’s also worth noting that what we’re talking about here, so far, isn’t the sci-fi dream of a perfect digital tutor—something like the Young Lady’s Illustrated Primer from Neal Stephenson’s novel The Diamond Age, which is something like an AI-powered storybook that adapts its content to the reader, and which then teaches said reader everything they need to know to flourish in life, day by day. Chegg and ChatGPT serve up tools that help students cheat on tests and homework, while also helping them look up information a lot easier when they decide not to cheat, and to practice various sorts of assignments and exams beforehand.

So this is a far easier space to compete in than something more complex and actually tutor-like. It may be, then, that moving in that direction, toward tools that focus more on replacing teachers and tutors, rather than helping students navigate schoolwork, might be the killer app that allows some of these existing tutoring-ish tools to survive and thrive; though it may be that something else comes along in the meantime which fulfills that promise better—maybe ChatGPT, or maybe some new, more focused version of the same general collection of tools.

It’ll probably be a few years before we see how this and similar bets that’re being made by at-risk companies facing the AI barbarians at the gate turn out, and at that point these tools will likely be even more powerful, offering even more capabilities and thus disrupting, or threatening to disrupt, even more companies in even more industries, as a consequence.

Show Notes

https://www.wsj.com/tech/ai/how-chatgpt-brought-down-an-online-education-giant-200b4ff2

https://openai.com/index/introducing-gpts/

https://ai.wharton.upenn.edu/focus-areas/human-technology-interaction/2024-ai-adoption-report/

https://www.weforum.org/stories/2024/07/ai-tutor-china-teaching-gaps/

https://en.wikipedia.org/wiki/Double_Reduction_Policy

https://journals.sagepub.com/doi/full/10.1177/20965311241265123

https://www.sciencedirect.com/science/article/abs/pii/S0738059324000117

https://archive.ph/VKkrL

https://www.japantimes.co.jp/news/2023/07/22/asia-pacific/china-private-tutoring/

https://www.nbcnews.com/news/world/chinas-youth-unemployment-hits-fresh-high-economic-slowdown-restrictiv-rcna172183

This week we talk about peat, pig iron, and sulphuric acid.

We also discuss the Industrial Revolution, natural gas, and offshore wind turbines.

Recommended Book: Deep Utopia by Nick Bostrom

Transcript

This episode is going live on election day here in the US; and this has been quite a remarkable election season for many reasons, among them that there’s been just a boggling amount of money spent on advertisements and events and other efforts to claim attention and mindshare, and in part because the vitriol and tribalism of the past several elections—an evolved, intensified version of those things—has almost completely dominated all those messages.

And as someone who’s based in a swing-state, Wisconsin, I can tell you that it’s been a lot. It’s been a lot everywhere, as US elections also claim more than their fair-share of news reportage in other countries, but in the US, and in the relatively few states that are assumed to be the kingmakers in this election, it’s been just overwhelming for months, for basically a year, actually. So instead of doing anything on the election, or anything overtly political—there’ll no doubt be time for that in the coming weeks, once the dust has settled on all this—let’s talk about coal. And more specifically, British coal.

Coal has been used throughout the British Isles for a long time, with early groups burning unrefined lumps of the substance to heat their homes, though generally only when their local, close-enough-to-the-surface-to-be-gathered source for the stuff was pure enough to beat-out other options, like peat and wood, which was seldom the case in most of these areas.

It was also used to create lime from limestone, the lime used for construction purposes, to make mortar, and it was used for metal-shaping purposes by blacksmiths.

Beyond that, though, it was generally avoided in favor of cleaner-burning options, as coal is often accompanied by sulphur and other such substances, which means when burned in its natural form, it absolutely reeks, and it can make anyone unlucky enough to be caught in the smoke it creates tear-up, because the resulting sulfurous gas would react with their eye-moisture to create sulphuric acid; not pleasant, and even though it was generally better than peat and wood in terms of the energy it contained, it was worse in basically every other way.

Earlier groups of people had figured out the same: there were folks in China as early as 1000 BC, for instance, who used these rocks as fuel for copper smelting, and people in these same early-use areas, where coal veins were exploitable, were really leaning into the stuff by the 13th century AD, when Marco Polo visited and remarked that the locals were burning these weird black stones, which granted them wild luxuries, like being able to take “three hot baths a week.”

Groups in Roman Britain were also surface mining, using, and trading coal at a fairly reasonable level by around 200 AD, though it was still primarily used to process things like grain, which needed to be dried, and to work with iron—as with those Chinese groups, coal has long been appreciated for its smelting capabilities, because of its high energy density compared to other options.

In the British Isles, though, coal was largely imported to major cities by sea, until around the 13th century when the easily accessed deposits were used up, and shaft mining, which granted access to deeper deposits via at times long tunnels that had to be dug and reinforced, was developed and became common, including in areas that hadn’t previously had surface sources that could be exploited.

In the 16th century, this and similar innovations led to a reliable enough supply of coal that folks living in the city of London were able to largely replace their wood- and peat-burning infrastructure with coal-burning versions of the same.

It’s thought that this transition was partly the consequence of widespread deforestation that resulted from a population boom in the city—more lumber was needed to build more buildings, but they also required more burnable wood fuel—though some historians have argued that what actually pushed coal to the forefront, despite its many downsides compared to wood and peat, is the expansion of iron smelting and the increasing necessity of iron for Britain’s many wars during this period, alongside England’s burgeoning glass-making industry.

Both of these manufacturing processes, making iron and glass, required just a silly amount of fuel—making just one ton of the lowest-grade cast iron, so-called pig iron, consumed something like 28 tons of seasoned wood, and glass was similarly wood-hungry.

What’s more, that combination of city expansion and the King’s desire to massively build-out his Navy meant timber resources were continuously being strained anywhere industry popped up and flourished, so those industries would then expand to areas where wood was still cheap, over time making wood it more expensive there, too. Eventually, wood was costly pretty much everywhere, and coal thus became comparably cheap in these regions, and you could use a lot less of it to achieve the same ends.

Even if that subbing-in led to bad smells and burning eyes and clouds of dense, black smoke wherever it was burned, then, the cost differential was substantial enough to make using coal the better option in many such cases and areas.

This boom in coal usage was amplified still further by the rapid clearing of forests due to the expansion of farm- and pastureland.

It was determined, by the late 17th century, that an acre of farm- or pastureland was worth a lot more than woodland used for timber or other purposes—around three-times as valuable—so there was a large-scale deforestation effort to basically claim as much value from these forested lands as possible, dramatically changing the landscape of the British Isles over the course of just a few decades; this transition in part enabled and powered by coal.

Around the year 1700, about five-sixths of all coal that was mined, globally, was mined in Britain, and that helped power the empire’s industrial revolution later that century, beginning in something like 1760, as the majority of clever devices that arose during that period were powered by coal, and the global industrial revolution that eventually created what we might consider technological modernity arose, initially—at least in this manifestation of the concept—from coal-powered Britain.

What I’d like to talk about today is a remarkable coal-related milestone, considering that history, that Britain recently marked, and what it might mean for this and other fuel-types, moving forward.

—

In 1882, the first-ever coal-fired power station opened in London—a thermal power station that uses coal as its fuel, which basically means you refine the stuff, break it into tiny, semi-uniform pieces, and then feed those pieces into a coal-fired boiler. In that boiler the coal is burned to generate heat, and that heat boils water, the resulting steam spinning turbines which turn generators that produce electricity.

Coal-fired power stations are massively inefficient, with modern versions of the model only boasting a 34-ish% efficiency, meaning about 34% of the total energy contained in the fuel source is ultimately converted into electricity—the rest, about 66% of the energy contained in the coal that’s burned, is lost along the way.

That’s not uncommon for power plants, though other fossil fuel-burning plants are somewhat more efficient on average, with oil-powered plants weighing in at about 37% efficiency, and gas-powered versions managing something like 50-60% at their most modern and sophisticated, though simpler variations of the design only achieve about the same as coal.

All fossil fuel-powered power stations emit greenhouse gases into the atmosphere as a byproduct of their operation, which has been shown to stoke climate change, and they all have pollutant-related byproducts, as well, though there’s a spectrum: gas is relatively clean-burning compared to its kin, while coal is the absolute worst, releasing all sorts of pollutants into the air with at times severe health consequences for anyone in the general vicinity; oil plants are somewhere in between those two extremes, depending on the type of oil used and the nature of the plant.

Those downsides are part of why newer technologies like large-scale wind turbines and solar panel arrays have been replacing fossil fuel-based power plants in many locales, and quite rapidly, though the infrastructure in many areas is optimized for these older-school options, which means there are the plants themselves, which are often quite large and real-estate-spanning, but there’s also all the mines, there’s the shipping facilities, the processing capacity for the coal or oil or whatnot—it’s a nation-spanning network of buildings and machinery and businesses, not to mention all the people who work jobs related to these vital, energy-creating industries.

Coal was already beginning to decline in the UK 100 years after that first plant was built, so by the 1990s, as gas, often called natural gas as a sort of branding effort by gas companies to make it sound cleaner and more desirable, was at that point already beginning to replace coal in many electricity-generating facilities.

Gas has done the same in many countries—especially those with vast natural sources of it, and the US has opened up a lot of new markets for this fuel type in recent decades, and in the past decade in particular, as it mastered the means of compressing gas into a liquid, often called LNG, and shipping it to ports in Europe around the same time Russia’s invasion of Ukraine was fundamentally rewiring the energy mix on the continent.

So gas has played a role in disrupting coal’s hold in many previously coal-happy areas, including the US. But it was renewables that really turned the tide against coal in the UK, with a combination of solar and wind making up about 6% of Britain’s electricity in 2012—compared to 40% for coal, at the time—but just over a decade later, in 2023, renewables were making up a whopping 34% of the UK’s energy mix, mostly due to the widescale deployment and success of offshore wind farms.

This, paired with the emergence of increasingly efficient appliances and lighting, which sip energy compared to previous-generation bulbs and kettles and refrigerators, meant the UK was able to deplete its coal-usage, even as energy demand increased—because that demand was less than anticipated, due to those efficiencies, and enough new renewables and gas facilities were coming online to meet that reduced demand.

At the tail-end of September this year, 2024, the UK witnessed the shut-down of its last remaining coal power plant, which was built 57 years ago.

This was a meaningful moment, as it marked the first time in about 142 years that coal wasn’t contributing to the UK’s electrical grid, and it has global significance, as while 23 European countries have announced that they will phase out coal in the relatively near-future, and while Belgium was the first previously coal-burning European nation to go fully coal-free, back in 2016, the UK is the first G7 nation to do so—the rest of the G7 having committed to accomplishing the same by 2035.

Decommissioning the plant will take about two years, and that will include the task of reallocating the plant’s 170-or-so employees to other positions within the power network, and going through the many steps required to clean up the area after decades of voluminous pollution, while also getting the area ready for other types of development.

In many cases right now, globally, that means swapping in some other piece of energy infrastructure; in some cases coal-fired plants can be replaced with gas-fired plants, which is still not ideal in terms of emissions, but much better than coal, and in some cases it’s a more significant change, like building-out grid-scale battery arrays, which allow nearby wind turbines and solar panels to store the excess energy they generate when the wind is blowing and sun is shining, so that none of that energy goes to waste, and so it can be used when the wind and sun aren’t cooperating.

The British government is also planning to expand its nuclear power capacity, quadrupling its currently five-strong nuclear power plant holdings by 2050, which is a choice that comes with a lot of its own consequences, including, often, very high price tags on building and operating such facilities. But because of the nature of nuclear power plants—specifically, that they produce high levels of consistent, reliable, emissions-free electricity—that additional expense is often okay, because that steady consistency nicely blends with the inconsistent output of solar and wind.

It’s worth noting that coal-heavy nations elsewhere around the world, like Russia, are currently having trouble with the stuff, Russia’s coal industry reportedly experiencing its worst crisis in 30 years due in part to sanctions, in part to a lack of demand from previous customers that’re transitioning away from coal, and in part due to issues within the industry, itself.

Coal production in Russia dropped by 6.7% year on year in July of 2024, marking the lowest output since the height of the covid pandemic, and it’s estimated that they’ve lost around 27% of monthly output compared to recent peaks.

There are different types and grades of coal, so those numbers are averages, and not all coal-exporting nations are having as much trouble as Russia right now. Australia is the world’s foremost exporter of coal, for instance, and while China is going through some economic complications right now—which is an issue for Australia, because they shipped the majority of their coal to China until just recently—India has been stepping in to pick up the majority of that slack. 

Australia has still cut its coal export outlook by 6% because of those and other geopolitical ripples, and there’s a chance their sales could continue to drop due to the transition to renewables on one hand, and the move toward gas-powered plants on the other.

But some types of coal remain the cheapest form of energy production in some countries, so there’s a good chance that rising stars like India, and possibly Indonesia and other Southeast Asian booming economies, as well, could step in and grab what they can, despite all the downsides of coal, because they can get it at a discount; which won’t be great for coal companies that are used to higher prices, but it likely will allow them to keep operating at something close to their previous capacity for longer than would otherwise be the case, lacking these rising nations that need cheap fuel, whatever the consequences of using it.

In the UK, though, coal is gone, and the remnants of its use are slowly being wiped away: the land cleaned up and repurposed, more of the grid being optimized for cleaner production types.

We’ll probably see a few other big nations accomplish the same over the next decade, but because of all that aforementioned geopolitical turmoil, there’s also a chance those planned end-dates will be pushed: the cheap, dirty needs of the present overshadowing these nations’ cleaner, healthier next-step ambitions.

Show Notes

https://www.eia.gov/tools/faqs/faq.php?id=107&t=3

https://e360.yale.edu/digest/uk-last-coal-plant

https://ourworldindata.org/grapher/electricity-mix-uk?stackMode=absolute&facet=none

https://www.wsj.com/us-news/coal-ash-cancer-epa-north-carolina-b39ddf6a

https://beyondfossilfuels.org/europes-coal-exit/

https://www.npr.org/2024/09/30/nx-s1-5133426/uk-quits-coal-climate-change

https://www.theguardian.com/business/2024/sep/30/end-of-an-era-as-britains-last-coal-fired-power-plant-shuts-down

https://www.epa.gov/sites/default/files/2016-06/documents/4783_plant_decommissioning_remediation_and_redevelopment_508.pdf

https://www.gisreportsonline.com/r/peak-coal/

https://www.moscowtimes.ru/2024/10/07/samii-tyazhelii-krizis-za30-let-vrossii-nachala-rushitsya-dobicha-uglya-a144209

https://interactive.carbonbrief.org/coal-phaseout-UK/index.html

https://www.bbc.com/news/articles/c5y35qz73n8o

https://www.nytimes.com/2024/09/30/climate/britain-last-coal-power-plant.html

https://www.washingtonpost.com/climate-environment/interactive/2024/uk-coal-power-exit/

https://www.theguardian.com/business/2024/sep/30/the-deep-history-of-british-coal-from-the-romans-to-the-ratcliffe-shutdown

https://www.reuters.com/markets/commodities/uks-last-coal-plant-shutdown-bodes-well-us-lng-exports-maguire-2024-10-01/

https://www.wired.com/story/uk-no-coal-fired-power-plants-first-time-in-142-years/

https://www.statista.com/statistics/371069/employment-in-coal-mining-industry-in-the-united-kingdom-uk/

https://apnews.com/article/high-court-rejects-uk-coal-mine-whitehaven-83b9b7ceedebee1b70927667987b4dd7

https://www.bbc.com/future/article/20240927-how-coal-fired-power-stations-are-being-turned-into-batteries

https://www.reuters.com/sustainability/climate-energy/britain-become-first-g7-country-end-coal-power-last-plant-closes-2024-09-29/

https://www.nytimes.com/2024/09/30/opinion/england-coal-wind-power.html

https://en.wikipedia.org/wiki/Coal-fired_power_station

https://en.wikipedia.org/wiki/Coal_in_Australia

https://en.wikipedia.org/wiki/Industrial_Revolution

https://en.wikipedia.org/wiki/Coal

This week we talk about Joe Rogan, Call Her Daddy, and podcast monetization.

We also discuss Kamala Harris, Donald Trump, and double-haters.

Recommended Book: You Sexy Thing by Cat Rambo

Transcript

In the world of US politics, double-haters are potential voters who really just don’t like the candidate from either major political party, and thus they decide whether and how to vote based on who they dislike least—or in some cases who they would like to hurt, the most.

This isn’t a uniquely American concept, as voters in many global democracies face similar situations, but it seems to be an especially pressing issue in this year’s upcoming US Presidential election—and election day is a week away as of the day this episode goes live—because the race is just so, so close, according to most trusted polls.

In that same context, swing states are states that could swing either way, theoretically at least, in terms of who their votes go to, and because these swing states contain enough electoral college votes to allow even the candidate who doesn’t win the popular vote to win the presidency, that makes them especially vital battlegrounds.

So there’s a scramble going on right now, for both parties, to muster their existing bases, to shore-up some of the demographic groups they’re relying upon in this election, and to get their messaging in front of as many of those double-haters and other undecideds as possible so as to maybe, possibly swing this neck-and-neck race in their direction.

Toward that end, we’ve seen simply staggering sums of money pulled in and spent by both major parties’ campaigns: it’s looking likely that this will be the most expensive election season in US history, with just under $16 billion in spending across federal races, alone—which is up from just over $15 billion in 2020, according to nonpartisan group Open Secrets; that actually means this election will probably end up being just a smidgeon cheaper than 2020’s election, if you adjust for inflation, rather than comparing in absolute dollar terms, but both of these races will have been several times as expensive as previous elections, weighing in at about double 2016’s cost, and triple what these races tended to cost previously, in the early 2000s.

For perspective, too, US elections were already quite a lot more expensive than elections held in other wealthy countries.

According to a rundown by the Wall Street Journal, Canada’s 2021 election only cost something like $69 million in inflated-adjusted dollars, and US elections tend to cost about 40-times more, per person—so this is a population-scaled figure—than elections in the UK and Germany.

The cost of local elections in the US have been increasing, as well, in some cases substantially, and that’s part of why unpaid exposure and promotion is becoming increasingly valuable: it takes a lot of communications oomph to puncture the hubbub of commercial marketing messages in the US, and while pulling in a lot of money to buy ads and fund other promotional efforts is one way to do that, it’s also possible to approach the problem asymmetrically, going to people where they already are, basically, and getting some of that valuable face-time without having to spend a cent on it.

And that’s what I’d like to talk about today—specifically, efforts by candidates to get on popular podcasts, and why this medium in particular seems to be the go-to for campaigns at a moment in which the electoral stakes are historically high.

—

Podcasts, by traditional definition, are audio files delivered using an old-school, open technology called RSS.

In the years since they first emerged, beginning in the early days of the 2000s, the transmission mechanisms for these audio files have become a bit more sophisticated, despite being based on essentially the same technology. They’ve been joined, though, by utilities that allow folks to stream undownloaded audio content, to ping the servers where these audio files are stored more regularly, and to attach all kinds of interesting and useful metadata to these files, which add more context to them, while also providing the fundaments of basic micropayment schemes and the capacity to include video versions of an episode, alongside audio.

That video component has been pushed forward in part by the success of content-makers on YouTube, where for a long while podcasters have promoted their audio shows with visualized snippets, behind-the-scenes videos, and other such add-on content. Over the past handful of years, though, it has also become a hotbed of original video podcast content, some podcasters even using YouTube as their native distribution client—and that, combined with Spotify’s decision to start offering video podcasting content alongside audio podcasting content, in part to compete with YouTube, has pushed video-podders to the forefront of many charts.

Multi-person conversational and interview shows have maybe benefitted most from that shift toward video, as being able to see the people recording these shows, and to watch their body language, all the little microexpressions and other components of conversation and social dynamics that are left out of pure audio shows, has helped them attract more listeners / viewers, while also making these shows an even more potent source of parasocial camaraderie—which was especially valuable during the lockdown-heavy phase of the covid-19 pandemic, but which is also arguably a valuable thing to provide at a period in which a lot of people across all demographics are suffering from intense loneliness and a perceived lack of connection; the sense of familiarity that folks felt listening to a familiar voice in their ear on a regular basis has been emphasized still-further by the ability to see those people on their phones, TVs, and laptops in the same way, and at the same regular cadence.

The business model of podcasting has also contributed to the expansion of this type of show, as while podcasting has never been as big and spendy an industry as comparable broadcast mediums, it has been growing, with most shows leaning on some combination of ads, sponsorships, memberships, patronage models, and subscriptions to keep their operations in the black.

Some shows make use of many or all of these income-generation approaches, and many of them have varied their business models based on the boom and bust phases the industry has seen over the years; so when ad revenue plummets, formerly ad-heavy shows will pivot to memberships, and when the listener membership well grows shallow, they might shift to some kind of featured sponsor model.

As of early 2024, there are more than half a billion regular podcast listeners, globally, and ad spending in this space, globally, reached over $4 billion for the first time this year.

That aforementioned shift toward video has tilted a lot of listening in that direction, with about a third of all podcast listeners in the US also watching at least one podcast, rather than just listening to it.

That watchability component has also nudged YouTube and Spotify into the lead in terms of podcast delivery, alongside Apple, which didn’t invent the podcast, even though the medium is named after their iPod product, but they did bring it to the forefront and make it widely available—Apple’s relative lack of investment in this space, for years, left the doors open for those other competitors, and again, their decision to feature video podcast content alongside pure audio shows has shifted the landscape of this industry substantially, raising questions about what a podcast even is, if any old YouTube show could also theoretically be categorized as such; it’s a blurry distinction at this point, a bit like the debate over whether audiobooks should be considered books, or if only written, visual versions should bear that label.

Also worth noting here is that nearly half, about 47%, of all US citizens ages 12 and up listen to a podcast at least once a month, and 34% listen every week.

11% of that demographic’s daily audio-time is spent listening to podcasts, which is quadruple the figure a decade ago, in 2014, and 23% of weekly podcast listeners in the US spend 10 or more hours with these shows each week, though the average listening time each week is also pretty high, weighing in at 7.4 hours.

Podcasts have diverse audiences and hit a range of economic classes and people of varying education levels—though it leans slightly higher than the average in terms of both educational attainment and income—and interestingly, folks seem to be especially influenced by podcast recommendations, 46% of weekly podcast listeners reporting that they purchased something based on a recommendation or advertisement they heard on a show.

All of which points at why podcasts, and especially interview podcasts, and even more especially video-heavy interview podcasts, have become such highly desired media real estate in this year’s US presidential election; these sorts of shows aren’t always the most desired medium for brands, because tracking return on investment, money earned per dollar spent, is difficult with podcasts compared to, for instance, buying ads on streaming TV shows or social media, but they’re great for raising awareness and general brand-building efforts, which is exactly what these candidates and their parties are aiming for.

So more people are listening to these things, people tend to trust what they hear on podcasts more than on other types of media, and the demographics these shows reach are highly desirable, politically.

This is why, over the past few weeks, candidates Kamala Harris and Donald Trump have appeared on some of the biggest podcasts in existence, right now: Call Her Daddy for the former, and the Joe Rogan Experience for the latter.

Both of these appearances were ostensibly pretty risky, as podcast interviewers tend to color outside the lines compared to hosts on conventional television or radio shows, but the potential upsides were huge for both, as Alex Cooper, the host of Call Her Daddy, which is kind of a comedic advice show, has become a massive force in the world of women’s issues, and she recently became one of the best-paid and most influential podcasters in the world by leaving Spotify for SiriusXM, that change beginning in 2025, for a reported $100 million.

Joe Rogan, in contrast, has consistently been the number one podcast in the world for years, and his audience skews toward the people Trump wants to reach: the listening base is 80% male, more than half of those listeners are ages 18-34, more than a third identify as Independents, politically, and a little over a quarter are Democrats who might be convinced to switch sides for this election, because of Rogan’s somewhat conservative-leaning, independent stance on most things.

Trump recorded a 3-hour podcast interview with Rogan, leaning into the host’s chilled-out, but often heavy and asymmetric-question laden format, and that was blasted out to the show’s 14.5 million Spotify followers and 17.5 million YouTube subscribers.

Call Her Daddy is the second-biggest podcast on most networks after Rogan’s show, and while it has a comparably meager 5 million weekly listeners, the show’s demographics lean heavily toward women, and especially young women, which is seemingly favorable to the messaging Harris wants to megaphone at this point in her campaign; she’s rounded-out that appearance with appearances on other shows, like All The Smoke, which is hosted by a pair of NBA stars, and The Breakfast Club, which is hosted by the popular personality, Charlamagne Tha God.

Trump has appeared on quite a few podcasts of late, as well, though they’ve largely been in the same demographic vein as Joe Rogan—Trump went on YouTuber Logan Paul’s show, Impaulsive, for instance, alongside This Past Weekened with Theo Von and the Lex Fridman Podcast—all shows that lean heavily toward the young, male demographic, and which skew somewhat conservative and/or the libertarian side of independent.

Like many aspects of this election, we don’t really know if these bets will pay off for these candidates and their campaigns. There’s a lot to suggest that folks trust podcasts and podcasters, and that this industry may therefore be an excellent means of blasting a message to the right people, allowing politicians to realize a huge return on the time they invest preparing for their appearances and recording these interviews.

On the other hand, there’s a chance that, like many supposed means of reinforcing brand awareness and identity, that the numbers are kind of fuzzy and don’t necessarily reflect the reality many people think they reflect: it could be that folks tune in, listen, and then don’t do anything with what they learn; a more passive means of engagement that results few, if any, real-world conseqences.

It could also be that one or the other, or both of these parties aimed at the wrong audiences, or at the wrong influencers to help them reach those audiences, which could result in the same outcome, but with their demographic assumptions to blame, rather than the nature of the medium.

We won’t know for sure until after the election, and even then it’ll still be an open question, because it’s difficult to definitely link action to outcome when it comes to this facet of the political world.

That said, it does seem pretty likely, that for the next few elections, at least, podcasters will carry somewhat higher credibility and weight, and consequently attract even more attention, and probably ad-dollars, too, because it’s becoming more and more difficult to reach the right people, the right potential voters, and podcasts are still new and wild westy enough that they could break through the hubbub, even when other content types struggle to do so.

Show Notes

https://www.bbc.com/news/articles/cy8nn0913e8o

https://backlinko.com/podcast-stats

https://www.insideradio.com/free/candidates-embrace-podcasts-but-is-it-working-here-s-what-one-survey-shows/article_b8858d76-92a8-11ef-9063-13e0c716cedd.html

https://www.npr.org/2024/10/27/nx-s1-5162304/politics-chat-trump-gives-3-hour-joe-rogan-interview-harris-leans-on-fascist-label

https://www.aljazeera.com/news/2024/10/23/trump-harris-turn-to-podcasts-and-maybe-joe-rogan-for-us-election-boost

https://www.elle.com/uk/life-and-culture/culture/a62526922/kamala-harris-call-her-daddy/

https://www.quillpodcasting.com/blog-posts/podcast-stats-and-facts-2024

https://soundsprofitable.com/research/the-podcast-landscape-2024/

https://www.edisonresearch.com/the-podcast-consumer-2024-by-edison-research/

https://finance.yahoo.com/news/alex-cooper-lands-100-million-143000863.html

https://en.wikipedia.org/wiki/Call_Her_Daddy

https://www.edisonresearch.com/the-race-to-rogan-who-will-candidates-reach-on-americas-top-podcast/

https://www.washingtonpost.com/elections/2024/10/25/trump-joe-rogan-podcast-interview/

https://time.com/7099104/presidential-podcast-media-tour-donald-trump-kamala-harris/

https://www.hollywoodreporter.com/business/digital/alex-cooper-interview-call-her-daddy-1236023570/

https://apnews.com/article/trump-election-lies-rogan-interview-ballots-voting-c8c06eb608c1b1ae8ca0e93ec1022b02

https://www.wsj.com/politics/elections/elections-cost-us-highest-spend-b8475961

https://www.politico.com/news/magazine/2024/10/21/meet-the-worlds-double-haters-00184634

https://www.washingtonpost.com/politics/2024/10/25/wisconsin-swing-state-undecided-voters-trump-harris/

This week we talk about DJT, Polymarket, and Kalshi.

We also discuss sports betting, gambling, and PredictIt.

Recommended Book: Build, Baby, Build by Bryan Caplan

Transcript

Trump Media & Technology Group, which trades under the stock ticker DJT, has seen some wild swings since it became a publicly tradable business entity in late-March of 2024.

The Florida-based holding company for Truth Social, a Twitter-clone that was released in early 2022 following former President Donald Trump’s ousting from Twitter—that ousting the result of his denial of his loss in the 2020 presidential election—is a bit of an odd-bird in the technology and media space, as while it’s ostensibly an umbrella corporation for many possible Trump-themed business entities, Truth Social is the only one that’s gotten off the ground so far, and that platform hasn’t done well in traditional business or even aspirational tech-business terms: a financial disclosure in November of 2023 indicated that the network had tallied a cumulative loss of at least $31.5 million since it was launched, and the holding company’s numbers were even worse: when they filed their regulatory paperwork in March of 2024, they noted that Trump Media & Technology Group had lost $327.6 million, while making a mere $770,000 in revenue.

Those kinds of numbers, the company hemorrhaging money, would be a huge problem if DJT was a typical media business, or business of any kind, really. But for most people who invest in the company’s stock, this entity seems to be less a traditional stock holding, like you might buy shares of NVIDIA or Coca-Cola, hoping to earn dividends or see the value of the stock increase over time based on the performance and assumed future performance of the company in question, but instead it seems to operate as a means of betting on Trump and his political aspirations: many people who have been asked why they’re buying the stock of a clearly fumbling company say that they do it because they like Trump and what he stands for, and some have suggested they assume the stock will do much better if and when he’s back in office.

Other entities, especially those who oppose Trump and his politics, have pointed out that this publicly traded business provides foreign and US entities an easy, and easily deniable means of basically bribing Trump—or getting on his good side, if you want to use less charged language—as they could simply, and legally pick up a large number of shares, raising the price of the stock, which in turn increases the size of Trump’s fortune, which he could then, if he so chooses, cash out of at some point, but in the mean time this allows him to do the more typical rich person thing and just borrow money against the non-money, stock assets he owns.

All of which would be difficult to prove, which is part of why this would, in theory, be an excellent means of funneling money to someone who might hold the reins of power in the near-future, if one were so inclined to do so.

But at the moment that’s all speculation, and with ongoing investigations into other purported bribery schemes on the part of Trump and his campaign, it’s not clear that Trump would need DJT in order to get money into his coffers, as more direct approaches—like simply depositing ten million dollars into his campaign account from Egypt’s state-run bank, seem more straightforward, and just as unlikely to result in any kind of pushback from the US’s oversight panels, based on how they’ve addressed that particular accusation so far, at least.

Of course, some people are simply looking for points of leverage anywhere they can find it, not for political or regulatory manipulation purposes, but to earn money by gambling on assets that change value in dramatic and seemingly predictable ways.

For day traders and other arbitrage-seekers, then, a stock that goes up and down based on the perceived successes and failures of a public figure who’s constantly saying and doing things that can be construed in different ways by different people is an appealing target, even lacking a political motivation for tracking (and perhaps even influencing, to a limited degree) those numbers.

What I’d like to talk about today is another type of political betting, and how a recent court case may make politics in the US a lot more tumultuous, maybe more measurable, and possibly more profitable, for some.

—

In mid-2021, a New York-based online prediction market called Kalshi launched in the US, and this service was meant to serve as a platform through which users could place bets—in the form of trades—on all sorts of things, ranging from when the Fed would next cut interest rates, and by how much, to who would win various global awards, like the Nobel in chemistry.

Bets can only be placed on yes or no questions, which shapes the nature of said questions, and delineates the sorts of questions that can be asked, and in general the platform pays out a dollar for each winning contract—so if you buy one contract saying the Republican party will control the House after November’s election, and they do, you would win a dollar, but if they don’t, you would lose whatever money you spent to buy that contract—and these contracts can be purchased for sums that are based on how likely the event is currently expected to be: so if there’s a low chance, based on all available variables, that the Republicans will take the House, that contract might cost substantially less than a dollar to purchase, whereas if it’s likely they’ll take it, it would cost close to a dollar—so the payout is larger for events considered to be unlikely.

The original idea behind Kalshi, and similar platforms, of which there are many, operating in many different places around the world, was to provide investors with a hedge against events that are otherwise difficult to work into one’s asset portfolio.

It’s relatively simple to have a bunch of bets that will pay out big time if the US economy does well, for instance, and simple enough to buy counter-bets that will pay out decently well if it does badly—many investors buying some of each, so they’re not wiped out, no matter what happens—but there are all sorts of things that can mess with one’s otherwise well-balanced investment strategies, like the emergence of global pandemics and the surprise decision of the UK to leave the European Union.

If you can place bets that will pay out big-time when unlikely things happen, though, that can help re-balance a financial loss that arises from the occurrence of said unlikely events; if you lose a bunch of money from your stock portfolio because the UK voted for Brexit, but you also bought a bunch of contracts on this kind of market that would pay out substantially if Brexit was successful, you’ll reach a kind of equilibrium that isn’t as simple to achieve using other markets, because of how difficult it can be to directly link a stock or bond with that kind of not-directly-financial event.

So Kalshi pitched itself as that kind of alternative asset market, predicated on bets, but while they had a license from the US Commodities Futures Trading Commission, or CFTC, to function as a contract market in the States, acquired the year before they launched, their proposal to start a political prediction market, which would allow folks to bet on which party would control the US congress, was denied by the CFTC in September of 2023, the agency claiming that allowing such bets would create bad incentives in the electoral process, and that offering these sorts of contracts would violate US market regulations for derivatives.

A judge ruled in Kalshi’s favor a year later, in September of 2024, saying that the agency had exceeded its authority in banning this type of contract-issuance by Kalshi, and while the CFTC attempted to stall that component of their market’s implementation, on October 2 of this year, a federal appeals court ruled in Kalshi’s favor, and the platform was thus formally allowed to offer contracts that served as a betting market for US politics on which actual money could be lost and earned.

That last point is important, as throughout this process, and even before Kalshi was launched, other betting markets have been common, including those that have allowed bets on US political happenings.

It’s just that the majority of them, and the ones that have persisted and grown in the US in particular, haven’t allowed folks to bet actual money on these things: they’ve allowed, in some cases, the betting of on-platform tokens, which represent credibility, not money, though a few money-trading entities, like PredictIt, have been on the agency’s radar, but in PredictiIt’s case, it was granted what amounts to a “we won’t take action against you, despite what you’re doing being questionable” letter from the CFTC, which until Kalshi’s case turned out in their favor, meant PredictIt was one of the few, large-scale, reputable real-money political prediction markets available in the US.

Not all such markets have been so lucky, but that luck has been highly correlated with their approach to handling money, the structure of the company, and the degree to which they’ve been willing to play ball with the CFTC and other interested agencies.

All that said, we’ve reached an interesting point in which these markets have conceivably become more serious and useful, because rather than relying on not-real tokens that have no actual value to anyone—so you could create an account on one of these sites, bet all your tokens on a silly position that makes no sense, and suffer no consequences for that bet—we now have platforms that allow folks to put their money where their beliefs are, which in turn should theoretically make these markets more reliable in terms of showing what a certain segment of the population actually believes; how likely different candidates are to win, different parties are to hold Congress, and how likely various bills are to be passed into law.

Interestingly, though, that theory may already be destined for the dustbin, as one of the larger betting platforms, Polymarket—which allows folks to place bets on all sorts of things using a crypto asset called USDC, and which isn’t regulated by the CFTC because its operations are not based in the US—is experiencing what looks like market manipulation, possibly meant to sway poll forecasts that take these sorts of markets into account.

What that means in practice is that of the nearly $2 billion in bets that have been placed on the outcome of the upcoming US presidential election on Polymarket, as of the day I’m recording this, about $30 million seems to have been recently bet by just four accounts, all of which have behaved so similarly that a report from the Wall Street Journal posits that they might be the same person, or a collection of people operating alongside each other.

In any case, the net-impact of this investment, which landed in late-October, was to bump Trump’s odds of winning to 60% from where it was previously, at 53.3%.

There’s a chance, of course, that this is just the result of a person or some people with money wanting to earn what they consider to be an easy buck, betting on the candidate they think is most likely to win, and there’s also a chance that they’re plowing that money into this bet in order to show support for their favored candidate.

But there’s also a chance that this is the first example, at this scale at least, of betting market manipulation that’s sizable enough to shift the balance of polls that take betting market numbers into consideration.

Some of the poll predictions you in see in the news work these numbers from these betting markets into their formulae alongside the findings of more conventional polling entities, basically, so if you have tens of millions of dollars to throw into this kind of market, you can bump your favored candidate’s seeming chances significantly higher, which then in turn can make it seem like that candidate has achieved a surge in support more broadly—despite that seeming support actually just having been bought and paid for by one or a few enthused supporters on this kind of market.

So if it does turn out that this is a conscious effort on someone’s part to shift perceptions of the election—maybe big-time Trump fans, maybe someone affiliated with him or one of the PACs trying to get him elected—that could be a big deal, especially considering that Trump and his people have said that they won’t accept the outcome of the election if they don’t win, and if they can show strong expectations, or seeming expectations in the shape of favorable poll numbers that their candidate was meant to win, that could be a point of seeming evidence in favor of their argument that there was voter manipulation by their opponent; this of course wouldn’t be the case, but because of how the news, and even more so social media platforms, sometimes present superficial versions of what’s actually happening, seeing the candidate who had 60% support lose could seem like a valid argument at a highly charged post-election moment, despite all the other evidence to the contrary.

One more important point to make here is that election markets don’t actually represent probabilities—they represent a relatively small population of people’s expectations or hopes about what will happen.

It’s in the interest of these markets to imply that there’s substantial meaning and real-deal data in their numbers, but that’s mostly marketing copy to try to get more people involved; at the end of the day, these markets are often wrong, are populated by outliers who don’t represent the voting public, and in many cases they’re heavily biased in all sorts of directions—some of them more popular with folks on the left, some more popular with folks on the right, and some more popular with folks who just love making big bets that feel like gambling, and in some cases creating chaos or funny outcomes just for laughs.

On that final point, it’s worth mentioning that sports gambling has recently become legal, to some degree at least, across much of the United States, and this has already become a huge industry, representing an expected $14.3 billion in 2024, alone, with an anticipated annual growth of something like 10%, which is astonishing for something that was mostly illegal until just recently—the Supreme Court decision that paved the way for it as a nation-spanning market was only made in 2018.

So there’s a chance that these prediction markets will boom, as there’s clearly an appetite for betting on stuff in the US, as a form of entertainment, as a means to try to get ahead, and potentially as a way to put one’s money where one’s mouth is.

Though all of these incentives and purposes could potentially make these markets less valuable for political researchers hoping to better understand odds, as the incentives may or may not align with those that lead to more accurate predictions, and there’s no way to really know how those post-money-injection numbers will align with actual voting tallies, or fail to do so, until we have more data about this and other near-future elections’ outcomes.

Show Notes

https://www.wsj.com/finance/investing/how-investors-are-betting-on-the-election-from-utility-stocks-to-djt-c2b9e838

https://www.yahoo.com/news/hes-sale-trump-djt-stock-001901595.html

https://www.cnbc.com/2024/09/03/trump-egypt-democrats-letter.html

https://en.wikipedia.org/wiki/Truth_Social

https://www.axios.com/2024/09/10/prediction-markets-election

https://stanfordreview.org/kalshis-court-victory-a-turning-point-for-prediction-markets-2/

https://www.politico.com/news/2024/10/04/harris-trump-election-betting-00182432

https://en.wikipedia.org/wiki/Prediction_market

https://www.investopedia.com/terms/p/prediction-market.asp

https://www.axios.com/2024/09/16/prediction-markets-election

https://asteriskmag.com/issues/05/prediction-markets-have-an-elections-problem-jeremiah-johnson

https://www.chapman.edu/esi/wp/porter_affectingpolicymanipulatingpredictionmarkets.pdf

https://www.ft.com/content/82199ea0-9707-4d37-b4c4-b65a65d17ecb

https://worksinprogress.co/issue/why-prediction-markets-arent-popular/

https://www.wsj.com/finance/betting-election-pro-trump-ad74aa71

https://www.washingtonpost.com/technology/2024/10/19/election-betting-trump-harris-odds-polymarket-predictit/

https://www.wsj.com/finance/investing/how-investors-are-betting-on-the-election-from-utility-stocks-to-djt-c2b9e838

https://www.wsj.com/livecoverage/stock-market-today-dow-sp500-nasdaq-live-10-03-2024/card/betting-markets-on-the-presidential-race-set-to-go-live-NnRne85QCyVAnc9nZy8z

https://www.wsj.com/finance/regulation/are-you-ready-to-bet-on-u-s-elections-a-judges-ruling-opens-the-door-556abc73

https://en.wikipedia.org/wiki/Kalshi

https://www.coindesk.com/policy/2024/09/13/kalshis-new-political-prediction-markets-halted-as-cftc-appeals-loss/

https://www.brookings.edu/articles/how-betting-platform-predictits-legal-struggle-could-hamper-regulators-and-hurt-regulated-firms/

https://www.wsj.com/finance/betting-election-pro-trump-ad74aa71

https://en.wikipedia.org/wiki/Polymarket

https://www.statista.com/outlook/amo/online-gambling/online-sports-betting/united-states

This week we talk about the HoloLens, the Apple Vision Pro, and the Meta Ray-Ban Smart Glasses.

We also discuss augmented reality, virtual reality, and Orion.

Recommended Book: The Mountain in the Sea by Ray Nayler

Transcript

Originally released as a development device in 2016—so aimed at folks who make software, primarily, not at the general public—the HoloLens, made by Microsoft, was a fairly innovative device that looked like virtual reality headgear, but which allowed folks to interact with graphical elements overlayed on a transparent surface so that they seemed to be positioned within the real world; so-called augmented reality.

This functionality relied upon some of the tech Microsoft had developed for its earlier Kinect accessory, which allowed Xbox owners to play games using their bodies instead of more conventional controllers—it used a camera to figure out where people, and their arms, legs, and so on, were in space, and that helped this new team figure out how to map a person’s living room, for instance, in order to place graphical elements throughout that room when viewed through the HoloLens’ lenses; so stuff could appear behind your couch, pop out of a wall, or seem to be perched atop a table.

The HoloLens was not the only option in this space, as several other companies, including other tech titans, but also startups like Magic Leap, were making similar devices, but it was arguably the most successful in the sense that it both developed this augmented reality technology fairly rapidly, and in the sense that it was able to negotiate collaborations and business relationships with entities like NASA, the US Military, and Autodesk—in some cases ensuring their hardware and software would play well with the hardware and software most commonly used in offices around the world, and in some cases showcasing the device’s capabilities for potential scientific, defense, and next-step exploratory purposes.

Like many new devices, Microsoft positioned the HoloLens, early on, as a potential hub for entertainment, launching it with a bunch of games and movie-like experiences that took advantage of its ability to adapt those entertainments to the spaces in which the end-user would consumer them: having enemies pop out of a wall in the user’s kitchen, for instance, or projecting a movie screen on their ceiling.

It was also pitched as a training tool, though, giving would-be astronauts the ability to practice working with tools in space, or helping doctors-in-training go through digital surgeries with realistic-looking patients before they ever got their hands dirty in real life. And the company leaned into that market with the second edition of the headset, which was announced and made available for pre-order in early-2019, optimizing it even further for enterprise purposes with a slew of upgrades, and pricing it accordingly, at $3,500.

Among those upgrades was better overall hardware with higher-end specs, but it also did away with controllers and instead reoriented entirely toward eye- and hand-tracking options, combined with voice controls, allowing the user to speak their commands and use hand-gestures to interact with the digital things projected over the real-world spaces they inhabited.

The original model also had basic hand-tracking functionality, but the new model expanded those capabilities substantially, while also expanding upon the first edition’s fairly meager 30 degrees of augmented view: a relatively small portion of the user’s line of sight could be filled with graphics, in other words, and the new version upgraded that to 52 degrees; so still not wall to wall interact-with-able graphics, but a significant upgrade.

Unfortunately for fans of the HoloLens, Microsoft recently confirmed that they have ended production of their second generation device, and that while they will continue to issue security updates and support for their existing customers, like the US Department of Defense, they haven’t announced a replacement for it—which could mean they’re getting out of this space entirely.

Which is interesting in the sense that this is a space, the world of augmented reality, which some newer entrants are rebranding as mixed reality, that seems to be blowing up right now: two of Microsoft’s main competitors are throwing a lot of money and credibility into their own offerings, and pitching this type of hardware as the next-step in personal devices.

Some analysts have posited, though, that Microsoft maybe just got into this now-burgeoning arena just a little too early, investing in some truly compelling innovations, but doing so at a moment in which the cost was too high to justify the eventual output, and now they might be ceding the space to their competition rather than doubling-down on something they don’t think will pay off for them, or they may be approaching it from another angle entirely, going back to the drawing board and focusing on new innovations that will bypass the HoloLens brand entirely.

What I’d like to talk about today are the offerings we’re seeing from those other brands, and what seems to be happening, and may happen in the near-future, in this augmented-reality, mixed-reality segment of the tech world.

—

I did an episode on spacial computing and the Apple Vision Pro back when the device was made available for purchase in the US, in February of 2024.

This device was considered to be a pretty big deal because of who was making it, Apple, which has a fairly solid record of making new devices with unfamiliar interfaces popular and even common, and because the approach they were taking: basically throwing a lot of money at this thing, and charging accordingly, around $3,500, which is the same price the second HoloLens was being sold for, as I noted in the intro.

But because of that high price point, they were able to load this thing up with all sorts of bells and whistles, some of which were fundamental to its functionality—like super-high-density lenses that helped prevent nausea and other sorts of discord in their users—and some that were maybe just interesting experiments, like projecting a live video of the user’s eyes, which are concealed by the headset, on the front of the headset, which to me is a somewhat spooky and silly effect, but which is nonetheless technically impressive, and is something that seems aimed at making these things less anti-social, because you can wear the Vision Pro and still see people, and this projection of their eyes allows them to see you and your facial expression at the same time.

I’ve actually had the chance to use this device since that episode went live, and while there are a lot of weird little limitations and hindrances to this device going mainstream at the moment, the technology works surprisingly well right out of the box, with the eye- and hand-tracking elements working shockingly, almost magically well for relatively early-edition tech; Apple is pretty good at making novel user-interfaces intuitive, and that component of this device, at least, seemed like a slam dunk to me—for casual use-cases, at least.

That said, the company has been criticized for that high price point and their seeming fixation on things like putting the users’ eyes on the outside of the headset, rather than, for instance, investing in more content and figuring out how to make the thing more comfortable for long periods of time—a common complaint with basically every virtual reality or mixed-reality headset ever developed, because of the sheer amount of hardware that has to be crammed into a finite, head-and-face-mounted space, that space also needing to be properly balanced, and it can’t get too hot, for perhaps obvious reasons.

Those criticisms related to price are the result not of comparison to HoloLens, as again, the pricing is basically the same between these two devices, but instead the result of what Meta has done with their mixed-reality offerings, which are based on products and technology they acquired when they bought Oculus Labs; they’ve leaned into providing virtual reality devices for the low- and mid-market consumer, and their newest model, the Meta Quest 3S is a stand-alone device that costs between about $300 and $400, and it has mixed-reality functionality, similar to the Vision Pro and HoloLens.

While Meta’s Quest line doesn’t have anywhere near the specs and polish of the Vision Pro, then, and while it didn’t arrive as early as the HoloLens, only hitting shelves quite recently, it does provide enough functionality and serves enough peoples’ purposes, and at a far lower price point, that it, along with its other Quest-line kin, has managed to gobble up a lot of market share, especially in the consumer mixed-reality arena, because far more people are willing to take a bet on a newer technology with questionable utility that costs $300 compared to one that costs them more than ten-times as much.

Interestingly, though, while Meta’s Reality Labs sub-brand seems to be doing decently well with their Quest line of headsets, a product that they made in collaboration with glasses and sunglasses company EssilorLuxottica, which owns a huge chunk of the total glasses and sunglasses global market, via their many sub-brands, may end up being the more popular and widely used device, at least for the foreseeable future.

The Ray-Ban Meta Smartglasses looks almost exactly like traditional, Ray-Ban sunglasses, but with slightly bulkier arms and with camera lenses built into the frames near where the arms connect to them.

If you’re not looking carefully, then, these things can be easily mistaken for just normal old Ray-Bans, but they are smartglasses in that they contain those two cameras on the front, alongside open-air speakers, a microphone, and a touchpad, all of which allow the wearer to interact with and use them in various ways, including listening to music and talking on the phone, but also taking photos of what they’re looking at, recording video of the same, and asking an AI chatbot questions like, what type of flower is this, and getting an audible answer.

These things cost around what you would pay for a Quest headset: something like $300-400, but their functionality is very different: they don’t project graphics to overlay the user’s view, in that regard they function like normal sunglasses or prescription glasses, but if you want to snap a photo, livestream whatever it is you’re seeing, or ask a question, you can do that using a combination of vocal commands and interacting with the built-in touchpad.

And while this isn’t the mixed-reality that many of us might think of when we hear that term, it’s still the same general concept, as it allows the user to engage with technology in real-life, in the real-world, overlaying the real world with digital, easily accessed, internet-derived information and other utilities. And it manages to do so without looking super obtrusive, like earlier versions of the same concept—Google’s Google Glass smartglasses come to mind, which were earlier versions of basically the same idea, but with some limited graphical overlay options, and in a form factor that made the wearer look like an awkward, somewhat creepy cyborg.

Snap, the parent company of Snapchat, has a similar offering which originally leaned into the same “these look just like glasses, but have little camera lenses in them” strategy, though with their newest iteration, their Spectacles smartglasses product has reoriented toward a look that’s more akin to a larger, clunkier version of the free 3d glasses you might use at the movie theater—not exactly inconspicuous, though offering much of the same functionality as Meta’s Raybans, alongside some basic graphical overlay functions: a lightweight version of what the Vision Pro and Quest offer, basically, and in a much small package.

These new Spectacles are only available for folks who sign up for the company’s developer program at the moment, however, and are purchased not as a one-off, but for $99/month, with a minimum commitment of 12 months—so the price tag is quite a bit higher than those Quests and Raybans, as well.

Interestingly, Meta’s Reality Labs recently held an event in which they showed off an arguably more advanced version of Snap’s Spectacles, called Orion.

These things are being pitched as the be-all, end-all mixed-reality solution that every company is trying to develop, but which they can’t develop yet, at least not at scale. They look like giant, cartoony glasses—they’re shaped like glasses, but comically oversized ones—and they provide many of the same benefits as today’s Quest headset, but without the large, heavy headset component; so these could theoretically be used in the real-world, not just in one’s living room or office.

The company announced this product along with the caveat that they cannot make it on scale, yet, because cramming that much functionality into such a small device is really stressing the capacity of current manufacturing technologies, and while they can build one of these glasses, with its accompanying wristband and a little controller, both of which help the glasses do what they do, in terms of compute and the user interface, for about $10,000 per unit, they could not, today, build enough of them to make it a real, sellable product, much less do so at a profit.

So this was a look at what they hope to be doing within the next decade, and basically gives them credibility as the company that’s already building what’s next—now it’s just a matter of bringing down costs, scaling up production, and making all the components smaller and more energy efficient; which is a lot of work that will take years, but is also something they should theoretically at least be able to do.

To be clear, most other big tech companies should be capable of build really snazzy, futuristic one-offs like the Orion, as well, especially if they, like Meta, offload some of the device’s functionality into accessory hardware—the Vision Pro has offloaded its battery into a somewhat clunky, pocketable appendage, for instance, and most of these devices make use of some kind of external controller, to make the user interface snappier and more accurate.

But Meta is attempting to show that this is the direction they see wearable technology going, and maybe our engagement with the digital world more holistically, as well. It’s easy to imagine a world in which we all have these sorts of capabilities built into our glasses and wristbands and other wearables, rather than having to work with flat, not-mixed-reality screens all the time, especially once you see the tech in action, even if only as a not-for-sale example.

One aspect of this potential future that Meta is forecasting is already leading to some soul-searching, though.

Some students at Harvard modified a pair of Meta Ray-Bans to use facial recognition and reverse-image search technology so they could basically look at a stranger, then learn a bunch of stuff about them really quickly, to the point that these students were able to do this, then pretend to know the that stranger, talk about their work, find their spouse’s phone number—a bunch of details that made it seem like they knew this person they’d only just met.

All of which is pretty wild and interesting, but also potentially frightening, considering that this is basically doxing someone on demand, in public, and it could be used—like many other tech innovations, granted—to enable and augment stalking or kidnapping or other such crimes.

None of which is destiny, of course. Nor is the success of this product type.

But there does seem to be a lot of interest in what these gadgets seem like they might offer, especially as the prices drop, and as more entrants carve out space in that relatively lower-cost space—which is a space Apple is reportedly planning to enter soon, too, with a new edition of their Vision Pro that would cost maybe something like half as much as the first one, and possibly smart glasses and maybe even Airpods with cameras meant for release over the next couple of years.

So it may be that the early divulgence of these next-step devices, showing us where these things might go with these higher-priced, smaller audience initial editions, could allow us to predict and prepare for some of their negative externalities before they go completely mainstream, so that when they finally arrive in their finished form, we’re a bit more prepared to enjoy the benefits while suffering fewer (though almost certainly not zero) of their potential downsides.

Show Notes

https://en.wikipedia.org/wiki/Spatial_computing

https://en.wikipedia.org/wiki/Apple_Vision_Pro

https://en.wikipedia.org/wiki/Meta_Quest_3S

https://en.wikipedia.org/wiki/Meta_Platforms

https://www.reddit.com/r/RayBanStories/comments/1e3frhc/my_honest_review_of_the_rayban_metas_as_everyday/

https://en.wikipedia.org/wiki/Ray-Ban_Meta

https://www.spectacles.com/spectacles-24?lang=en-US

https://en.wikipedia.org/wiki/Spectacles_(product)

https://forums.macrumors.com/threads/students-add-facial-recognition-to-meta-smart-glasses-to-identify-strangers-in-real-time.2438942/

https://archive.ph/6TqgF

https://www.theverge.com/24253908/meta-orion-ar-glasses-demo-mark-zuckerberg-interview

https://about.fb.com/news/2024/09/introducing-orion-our-first-true-augmented-reality-glasses/

https://www.reddit.com/r/augmentedreality/comments/1frdjt2/meta_orion_ar_glasses_the_first_deep_dive_into/

https://appleinsider.com/articles/24/10/13/cheaper-apple-vision-headset-rumored-to-cost-2000-arriving-in-2026

https://www.uploadvr.com/microsoft-discontinuing-hololens-2/

https://www.theverge.com/2024/10/1/24259369/microsoft-hololens-2-discontinuation-support

https://www.theverge.com/2022/6/7/23159049/microsoft-hololens-boss-alex-kipman-leaves-resigns-misconduct-allegations

https://en.wikipedia.org/wiki/Microsoft_HoloLens

This week we talk about the AfD, the Freedom Party, and the Identitarian Movement.

We also discuss Martin Sellner, Herbert Kickl, and racialism.

Recommended Book: The Ministry of Time by Kaliane Bradley

Transcript

Racialism, sometimes called scientific racism, is the pseudoscientific belief that groups of human beings are inherently, biologically different from each other based on different evolutionary paths that have carved up the species into different races that are distinct enough from each other to make interbreeding undesirable, and cultural exchange a dangerous hazard.

Said another way, racialism posits, using all sorts of outdated and misinterpreted scientific understandings—like determining intelligence based on the shape of a person’s skull—that black people and white Europeans and folks from Asia are different enough (which is an idea also called polygenesis) that they should stay in their own parts of the world, and that by separating everyone out according to presumed racial background, we would all be able to do as we like, based on our own alleged cultural guide rails, and in accordance with our own, alleged biological destinies; which in some cases would mean invading and killing and maybe enslaving the other, inferior, in our minds at least, races, but in the polite, political telling, usually means something like putting up walls to keep out the racially inferior riffraff, so they don’t pollute our good and pure and obvious superior bloodlines.

Important to note is that different people with genetic lineages in different parts of the world do tend to have distinct collections of biological traits, ranging from skin tone to height to propensities to, or defenses against various sorts of disease.

There’s actual no clean line between groups of people the way this theory says, though: race, the way the word is used today, references a collection of qualities that tend to be found within different groups of people, but every person is a unique collection of genetic mutations and variations, and the old-school concept of biological race has not held up to modern scientific scrutiny—it’s mostly a cultural concept at this point, and even then it’s a fairly fuzzy one.

That said, a lot of very smart people used to believe in the racialism concept back in the Enlightment era, from around the mid-1600s to the late-1700s, as science back then was helping us delineate between all sorts of species, and giving us a hint of the more complete evolutionary understandings that would arrive the following century; but as with many fields of inquiry, this initial glimpse granted us as much new confusion, masquerading as insight, as it did actual, novel understandings.

Today, this concept is almost exclusively cleaved to by folks belonging to various racial supremacist groups, including but not limited to those who are part of the so-called Identitarian Movement, which is a far-right, European nationalist ideology that spans many countries and political organizations, and which aims, among other things, to significantly truncate or end globalization, to do away with multiculturalism in all its forms, to combat what this group sees as the spread and influence of Islam across Europe, and to significantly limit or even completely end immigration of people from outside Europe into European nations.

Folks and parties that subscribe to this ideology are often considered to be ultra-conservative, but also xenophobic and racist—racism being distinct from racialism, as racialism posits there are different, hard-coded biological racial realities that cleanly delineate one group of humans from another, while racism tends to be the belief that one group of people is superior to another, with folks who are racist at times acting on that belief in various ways.

The Identitarian Movement is officially categorized as a right-ring extremist group by the German intelligence agency, and the Southern Poverty Law Center considers a slew of groups that align with this movement to be hate groups.

Though based on the writings and principles of earlier thinkers and politicians, this group is actually fairly modern, only coming into being in its current form in the early 2000s—though the collection of ideas and efforts that informed this movement arose in France in the 1960s as part of a neo-fascist effort to inject out-of-vogue, extremist ideas into respectable, post-WWII political debate.

This was essentially an effort to rebrand Nazi ideology so as to make it seem smart and with-it in the still-stunned, but rebuilding European idea marketplace, and its primary innovation was taking some of those fascist concepts and hiding them under the more palatable label of nationalism—which was experiencing a resurgence following the wave of multiculturalism that began to flourish after the war, though not without imperfections and conflict.

One of the most popular elements of this ideology, though, was introduced a fair bit later, in the early 2000s and 2010s.

Remigration refers to the idea that liberals, people on the left of the political spectrum, want to replace good, hard-working, morally correct, white French people—and later this idea was expanded to encompass all white Europeans—with folks from other countries, especially Muslim-majority countries, but also other places where folks don’t tend to be white.

These lefties are keen to do this for a variety of reasons, apparently, but one of the most popular claims is that they want to give handouts to these new arrivals, and thus get their votes, capturing the government forever by slowly reducing the overall population of the good, wholesome white locals, in order to out-populate them with new arrivals, whose votes will forever be captured by the politicians who gave them all these handouts.

Sometimes called The Great Replacement Theory, this idea serves as justification for the aforementioned, increasingly popular concept of remigration, which basically means rounding up everyone who’s living in Europe, but not originally from Europe, and shipping them elsewhere—even if they are citizens, and even if they aren’t citizens of the countries they’re being shipped to.

Some versions of this idea also say that the descendants of immigrants, folks who were born in their European homes, not elsewhere, should nonetheless be shipped back to where their grandparents came from, due to a lack of sufficient assimilation—which means taking up the culture of the place you’ve moved to, but in this case usually serves as a stand in for “has a different faith, likes different food, adheres to different norms,” and other multiculturalism-linked, distinctions.

This rounding up and shipping would be based on the person’s supposed racial identity, not on their national identity—so in a way, this concept is a means of smuggling racialism into politics, by making it seems as if the modern way of organizing the world and its people—that of nation states, and those nation states granting an identity, a national origin—is not inherent or ideal, and that we should instead force people to stay where we believe other people like them, according to our beliefs about such things, originally came from, and thus, belong.

That underlying concept isn’t one that’s taken seriously by most scientists, philosophers, demographers, or anyone else who’s profession is linked to this collection of ideas, but it’s proven to be a useful narrative and justification for folks who feel as if they’re becoming strangers in what they consider to be their homeland, their culture, their city, and so on. And that’s made it a useful point of leverage for traditionalist and conservative political parties across Europe; and increasingly, in recent years especially, elsewhere around the world, as well.

What I’d like to talk about today is a party in Austria that has leaned heavily into this collection of ideas, and which claimed the most votes in the country’s recent election, as a consequence.

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The Freedom Party, or FPO, is an Austrian political party that’s a founding member of the European-scale Identity and Democracy Party, which recently merged with other, fellow traveler parties from the Czech Republic and Hungary, to become the Patriots for Europe group; though all of these entities share roughly the same ideological platforms and practical, political ambitions.

And among those ambitions is the desire to tackle the issue of immigration across the EU, reducing especially the number of people coming into the bloc from Muslim-majority nations, which large numbers of people in many European countries have complained about, usually because they feel the cultures of their hometowns and home countries are changing rapidly, and they consequently feel like they’re being elbowed out and replaced by these newcomers.

This is not a new complaint, and this isn’t only a European thing; across history, even very modern history, when a wave of immigrants arrive in a new home, that can make the people who were there before them feel like they’re under assault—and if those new arrivals have a different religion than the majority of the people in the place they’ve immigrated to, that can increase the perceived differences and threats, as can a difference in skin color, the clothing they wear, cultural customs, foods, fragrances, language, and just about anything else.

This angle of politicking has become increasingly popular with mostly but not exclusively conservative parties around the world in recent years, though, as some of those parties have gotten pretty good at spreading this message to disaffected people, including disaffected youths, in some of the most immigrated-to places in the world.

So young men in the United States have, according to recent polls, been hearing a lot about this and seem to be open to the idea that some of the, on average, at least, issues they seem to be facing in terms of educational attainment and employment options, among other things, are the fault of those new arrivals, and that’s possibly a component of the gender-skewed shift we’re seeing in the lead-up to November’s election, with young people in general leaning liberal, but more young men leaning conservative than young women.

That’s almost certainly not the only issue at play here, of course, but it’s something conservative politicians in the US seem to be leveraging, even to the point that former president and current Republican candidate Donald Trump recently mentioned the term “remigration” in a social media post: something that’s being seen by political analysts as a trial balloon to see if the concept might be picked up by folks in his political orbit, and might in turn garner him more support amongst people who feel like too many immigrants are entering the US, and that all that immigration is bad for one of several possible, and well-promoted, reasons; maybe, this trial balloon implies, we should just ship them all back from where they came from, and that may then free up housing and jobs and maybe set things back to normal, how things used to be.

It’s worth noting that the word remigration was initially used to refer to the return of European Jews to their homes after WWII, but it was adopted by French white nationalists in the mid-2010s to allude to deporting immigrants and the children of immigrants, en masse.

The term became more widely known after an investigation found that, in late-2023, members of the Alternative for Germany, or AfD party had a secret meeting with neo-nazis, at which there was a presentation by a thirty-something far-right Austrian political activist named Martin Sellner, who among other things is the leader of the Identitarian movement I mentioned in the intro, and in that talk he supported the idea of a program that would involve identifying and removing minorities of various kinds from Germany by force—remigration, basically, a topic he’s also written a book about.

Sellner later said that his words were twisted by the media and that remigration is really just a collection of policies that would slow or stop some types of immigration in the future, but he was banned from Germany because of that talk, until a German court revoked that ban last May, and he was denied entry into the UK in 2018, and into the US in 2019 because of a large donation he received from the mass-shooter who attacked two mosques in Christchurch, New Zealand in 2019, killing 51 people and injuring 89.

Sellner himself has said that until 2011 he was a neo-nazi, and his wife, an American pro-Trump online influencer—who was a big proponent of the so-called Pizzagate conspiracy theory among other notable, and demonstrably untrue narratives that became popular in the lead up to previous elections—she spreads a lot of the same content, but with a US bent, rather than a European one.

Both Sellners, and other members of the Identitarian movement, have been accused of parroting Nazi talking points, promoting things like Holocaust denial, and calling for minorities to be mass-executed, but they generally contend that they’re simply proud nationalists who love their countries and don’t want to see them changed or ruined by a bunch of people from other places with different ideas, beliefs, and priorities coming in and taking all the jobs, and tweaking everything to suit their wants and needs, against the desires of those who were there first.

The concept of remigration has attained popularity at a more rapid rate in some places than others, and it seems to have done especially well in Austria—the country’s Freedom Party won 29% of the vote in the country’s last election in late-September of this year, and that was the highest tally of all the parties that participated; which is notable in part because of what the Freedom Party believes now, in remigration and adjacent policies, but also because this is a party that was founded in the 1950s by a former SS officer and Nazi politician.

It’s expected that the Freedom Party won’t be able to form a government, because every other party has said they won’t form a coalition with them—the currently governing conservative People’s Party has said they might be open to it, but not with Herbert Kickl, the group’s current leader, involved in the resultant government.

Kickl is an ardent ally of Russian president Putin and has been accused of attempting to meld right-wing populism with nazi-valenced, fascist extremism—a common accusation against folks in this corner of the political spectrum, though in some cases an accusation that is also seemingly true.

Like Sellner and other folks with this ideological orientation, Kickl promotes the idea of Remigration, which in the context of Austrian politics, in his mind at least, would help reinforce the strength of a Fortress Austria with completely closed borders and which is run by an all-powerful security state apparatus, that is capable of managing those borders, and keeping the peace inside the nation’s impermeable walls.

Kickl has said, in the wake of the election in which his party was victorious, that Austrian politicians are making a decision, by excluding his party, and him specifically from government, that is a slap in the face to the electorate—though he’s continued to make overtures to other conservative parties in the hope that they might be willing to work with the Freedom Party to form a functioning government; this seems unlikely, at this point, though it’s not impossible.

Even without a functioning coalition, though, Kickl and his party’s win at the polls, bringing in the most support of any party, speaks volumes about the popularity of this general collection of concepts and ideas; and the same seems to be true in many other countries where these ideas are being spread: despite a few let-downs for European far-right parties in recent years, this collection of political entities and personalities have done pretty well over the past decade, making substantial gains in France, Germany, and the Netherlands, in particular.

That these parties often align themselves with fascist governments and subscribe to easily disproven conspiracy theories doesn’t necessarily outweigh their support of increasingly popular anti-immigration policies, it would seem, and that popularity seems to be the result of their success in tying immigration to all manners of social and economic ills.

Much of Europe is still experiencing economic downswings, high levels of inflation, and overall underperformance compared to their peers, post-pandemic peak, so this sort of messaging may be decently well-received even by folks who wouldn’t typically agree with much of the rest of their platform or narrative, but who are currently looking for anything that defies the current status quo, and anyone who provides something that seems like it might be an explanation for those many and varied downswings and other perceived ills.

Show Notes

https://www.infomigrants.net/en/post/56618/italyalbania-asylumseeker-deal-to-cost-%E2%82%AC653-million-report-finds

https://archive.ph/PFWhk

https://www.nytimes.com/2024/09/29/world/europe/austria-election-freedom-party-kickl.html

https://www.reuters.com/world/europe/austrian-far-right-head-urges-rivals-let-him-govern-after-election-win-2024-10-05/

https://www.reuters.com/world/europe/austria-holds-tight-election-with-far-right-bidding-historic-win-2024-09-28/

https://en.wikipedia.org/wiki/Remigration

https://en.wikipedia.org/wiki/Race_(human_categorization)

https://en.wikipedia.org/wiki/Identitarian_movement

https://en.wikipedia.org/wiki/Great_Replacement

https://en.wikipedia.org/wiki/European_New_Right

https://en.wikipedia.org/wiki/Scientific_racism

https://en.wikipedia.org/wiki/Martin_Sellner

https://en.wikipedia.org/wiki/Brittany_Sellner

https://en.wikipedia.org/wiki/Herbert_Kickl

This week we talk about the Fed, interest rates, and inflation.

We also discuss cooling economies, the Federal Funds Rate, and the CPI.

Recommended Book: Dirty Laundry by Richard Pink and Roxanne Emery

Transcript

I’ve done a few episodes on this general topic over the past several years, so I won’t get super in-depth about many of the specifics, but the US Federal Reserve has a dual-mandate to keep prices stable and to maximize employment in the country—though that core responsibility has been expanded in recent years to also include regulatory control over banks, providing a variety of services to banks and other savings associations, and doing what it can to moderate long-term inflation rates.

A lot of these responsibilities are intertwined, in the sense that, for instance, if you increase interest rates, that can lead to less spending by corporations that might otherwise borrow and spend liberally, creating more jobs; so adjusting one lever often tweaks seemingly disconnected outcomes—which is part of why this agency’s activities often fly below the radar of non-regulation, non-monetary-world people and publications; they’re super-careful with their powers, because one wrong move can cause ripples of discomfort throughout the US and global economy.

When one of those metrics they’re meant to moderate goes haywire, on the other hand, they’re all over the news; their every action, even the seemingly unimportant ones, tracked in great details, and breathlessly reported-upon.

For a variety of reasons, including the large-scale shut-down of various aspects of society and the global economy, and the consequent disruption of global supply chains, inflation—as measured by CPI, or the Consumer Price Index—shot through the roof, pretty much everywhere on the planet, beginning in 2020.

Leading up to that moment, many wealthy countries had been doing pretty well in terms of moderated inflation levels, and the US was no different: year-over-year inflation growth was down to sub-1% levels in 2014 and 2015, and it was close to the Fed’s 2% target level from 2010, when the worst of the 2007-2008 economic crisis had receded, until 2020, when it was down to 1.4%.

That year, the Federal Funds Rate, which is the lever the Fed uses to adjust interest rate levels throughout the US government and economy, setting the interest rate banks charge to lend each other money short-term, basically, that number eventually influencing everything from savings account interest payments to mortgage rates to what you can expect to pay for a car loan—that Federal Funds Rate was down to .25% in 2020 and 2021, which is very low, which meant that debt was very cheap and easy to acquire, corporations happily borrowing as much money as they wanted, as it would cost them very little to do so, and that meant expansion across the economy, that expansion further aided by low interest paid on savings accounts and similar, safe-havens for money, which made investing in startups, stocks, and similar, risky investment vehicles more appealing—because the safe stuff didn’t pay much of anything.

All of which meant a spending bonanza—right up to the point that COVID-19 started rippling outward from China, and the world’s governments responded with lockdowns and similar, economy-stifling measures.

By the end of 2021, year-over-year inflation in the US was up to 7%, from 1.4% the previous year, and it was 6.5% the following year.

In 2022, the Fed bumped the Federal Funds Rate from that incredible low of .25% up to 4.5%—a huge jump, and a staggering blow for an economy that was experiencing a dramatic surge in prices; the goal being to slow things down, and consequently, hopefully, also slow that inflation rate.

Other factors likewise influenced inflation around the world during this period, including Russia’s invasion of Ukraine, which massively complicated the global energy market, alongside other disruptions, and the weirdening of politics, which have become increasingly tribal and extreme over the past decade or so in many governments around the world, have made it trickier to legislate, and have carried a wave of unserious and obstructive lawmakers into office.

That hiking of the Federal Funds Rate ended what’s been called the US’s ZIRP era: a period in which zero interest-rate policy, or so close to zero that it’s essentially zero interest rate policy, defined the shape of the economy, what professions everyone chose to pursue, which players became dominant in their industries, and what sorts of bets made financial and reputational sense.

The US, and much of the world, especially the wealthy world, was thus suddenly plunged into a very different financial and regulatory environment, changing its posture and the politics of money and spending, while also queueing things up for a potential future in which inflation might be tackled and the Fed might start adjusting the dial downward once more, tipping the economy back into something more spendy and risk-taking, after a handful of years in which the name of the game has been cutting costs, laying off as many people as possible, and recalibrating toward today’s profits over investing in tomorrow’s potential gamechanging outcomes.

What I’d like to talk about today is the Fed’s recent decision to do exactly that, adjust their interest rate dial, and how the way they did it is being received by those who are the most affected by this choice.

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The mechanism of the Federal Funds Rate is fairly straightforward: make it more expensive to borrow money and you tend to cool the economy.

Do this at the wrong time—when the economy is already cool—and you hurt the businesses that make up the production side of things, but also consumers, as there likely won’t be enough jobs, and enough jobs paying enough for folks to earn a living, buy things, and keep those businesses operating at nominal capacity.

Don’t do it when you need to, though, and the economy can get out of hand, running too hot, expanding wildly, and possibly also pumping up inflation at a rate that makes everything pricier, which can lead to similar consequences: folks not able to afford as much because the price of things is going up, despite their pay being decent and the job market being on fire.

This rate has to be used like a scalpel, not a chainsaw, then, lest you tip things one way or the other, in either case resulting in some type of economic truncation and various types of suffering for the citizenry of the country in question.

In this context, a “soft landing” is a semi-mythical accomplishment involving the just-right application of the Federal Funds Rate so that you increase interest rates, maybe dramatically, to stifle high inflation, but then pull those interest rates back at just the right moment so that the economy is cooled, but not damaged, and you’re thus able to put things back on a nice growth trajectory, but with something like a 2% inflation rate, rather than something much higher, or just as bad in some ways, much lower than that.

It’s been speculated that a soft landing might be attainable by this Fed’s current leadership because they seemed to be acting prudently and objectively, despite the politics surrounding their efforts, and they also seemed willing to hold off on lowering the rate even when much of the business world and parts of the government were losing its mind over worry that they would keep it high for too long.

In late September 2024, the Fed announced that they’d decided to finally cut this rate, from a target range of 5.25-5.5%, down to a target range of 4.75-5%.

That’s a drop of .5%, which is unusual except in emergency circumstances, and while it wasn’t totally out of the blue—many analysts and betting markets had given a high probability to this potentiality, as opposed to the usual .25% cut—it was still quite a big event, as it makes pretty clear that the Fed sees their job as being mostly done, at least in the sense that they need to cut inflation quickly and dramatically.

That decision was made on the basis that US inflation rates, using the Fed’s preferred index, had dropped for the fifth consecutive month in August of this year, down to 2.2%, which marked the lowest level since February of 2021; that’s down from 2.9% in July, and is tantalizingly close to their target rate of 2%.

The implications of this double-the-usual drop in the Federal Funds Rate are many, and the specifics and claims vary depending on who you ask.

One perspective of why this did this how they did it is that the Fed sees that it’s work is done on this matter, and they’re keen to get interest rate levels back to something more moderated as quickly as possible so that the economy can keep its solid momentum going apace. They also recognize that there’s a delay on these sorts of decisions and their impact, so getting close to 2% and then pulling back is more likely to ultimately land them somewhere close to 2%, while waiting for reports that show 2% before pulling back would be likely to lead to an overshoot, which could be really bad for economic outcomes.

Another view is that the Fed accidentally held on a little too long and maybe should have cut rates by .25% at their previous meeting, and now, to make up for that, they doubled the cut; but  because of that accidental delay, the economy could suffer a bit, the Fed overshooting after all, which again, wouldn’t be ideal, but is a possibility because of that aforementioned delay in cause and effect.

Some prognosticators in this space, however, are seeing this as a panicky indication that we’re actually careening toward a recession, as some of the economic indicators folks watch to predict such things are flashing red, and while a successful soft landing could theoretically help the US avoid such a path, the current wave of relief and optimistic anticipation could also be an illusion that’s concealing structural weaknesses in the US economy that are about to rupture.

The most popular version of that more pessimistic prediction is that the US will experience a recession in 2025, maybe 2026 at the latest, and it will have to make it through that trough before it can start climbing up the peak, again—which would be bad news for investors and businesses, and would mean basically resetting to a standing start, in terms of growth, as opposed to perpetuating the momentum of the economy as it exists, today, which is doing pretty well by most metrics.

That could also be quite bad for burgeoning industries like those connected to AI systems, renewable energy, and microchips, as these are all investment-intensive corners of the economy, and a recession would almost certainly significantly truncate the amount of money sloshing around in investors’ bank accounts, waiting to be injected into businesses operating in such spaces.

All that said, at the individual level, while inflation has been moderated by many measures, prices dropping substantially from where they were even a few months ago, what’s been called the “vibecession” seems to still be hampering the everyday person’s sense of how things are going economically in the US—the numbers look pretty good, but the average person reports that they think things are going catastrophically.

It’s thought that this is at least partly the consequence of economic ignorance—folks only remembering the many negative headlines they see, and not realizing how historically low unemployment is, and how historically high the stock market has climbed, alongside other positive measures.

But the more potent ingredient, almost certainly, is that while inflation has moderated for many common goods and expenses, others, like food, are still quite high, and that’s an expense that we don’t just see periodically, like when we buy new shoes or a new car, but every week or even every day, which is a far more regular punch to the gut that hits not just our pocketbooks, but also our perception of how far our money goes, and how well off we feel as a consequence.

There’s already a great deal of speculation as to what the Fed will do at its next meeting in November, and bets on popular futures markets indicate there’s a 54% chance of another half-point cut, as opposed to a 46% chance of a quarter-point cut.

That latter potentiality would arguably support the assertion that the Fed is scrambling to make up for lost time, hoping to avoid an inflation reduction overshoot—or from a more positive perspective, maybe just wanting to get back to a more neutral interest rate stance sooner rather than later, to help keep the economy chugging along, without any periods of sluggishness, while the former potentiality, a quarter-point cut in November, would ostensibly seem to be a more confident stance from the Fed, but could also worry investors, as it might mean it’ll take a bit longer to fully return to that neutral stance.

Whatever speed the Fed ends up opting for in dropping interest rates, though, most analysts see the rate falling to something like the 3-3.25% range by the middle of 2025, which is at the top end of what’s generally see as a neutral rate for such things—a rate that won’t add fuel to a hot economy, but also won’t cool things artificially.

By that point, we’ll probably also know if the Fed has managed to nail a soft landing; it seems like they might have, but at this point there is still reason to suspect they didn’t, and that this is just the silence before the storm.

Show Notes

https://www.washingtonpost.com/opinions/interactive/2024/john-lanchester-consumer-price-index-who-is-government/

https://en.wikipedia.org/wiki/Consumer_price_index

https://en.wikipedia.org/wiki/Misery_index_(economics)

https://apnews.com/article/federal-reserve-barkin-interest-rates-inflation-bba49b528649cf866e391a783033c067

https://www.cnn.com/2024/09/23/economy/rate-cut-what-next/index.html

https://www.wsj.com/business/entrepreneurship/fed-interest-rate-cut-small-business-spending-abfed941

https://www.forbes.com/sites/georgecalhoun/2024/09/26/the-feds-rate-cut--a-soft-landing--or-fake-news/

https://www.reuters.com/markets/us/fed-is-aligned-rate-cuts-upcoming-data-will-shape-pace-2024-09-27/

https://apnews.com/article/interest-rates-inflation-prices-federal-reserve-economy-0283bc6f92e9f9920094b78d821df227

https://www.cbsnews.com/news/federal-reserve-rate-cut-credit-cards-mortgages-already-lowering-rates/

https://www.federalreserve.gov/newsevents/pressreleases/monetary20240918a.htm

https://www.investopedia.com/will-fed-rate-cuts-save-commercial-real-estate-cre-loans-banks-8719181

https://finance.yahoo.com/news/new-pce-reading-supports-case-for-smaller-fed-rate-cut-in-november-143349577.html?guccounter=1

https://www.bloomberg.com/news/articles/2024-09-28/powell-speech-and-jobs-data-to-help-clarify-fed-rate-path?embedded-checkout=true

https://www.reuters.com/markets/us/traders-bet-second-straight-50-bps-fed-rate-cut-november-2024-09-27/

https://en.wikipedia.org/wiki/Federal_funds_rate

https://en.wikipedia.org/wiki/Zero_interest-rate_policy

https://www.investopedia.com/terms/s/softlanding.asp

https://www.cbsnews.com/news/federal-reserve-rate-cut-credit-cards-mortgages-already-lowering-rates/

https://www.theguardian.com/business/2024/sep/27/stock-markets-hit-record-highs-after-news-of-a-fall-in-us-inflation

This week we talk about interdiction, the NSA, and Mossad.

We also discuss exploding pagers, targeted strikes, and paramilitary organizations.

Recommended Book: Uncertainty in Games by Greg Costikyan

Transcript

In the world of technology, and especially computers—or anything with microchips and thus, some computing capabilities—a “backdoor” is a bit of code or piece of hardware that allows someone (or a group of someones) to get inside that computer or compute-capable device after it’s been delivered and put into use.

At times the installation of backdoors is done beneficently, allowing tech support to tap into a computer after it’s been sold so they can help the end-user with problems they encounter.

But in most cases, this term is applied to the surreptitious installation of this kind of hardware or software, and generally it’s meant to allow those doing the installing to surveil the activities of whomever is using the product in question, or maybe even to lock them out and/or hijack its use at some point in the future, should they so desire.

There are potential downsides to the use of backdoors even when they’re installed with the best of intentions, as they can allow malicious actors, like hackers, working independently or for agencies or nation states, to tap into these devices or networks or whatever else with less effort than would have otherwise been required; in theory such a backdoor would give them one target to work on, rather than a bunch of them, which would mean attempting to access each and every device individually; a backdoor in an operating system would allow hackers who hacked that backdoor system access to every device that uses said OS, for instance.

Backdoor efforts undertaken by the US National Security Agency, the NSA, were famously divulged by whistleblower Edward Snowden, revealing all sorts of—to many people outside the intelligence world, at least—unsavory activities being conducted by this agency, among them efforts to install backdoors in software like Linux, but also hardware like routers and servers, at times opening these devices up and installing what’s called a Cottonmouth, which allows the NSA to gain remote access to anything plugged into that device.

This sort of interdiction, which is basically the interception of something before it reaches its intended destination—so intercepting a modem that’s been ordered by a big company, opening it up, installing a backdoor, then repackaging it and sending it on its way to the company that ordered it as if nothing has happened—is not uncommon in the intelligence world, but the scope of the NSA’s activities in this regard were alarming to pretty much everyone when they were divulged, with leaks and reporting showing, basically, that the NSA had figured out ways to put hardware and software backdoors in just about everything, in some cases resulting in the mass collection of data from American citizens, which goes beyond their legal remit, but also the surveillance of American allies, like the chancellor of Germany.

What I’d like to talk about today is another, recent high-visibility example of an intelligence agency messing with devices ordered by a surveillance target, and what consequences we might expect to see now that this manipulation has come to light.

—

In the world of covert operations—spy stuff, basically—a “hand of God” operation is one that is almost immaculately targeted to the point where it might almost seem as if those who are struck did something to piss off a deity; those who the targeters want to hit are hit, and everyone else is safe or relatively safe.

In 2020, a hand of God operation was launched against an Iranian general named Qassem Solaimani while he was near the Baghdad airport, an American Reaper drone hitting Solaimani and his escorts’ cars with several missiles, killing the general and nine other people who were with him, but leaving everyone else in the area largely unscathed—not an easy thing to do.

Hamas’s leader, Ismail Haniyeh, was assassinated in July of 2024 by Israel, which blew up his bedroom in a military-run guesthouse in Iran’s capital city, Tehran, either using a well-targeted missile or a bomb that they somehow managed to hide in that room ahead of time—either way, it was a very precise attack that made use of a lot of intelligence data and assets in order to hit the target and just the target, avoiding other casualties as much as possible—which again, can make this sort of strike, though still massively destructive, seem like an act of god because of how highly specific it is.

On September 17 of 2024, at around 3:30 in the afternoon, local time, thousands of pagers, which were purchased and used by the militant group Hezbollah, which governs the southern part of Lebanon, and which is locked in a seemingly perpetual tit-for-tat with Israel, mostly using rockets and drones across their shared border, these pagers began to buzz, indicating there was a new message from Hezbollah leadership, and then seconds later they exploded—some in their owners’ pockets or on their hips, some in their hands, if they lifted them to their faces to see what the message contained.

These sorts of devices were subbed-in for smartphones by the organization’s leadership in recent years, especially following the early October attacks on Israel by Hamas in 2023, due to fears that Israel’s notorious intelligence agency, Mossad, would be able to tap their communications if they used more sophisticated tools.

The pagers in question were a bit more modern than those that were common a few decades ago, allowing users to basically text each other, and it was thought that they were simple enough that they would reduce the number of software backdoors that Mossad could use to intercept their messages, while still allowing those in the higher-levels of the organization to communicate with each other quickly and efficiently.

Instead, it looks like Hezbollah acquired these pagers from an Israeli shell company—maybe several shell companies—operating out of Hungary which licensed the device schematics and branding of a Taiwanese company in order to make it seem legit.

This company or companies were set up in mid-2022, and the tangled web of activities surrounding them is still being unspooled by journalists and intelligence agencies, but pretty much everyone, from the pager brand’s parent company to the Hungarian government deny any connection to any of this, the US and Israel’s other allies deny having any foreknowledge of the operation, and Israel’s Mossad is of course not divulging their secrets, so it could be a little while before we know all the details, if we ever do, but it seems like this larger operation, the infrastructure for it, anyway, may have been in the works for a decade or more.

The way it played out, though, is that those thousands of pagers seem to have been filled with a few ounces of explosives and rigged with software that would detonate said explosives when a specific message was received by them. These pagers, then, were delivered to Hezbollah, distributed to their higher-ups, their inner-circle, basically, and then on September 17 thousands of them received the detonate message, blew up, and killed at least 12 people and injured nearly 3,000.

Lebanon’s hospitals were filled with the dead and grievously injured, shutting down a significant chunk of their overall medical capacity, and the following day a wave of radios—the kind used to communicate, not the kind used to listen to music, so basically walkie-talkies—alongside a few mobile phones, laptops, and some solar power cells, all owned and used by Hezbollah officials and operatives, blew up, killing at least 25 people and injuring about 450.

Then, a few days later, Israel launched an airstrike on a suburb in Beirut—the capital city of Lebanon—killing two senior Hezbollah officials and something like 36 other people with the 140 or so rockets it launched during the operation.

Anonymous officials from the US and Israel have told reporters that the explosives hidden in those pagers and other devices, were originally meant to be used as an opening salvo of an all-out attack against Hezbollah, which by definition would probably mean an invasion of Lebanon, since Hezbollah controls a fair portion of the country, but they were growing concerned that Hezbollah might have been on to them and their explosives-hiding efforts, so they decided to move sooner than planned and detonate these devices without having that immediate full-bore followup ready to go.

This might be part of why the attack is generally being seen, in analytical and intelligence circles, at least, as a tactical success but a strategic question mark, as the end-goal isn’t really clear, especially since Israel is still partly tied-up in Gaza and increasingly the West Bank, as well, and thus not super well-prepared for a potential real-deal war with Lebanon, to its north. This operation’s culmination would have made a lot more sense several months in the future, when they would theoretically have been in a better spot to detonate these devices, launch a bunch of missiles, and then move in with soldiers on the ground to capture or kill the rest of Hezbollah’s leadership.

It has been posited that this effort still serves a few important purposes for Israel’s military and intelligence agencies, though. For the latter, it serves as a reinvigoration of the “don’t mess with us” reputation they held up until the successful sneak-attack by Hamas last October; Mossad has been heavily criticized for ignoring the signals they were receiving about that attack, and this could have been partly meant to show their government and the world that they still have plenty of gas in the tank; it was a highly sophisticated operation, and it’s fairly terrifying to think that the devices we all carry in our pockets might be weaponized in this way; Iran’s military is reportedly disallowing the use of such devices for the time being, and local airlines are not allowing folks to bring these sorts of things aboard, either, so the scare-factor has definitely worked, and it will likely make it a lot more difficult for Hezbollah and similar organizations in the area to function, since they won’t know for certain which of their communication channels have been compromised and potentially weaponized against them.

The Israeli military, too, would seem to benefit from what amounts to a decapitation attack on an organization that has declared its intention to wipe Israel off the face of the map.

Hezbollah and similar organizations are more fluid than typical government organizations by necessity, but Hezbollah is a lot more established and entrenched than other Iran-backed entities, like Hamas in Gaza and the Houthis in Yemen, which means they have more infrastructure, a larger military force, and a more concrete leadership structure—the latter of which was hit hard by these strikes and hand of God operations, and the former of which has been hit hard over the past year or so, airstrikes targeting Hezbollah’s rocket, drone, and missile capabilities in particular having become more common since Hamas attacked Israel.

There are several interesting, and in a few cases alarming, possible implications of this operation and its accompanying airstrikes.

First is that it could represent a time-delayed unofficial declaration of war by Israel against the Hezbollah-controlled portion of Lebanon.

There have been very clear red-lines honored by both militaries for the past several years, both of them generally sticking to hitting targets within a few miles of their shared border, and both sides generally avoiding hitting major cities or higher-ups from the opposing side with their strikes; a lot of rockets and missiles and drones flying, but few of them hitting anything meaningful, other than the sites from which those projectiles were launched.

Israel seems to be indicating that the rules have changed, though, and while Hezbollah has made similar gestures in recent days, aiming at and hitting a few Israeli targets beyond the typical projectile launch-sites and military installations close to the border, including towns dozens of miles from that border, they’re still proving to be less brazen than Israel in this regard, so far at least.

So it could be that Israel is leaving Hezbollah some space to back off, giving them a taste of what’s to come if they don’t accept that ultimatum, and it could be that Hezbollah is gesturing at hitting back, but avoiding doing anything they can’t step back from in order to give themselves time to either tone things down on what feels like their own terms, or to prepare for a more formal conflict; this could change at any moment, of course, but that seems like the most likely resting stance for Hezbollah at the moment—though in recent days both sides have indicated they’re not just prepared, but actually keen for a more formal conflict, including an Israeli invasion of Lebanon, which would allow the Israelis to do more capturing and disassembling of Hezbollah’s infrastructure, but could also bog them down in street combat, which would make them less effective in Gaza, while also probably requiring the summoning of thousands of new soldiers, or already active, but exhausted soldiers—which wouldn’t be a popular move on the Israeli homefront.

This also raises all sorts of questions about the safety, or lack thereof, of international supply chains.

Some of these supply chains have already suffered as a consequence of their tangling and breaking during the height of the COVID-19 pandemic, but others are beginning to shrink or even wither as a result of concerns about, for instance, China integrating itself in global communications systems via its 5G technology and mobile devices, which has led to all sorts of sanctions and import bans by countries like the US and their allies.

Could iPhones built in China be messed with before they’re shipped to their end-users in other countries? It’s not impossible, and the same is true of just about anything that’s made in one place and exported to another. That doesn’t mean it will happen, but the knowledge that it could—and the line that’s been crossed by Israel in blowing up seemingly safe personal devices in this way—could lead to more such bans, or at least concerns and posturing by political figures about these fears. That, in turn, could expedite the truncating and culling of some of these supply chains, further curtailing the expansiveness, range, and openness of global trade.

And finally, this raises more concerns about the possibility of Israel’s invasion and occupation of Gaza sparking a larger, regional conflict, as Hezbollah is backed by Iran, which also backs an array of other non-government interests in the region, including several paramilitary groups. And the Israeli government seems keen to take down as many of the threats it’s surrounded by as possible before any peace treaties are signed; which perhaps understandable when you’re running a country that’s been invaded by all of its neighbors simultaneously as many times as Israel has in its relatively short history as a sovereign nation, but it’s also pretty alarming as Israel is a hugely potent military force in the region, and it’s backed by many of the world’s most globally potent military forces, which means it could wreak a whole lot of havoc if it wants to, and if such an effort increases in scope, that could pull other regional powers, like Iran, more formally and overtly into the conflict.

There are other forces at play, here, too, like the political machinations of Israeli Prime Minister Netanyahu, who’s walking a fine line attempting to stay in office in the midst of large and seemingly endless protests by Israelis who oppose his seeming kowtowing to the country’s far-right political establishment, and who’s scrambling to stay in office, in part to avoid facing ongoing corruption charges against him.

There are also external factors that could influence the region’s next steps, like Russia, which would love to see this conflict expand because that would take resources and attention away from its invasion of Ukraine, while other nations, like Saudi Arabia, would likely prefer to continue along a previous course of regional stabilization and normalization—of more trade enabled by more peace, basically—though it now seems inclined to put those efforts on pause because of the unpopularity of dealing directly with Israel until and unless it recognizes a Palestinian state, which doesn’t seem likely in the immediate future, given everything that’s happened in the past year.

Lots going on, then, and this most recent wave of attacks would seem to stir the pot more than it settles much of anything for everyone involved; which means, most immediately, and this is true whether or not Israel and Lebanon more formally go to war with each other, the ongoing peace talks that many of Israel’s neighbors and allies have been hoping for have been essentially back-burnered for the time being.

Show Notes

https://en.wikipedia.org/wiki/Assassination_of_Qasem_Soleimani

https://en.wikipedia.org/wiki/Assassination_of_Ismail_Haniyeh

https://archive.ph/OqfPt

https://www.nbcnews.com/news/world/israel-strikes-lebanon-hezbollah-revenge-device-blasts-nasrallah-rcna171946

https://www.nbcnews.com/news/world/hezbollah-commanders-killed-israel-strike-beirut-device-blasts-rcna172085

https://www.washingtonpost.com/world/2024/09/21/israel-lebanon-hezbollah-exploding-pagers/

https://www.bbc.com/news/articles/cz04m913m49o

https://www.nytimes.com/2024/09/21/business/dealbook/exploding-pagers-deliver-supply-chain-warning.html

https://www.wsj.com/world/middle-east/hezbollah-exploding-pagers-israel-supply-chain-a4937b48

https://www.wsj.com/world/middle-east/israels-ultimatum-to-hezbollah-back-off-or-go-to-war-f1b99924

https://www.washingtonpost.com/national-security/2024/09/21/israel-lebanon-pager-explosions-hezbollah-warfare/

https://www.axios.com/2024/09/21/hezbollah-launches-medium-range-rockets-israel

https://www.nytimes.com/live/2024/09/22/world/gaza-israel-hamas-hezbollah

https://apnews.com/article/israel-palestinians-gaza-755733f50ad52c5af05a2ea7ef082e26

https://www.nytimes.com/2024/09/21/world/middleeast/israel-hezbollah-lebanon.html

https://www.nytimes.com/2024/09/20/world/middleeast/gaza-cease-fire-talks-hezbollah-lebanon.html

https://www.msn.com/en-us/news/world/israel-s-hand-of-god-operation/ar-AA1qMval

https://www.nytimes.com/2024/09/17/world/middleeast/israel-hezbollah-pagers-explosives.html

https://www.nytimes.com/2024/09/17/world/middleeast/hezbollah-pager-explosions-lebanon.html

https://www.axios.com/2024/09/18/hezbollah-pager-explosions-supply-chain-terror

https://apnews.com/article/lebanon-israel-hezbollah-pager-explosion-e9493409a0648b846fdcadffdb02d71e

https://www.nytimes.com/2024/09/22/world/middleeast/mideast-diplomacy-hezbollah-israel.html

https://www.nytimes.com/live/2024/09/22/world/gaza-israel-hamas-hezbollah

https://www.nytimes.com/2024/09/23/world/middleeast/israel-hezbollah-escalating.html

https://www.reuters.com/world/middle-east/irans-guards-ban-communications-devices-after-strike-hezbollah-security-2024-09-23/

https://arstechnica.com/tech-policy/2014/05/photos-of-an-nsa-upgrade-factory-show-cisco-router-getting-implant/

https://www.reuters.com/article/world/spy-agency-ducks-questions-about-back-doors-in-tech-products-idUSKBN27D1DO/

https://www.extremetech.com/defense/173721-the-nsa-regularly-intercepts-laptop-shipments-to-implant-malware-report-says

https://en.wikipedia.org/wiki/National_Security_Agency

https://en.wikipedia.org/wiki/Hardware_backdoor

This week we talk about EREVs, Ford’s CEO, and Hertz.

We also discuss the used EV market, plug-in hybrids, and the Tesla Model 3.

Recommended Book: Not the End of the World by Hannah Ritchie

Transcript

In late-2021, car rental giant Hertz announced that it would purchase 100,000 Tesla Model 3 sedans for its fleet, giving customers the opportunity to drive what had recently, in 2019, become the best-selling plug-in electric car in US history, beating out the Chevy Volt, and then in 2020 become the bestselling plug-in in the world, bypassing the Nissan Leaf.

This was announced about six months after the company went through a massive restructuring, triggered by a bankruptcy filing in May of 2020, which landed Hertz in the hands of a pair of investment firms that purchased a majority stake in the company for about $4.2 billion.

Part of the goal in making such a huge electric vehicle purchase was that it would ostensibly set Hertz up with some of the snazziest, most future-facing vehicles on the road, and it should—if everything went according to plan—also provide them with some advantages, as full-bore EVs have far fewer parts than traditional internal-combustion vehicles, which means a lot less that can go wrong, and fewer moving pieces that need maintenance; which is pretty vital for vehicles that will be driven pretty much continuously.

So the single largest purchase of electric vehicles in history would represent a massive up-front investment, but the hope was that it would both pay off in dollars and cents, maintenance-wise, and help differentiate a brand that had recently been through some very rough patches, business and competition-wise.

Unfortunately for Hertz, that’s not what happened.

Initially, this announcement bumped the company’s stock up by about 40% over the course of just two weeks, but the Model 3s they purchased weren’t as popular as they thought they would be, and though EVs should in theory be easier to maintain than their ICE peers, the relatively low number of specialized repair shops and high cost of relatively scarce spare parts meant that the cars were actually more expensive to maintain than more common and less flashy alternatives.

The company was also dinged by Tesla’s decision to raise its prices around the same time Hertz was making the majority of its purchases, and Hertz decided to start offloading some of the Model 3s it had bought—which only ended up being about 30,000, rather than the originally announced 100,000—selling the cars at a fire-sale discount, in some cases as low as $25,000, which could drop to about $21,000 in areas where EV tax credits applied to used vehicles.

Unfortunately for those who bought them, many of these used Teslas were hobbled by the same issues Hertz was scrambling to address, but couldn’t make work for their business model.

Many initially happy used-Tesla purchasers found that their car’s battery pack was fundamentally damaged in some way, in some cases costing half, or nearly the same as the price they paid for the car, to repair or replace.

This fire sale arrived at around the same time as an overall drop in used EV prices across the market, too, which meant that Hertz’s prices—though at times falling to about half of what a new Model 3 would cost—weren’t as great as they could have been, especially for cars with so many potentially costly problems.

In other words, at this moment the whole of the EV industry was experiencing a bit of a price shock, as most automobile companies selling in the US were introducing new EV models, and they were finding that supply had surged beyond demand, leaving some of them with lots full of cars—especially in parts of the country where EV charging infrastructure still hasn’t been fleshed out, dramatically diminishing the appeal of EVs in those regions.

In early 2024, Hertz’s CEO resigned, mostly because his bet on Teslas and other EVs, hoping to making about a fifth of the company’s fleet electric, didn’t go as planned, and that’s left the company’s stock trading at around 11% of its 2021 high price point as of early September 2024.

To replace him, the company brought in a former executive from Cruise, which is an autonomous car technology company that’s owned by General Motors; another company that’s been trying to figure out the proper balance between investing in where the automobile market in the US is, today, and where it will be in the coming years.

What I’d like to talk about today is another facet of the automobile industry that’s changing pretty rapidly, and a new take on a third option, straddling the internal combustion engine and EV worlds, that seems to be evolving in a compelling—to those running these companies, at least—manner.

—

In January of 2023, the CEO of Toyota, who was the 66-year-old grandson of the company’s founder and who had been running the company since the early 2000s, stepped down from his position following a wave of criticism about his outspoken focus on hybrids over electric vehicles.

This company, which in some ways has been defined in recent years by its gamble to release the very well-received Prius, an early hybrid that really leaned into the concept of using a battery to support the activities of the car’s conventional fuel-burning engine, which resulted in a bunch of energy-efficiency benefits, the company had lagged behind its competitors in developing, announcing, and releasing new electric vehicle models to compete with the likes of Tesla—a company that was eating everyone else’s lunch in the EV department, and which was seeing sky-high valuations as a consequence.

Toyota was also being criticized by environmentalist groups for failing to move toward fully electric, zero-emissions vehicles, as while it did have a few EV models on the market, they were seemingly afterthoughts, accounting for less than 1% of the company’s US sales, and the main model, the cumbersomely named bZ4X, experienced a significant safety recall that upended its rollout plans.

Toyota’s new CEO leaned a bit more into EVs, announcing 10 new models in 2023, alongside plans to sell 1.5 million of them per year by 2026. But the company was still selling more cars than any other automaker on the planet, and the vast, vast majority of them were some kind of fuel-burning vehicle.

Despite the change in leadership, then, and the slight tack toward EVs the new CEO made soon after ascending to his new position, the company was still being criticized by environmentalist groups for not doing enough or moving fast enough, and the market seemed to think Toyota was setting itself up for a pretty grim next decade, since it was falling so far behind its competition in terms of supply chains and manufacturing know-how, related to EVs.

This general storyline, though, seems to have changed over the past year.

Yes, it’s still generally assumed that EVs are the future, that the electrification of everything is where we’re headed as a globe-spanning civilization, not just our transportation, but everything moving toward renewables—and that’s for climate-related reasons, but also the economics of renewables, which, once installed and connected, tend to be a lot more favorable, economically, than fossil fuel-based alternatives, almost always.

That said, the aforementioned disconnect between EV availability and investment, and EV demand in the United States has increased over the past year. EV sales are continuing to increase overall, but the huge spike in sales we saw over the past handful of years has tempered into a slower ascension, and many automakers have found themselves with car lots filled with models that aren’t the ones people want—at least not in the requisite numbers to keep lot turnover happening at the rate they like, and in some ways need, to see.

This is not the case in many other countries, I should note.

In China, EVs already made up something like 37% of the country’s total automobile marketshare, the share of new cars sold, in 2023, and across Europe, about 24% of all new cars sold were plug-in electric vehicles that same year.

In the US, the number is still in the single-digits, something like 8% as of Q2 2024, which is a lot bigger than the 5% or so in early 2022, but again, not the kind of rampant growth carmakers were planning for.

Another component of the automobile industry in the US has continued to grow a fair bit faster, though, up more than 30% year-over-year, accounting for up to 9.6% of the country’s total light-duty car marketshare in the second quarter of 2024.

And that slice of the market is the world of hybrids—the component of the car industry that Toyota has bet heavily on, despite antagonism from all sides, over the past several years, and which other automakers like Ford, are pivoting toward, as well; Ford recently announced that it would no longer be releasing a full electric, large SUV in the near-future, and will instead be releasing hybrid models, possibly including plug-in hybrid models.

Plug-in hybrids are like traditional hybrid vehicles, except they have a larger on-board battery pack that can be plugged into an electrical outlet, which allows them to be even more efficient than their traditional hybrid kin; so they're like a traditional ICE vehicle, but with a big, plug-innable battery that helps that engine be more efficient, giving it much better gas mileage.

Another recent development in this space, though—one that’s already pretty well-known in China, but still foreign enough in the US that the CEO of Ford said, after being exposed to the idea for the first time earlier this year, that he thinks it might be the right variation of existing approaches to help the US make the transition to electric vehicles—is called an extended-range electric vehicle, or EREV, and rather than being a hybrid with a suped-up battery, it’s an EV with a built-in, smaller internal combustion engine that serves as an onboard generator, allowing the car to burn fuel to generate electricity, which then charges the car’s giant battery, giving it more range when it’s needed.

The CEO of Ford thought this lined up well with how the American market works, and could help temper the range-anxiety many Americans feels, worrying that the battery packs in their EVs won’t allow them to take road trips, or might run out of juice when they’re partway through their homeward-bound commute at the end of the day; recharging an EVs battery still takes a fair bit longer than filling up a tank of gas, and there are way more gas stations than EVs plug in points around the country, as of 2024.

So if there were a little engine inside their EV capable of giving it a backup charge when necessary, and if that little generator could be fueled using gas that’s widely and relatively inexpensively available across the US, that could in theory help people transition to driving with electricity—which can be generated cleanly, using renewables—most of the time, while having that backup system in place, for when it’s needed, which might be rarely or never.

In late-2023, car-maker Stellantis unveiled their Ram 1500 Ramcharger, which is an EREV that can drive up to 690 miles on its battery pack, but it also includes a 3.6-liter V6 engine that activates when the main 92kW battery is running low on juice; a little generator that burns fuel to recharge the main battery.

One of the big, market-defining questions related to that new Ram and similar models, though, is whether US government regulators will categorize EREVs as zero-emissions vehicles, because, in theory at least, they will at times not be zero-emissions, even though for many people they would probably run on just their batteries most of the time.

This judgement call could impact sales substantially, though, as such determinations help define what would-be customers pay up front, what sorts of tax benefits, if any, they can expect on their purchases, and what sorts of taxes and other fees they’ll pay along the way, for the life of the vehicle.

Whether this topsy-turvy version of the hybrid—the traditional version having a conventional engine with battery backup, and this new riff on the theme defined by a massive main battery with a conventional engine backup—whether it will do well on the market anywhere outside of China has yet to be seen, and there’s still the question of whether other automakers will be able to spin up their own versions of the concept before the market moves again, trends realigning, and more plug-in electricity infrastructure maybe making vanilla EVs more desirable and useable in more parts of the country.

In the meantime, though, we seem to be seeing—rather than the clean transition from ICE vehicles to EVs that some people had hoped for and expected—something more akin to a Cambrian Explosion, where new pressures and innovations are sparking all kinds of interesting offshoot evolutions, and rather than just two options, one supposedly the future and the other supposedly on its way out, we have a half-dozen core themes around which most new vehicles are being built, some of them interchangeable, some not so much, and that suggests we could see more large recalibrations and broad market shifts, alongside a slew of new combinations and innovations, before the previous paradigm fully gives way to whatever ultimately replaces it.

Show Notes

https://electrek.co/2023/01/26/toyota-ceo-steps-down-amid-electric-vehicle-movement/

https://caredge.com/guides/electric-vehicle-market-share-and-sales

https://en.wikipedia.org/wiki/Electric_car_use_by_country

https://cleantechnica.com/2024/08/28/u-s-share-of-electric-hybrid-vehicle-sales-increased-in-2nd-quarter-of-2024/

https://electrek.co/2023/04/07/toyotas-new-ceo-adjusts-ev-plans-but-sticks-to-a-hybrid-approach/

https://www.thestreet.com/electric-vehicles/ford-ceo-says-this-type-of-vehicle-can-be-the-bridge-for-electrification

https://www.wsj.com/business/autos/the-plug-in-hybrid-car-starts-to-win-over-buyers-2155e054

https://en.wikipedia.org/wiki/Plug-in_hybrid

https://fortune.com/2024/06/07/buy-used-tesla-hertz-fire-sale/

https://en.wikipedia.org/wiki/Tesla_Model_3

https://www.roadandtrack.com/news/a60232041/hertz-ceo-resigns-after-big-bet-on-evs-fails-to-pay-off/

https://www.roadandtrack.com/news/a35698039/hertz-potentially-saved-from-bankruptcy/

https://www.roadandtrack.com/news/a38053117/hertz-buying-100000-teslas/

https://qz.com/tesla-hertz-used-electric-cars-evs-damage-glitches-1851482632

https://archive.ph/364dj

https://www.cnbc.com/2023/10/26/hertz-pulls-back-on-ev-plans-citing-tesla-price-cuts-repair-costs.html

https://en.wikipedia.org/wiki/Cruise_(autonomous_vehicle)