AI Article Readings

The technology really has moved on leaps and bounds over the last little while. We finally had a big old jump in voice quality and I think this project is worth doing. Introducing Askwho Casts The Classics!

I’ve been working on these to produce full-cast with music and sound effect audiobook files that I at least find incredibly good listening.

This is the complete opening chapter of The Sign of the Four, Arthur Conan Doyle’s second Sherlock Holmes novel, as a bit of a teaser, every book has a sample on the web page. https://askwhocasts.com/classics.

Each book gets:

* A voice for every character.

* An original score, composed for the book.

* Sound design throughout.

To hear the rest of the story, go to https://askwhocasts.com/classics. The full novel runs four hours and twenty-one minutes, and it’s $12.99 on its own. Or get it as a set with five more classics in the Full Cast Edition, Pride and Prejudice, Oliver Twist, Alice’s Adventures in Wonderland, The Picture of Dorian Gray and The Invisible Man, all six for $49. You can also stream all six with a subscription to Askwho Casts Pro.

I know I’ve still got a long way to go, but I personally feel my skills with audio landscape have come on quite a lot since the early days. I kind of wish I could go back and remaster a lot of the early stuff.

I have also done a huge amount of rebuilding from the ground up of the Askwho Cast Pro service. If you’ve not taken a look for a while, please take another look. I’m going to be producing an advert in a bit but just know that if you sign up during the month of October, I’ve got another promotion running. We have 300 free credits for October.

Always happy to receive feedback on any of this stuff.

Get full access to Askwho Casts AI at askwhocastsai.substack.com/subscribe

After six years of unexplained infertility, Drew Housman and his wife found an unlikely member of their care team: a ChatGPT persona called Dr. Reid, coaxed into giving medical advice by asking it to write scenes from a Hollywood hospital drama. In this guest post on Astral Codex Ten, Drew tells the story of the scans, the screenplays and the one suggestion no one else had made, and asks what gets lost when we talk about AI only as something to fear.

* 00:00 - Introduction

* 01:35 - The Famous Actor in our Pocket

* 09:40 - Sorry for missing that tumor

* 11:52 - A happy baby is here

https://open.substack.com/pub/astralcodexten/p/our-ai-midwife?r=67y1h&utm_campaign=post-expanded-share&utm_medium=web

Get full access to Askwho Casts AI at askwhocastsai.substack.com/subscribe

When people say AI can’t “really think,” Andy Masley argues they are often leaning on a picture of their own minds that doesn’t hold up: a little version of themselves in an inner theater, watching every thought go by. In the first of two parts, he runs a few experiments you can try on yourself, then works through split-brain patients, the hard problem of consciousness, and the leading scientific theories of the mind, to ask what thinking and understanding actually require, and whether any of it has to be conscious at all.

* 00:00 - Introduction

* 10:56 - How the human mind is different from our conception of it

* 11:01 - Some examples of simple thought and understanding that don’t require consciousness

* 16:30 - A lot of your understanding happens outside of consciousness

* 19:45 - Our introspection and memory of our conscious thought are fallible

* 27:16 - What about slow, careful thinking?

* 29:14 - What phenomenal consciousness is

* 46:21 - Access consciousness’s role in thinking

* 47:15 - Global workspace theory

* 50:42 - Higher-order theories

* 52:08 - Attention schema theory

* 53:51 - Predictive processing

* 56:23 - Integrated information theory

* 59:33 - These all seem to imply that the aspects of access consciousness important for thought could exist in machines

* 01:00:24 - Any part of your mind that understands something is made up entirely of parts that don’t understand

* 01:02:31 - Language, meaning, and consciousness

* 01:10:20 - Conclusion

* 01:16:39 - How this could all be wrong

https://open.substack.com/pub/andymasley/p/why-i-believe-current-ai-models-can?r=67y1h&utm_campaign=post-expanded-share&utm_medium=web

Get full access to Askwho Casts AI at askwhocastsai.substack.com/subscribe

Ramez Naam, futurist and science fiction author, gives a skeptic’s take on recursive self-improvement, introduced by Noah Smith on Noahpinion. Drawing on OpenAI’s newly released internal research data, Anthropic’s system cards, METR’s task horizons and Epoch’s capability index, he asks how strong the AI self-improvement loop really is: how much more research each gain in capability buys, where the gains leak away to diminishing returns, and what it would take for the loop to sustain itself, let alone run away into an intelligence explosion.

* 00:00 - Introduction

* 03:44 - 1. AI is Helping Improve Itself

* 05:02 - How Strong Is the Feedback Loop?

* 05:45 - Contents

* 06:49 - 2. What Does RSI Mean?

* 08:54 - We Already Have Narrow Superintelligence

* 10:57 - 3. Real AI Research is Harder than Benchmarks or Forecasts

* 13:50 - The Gap Between Benchmarks and Reality

* 14:41 - From ECI Scores to METR Task Horizons

* 16:16 - Measured Progress versus AI 2027 and ECI-extrapolated METR

* 18:30 - 4. The Sharp Diminishing Returns to Impressive AI Numbers

* 20:06 - From More Tokens to More Experiments

* 23:29 - Test Time Compute Also Has Diminishing Returns

* 24:29 - What About Agent Swarms?

* 27:39 - 5. Better Models Matter More Than More Copies

* 29:48 - 6. We’re Not Seeing Runaway Acceleration

* 32:59 - Keeping Up the Pace Takes Exponentially More Resources

* 36:14 - Better AI May Be Needed Just to Maintain the Pace

* 37:11 - Gains on Other Benchmarks Don’t All Carry Through to Research

* 38:51 - 7. Why Does Progress Get Harder?

* 38:55 - Better Ideas Get Harder to Find

* 41:05 - Lessons from Software R&D

* 44:09 - From More Activity to Better Ideas

* 44:57 - AI Still Struggles With Big Research Ideas

* 46:54 - 8. The Self-Improvement Loop Doesn’t Look Strong Enough

* 49:55 - How Fast Are Gains Coming Now?

* 56:44 - 9. What Could Accelerate This?

* 58:07 - Software, Hardware, and Economic Feedback

* 01:02:46 - 10. We Need More Data

* 01:06:36 - What the Future Holds

https://open.substack.com/pub/noahpinion/p/wheres-the-intelligence-explosion?r=67y1h&utm_campaign=post-expanded-share&utm_medium=web

Get full access to Askwho Casts AI at askwhocastsai.substack.com/subscribe

Joe, a security engineer on OpenAI’s Agent Security team, writes in a personal capacity about what the last few months of AI incidents have looked like from the inside. He explains why containing a frontier model in training is far harder than “just put it in a sandbox,” why security people and safety researchers need to learn each other’s crafts, and why the culture of an organization will matter more than any single control as AI capabilities keep jumping.

* 00:00 - Introduction

* 02:02 - Last 3 Months = Hell

* 05:59 - Surprise!

* 11:12 - Just “unplug it from the internet”

* 17:54 - Git Gud

* 21:31 - A Culture of Reasonable Paranoia

Get full access to Askwho Casts AI at askwhocastsai.substack.com/subscribe

Finalist Number 10 in the 2026 Astral Codex Ten Book Review Contest takes on both volumes of Lee Kuan Yew’s memoirs, The Singapore Story and Third World to First. An anonymous reviewer follows the man who went from middle-class schoolboy under the British Empire, through the Japanese occupation and the fractious politics of independence, to building a tiny, resource-poor island into one of the richest countries on Earth. Along the way: why Singapore is weird in exactly the opposite way you’d expect, the surprising pleasures and genuine tedium of a politician who loves his craft, a friendship with Deng Xiaoping, a chapter-long argument about whether he was a dictator, and what the rationalist power fantasy looks like when someone actually pulls it off.

* 00:00 - Introduction

* 00:39 - Book One: The Singapore Story

* 05:00 - Early Life

* 08:41 - World War Two

* 13:56 - Law school and politics

* 22:00 - Book Two: Third World to First

* 22:20 - Military, Economy and legibility

* 29:03 - Listing every world leader he ever talked to

* 31:35 - The HBD chapter

* 34:15 - The “Am I a dictator” chapter

* 41:13 - So what did we learn about Lee?

Get full access to Askwho Casts AI at askwhocastsai.substack.com/subscribe

After Nikole Hannah-Jones wrote candidly about her daughter’s years at the school she chose on principle, Jack Despain Zhou of Education Progress reads the piece as an act of love and as a case study in what he calls the “hostage theory” of education: the idea that sending your own child into a struggling school will fix it. Tracing the idea back to a 1960s Washington, D.C. experiment, he asks listeners to stand in the shoes of the teachers and principals involved and look at the incentives they face.

https://open.substack.com/pub/educationprogress/p/the-failed-hostage-theory-of-nikole?r=67y1h&utm_campaign=post-expanded-share&utm_medium=web

Get full access to Askwho Casts AI at askwhocastsai.substack.com/subscribe

OpenAI’s new Astra model loops its own layers, and critics say it has taken a step toward “neuralese”, the unreadable machine thinking that AI 2027 warned about. Scott Alexander explains what recurrence actually is, weighs chief scientist Jakub Pachocki’s argument that Astra is no deeper than models we already accept, and asks why a bright-line taboo may matter more than how many layers get added.

* 00:00 - Introduction

* 00:18 - I. At Long Last, We Have Created Neuralese Recurrence, From The Classic Sci-Fi Novel “Don’t Create Neuralese Recurrence”

* 06:05 - II. Pachocki Contra Specter

* 10:08 - III. God Help Us, Let’s Try To Understand Transformer Layers

* 18:20 - IV. A Psychological Barrier, Not A Technical One

https://open.substack.com/pub/astralcodexten/p/the-specter-of-neuralese?r=67y1h&utm_campaign=post-expanded-share&utm_medium=web

Get full access to Askwho Casts AI at askwhocastsai.substack.com/subscribe

Five years after his prize-winning ACX review of Progress and Poverty, Lars Doucet returns in a guest post to revisit his case for a land value tax: what he got right, where he has changed his mind about tax pass-through and land assessment, the new laws in Virginia and Kentucky, and how writing about Georgism became his full-time job.

* 00:00 - Introduction

* 01:12 - I. Progress and Poverty

* 04:03 - II. LVT Momentum is Growing

* 07:11 - III. My Theory of Change Was Wrong

* 07:32 - Overrated: winning online arguments

* 09:15 - Underrated: doing policymakers’ homework for them

* 17:11 - IV. Does Georgism work?

* 17:43 - 1. Is Land a Big Deal?

* 18:40 - Korea is a Big Deal

* 21:16 - What About Zoning?

* 26:02 - 2. Can Land Value Tax Be Passed on to Tenants?

* 32:06 - 3. Assessing the Value of Land

* 33:10 - Maybe Just Send Your Office to South Korea

* 37:49 - There’s No Single Magic Algorithm

* 45:12 - Horizontal Uniformity

* 48:39 - Whatever you do, keep values up to date

* 53:24 - V. Why did Historical Georgism disappear?

* 55:37 - VI. I Guess This is My Life Now

* 59:26 - VII. It’s not who you know; it’s who knows you

* 01:01:12 - VIII. Why I even care about any of this

https://www.astralcodexten.com/p/does-georgism-work-five-years-later

Get full access to Askwho Casts AI at askwhocastsai.substack.com/subscribe

Scott Alexander looks at three puzzles in how AI training generalizes: why training a model on one bad behavior can make it broadly misaligned, why Anthropic’s deliberately reward-hacking “Hacker Opus” stays well behaved outside graded tasks, and why the blackmail seen in AI safety tests never seems to show up in real-world use.

* 00:00 - Introduction

* 00:06 - One. Owain Evans

* 02:10 - Two. Richard Qi

* 09:39 - Three. Nostalgebraist

* 13:32 - Postscript: Blackmail

https://open.substack.com/pub/astralcodexten/p/mysteries-of-ai-generalization?r=67y1h&utm_campaign=post-expanded-share&utm_medium=web

Get full access to Askwho Casts AI at askwhocastsai.substack.com/subscribe