Bold Conjectures with Paras Chopra

I’m with Patri Friedman who is a General Partner @ Pronomos Capital, the world's first charter city VC fund. Before this, he founded The Seasteading Institute, a non-profit that explores the creation of sovereign ocean colonies.

What is a charter city? What does a sovereign ocean colony mean? We will explore all these ideas in detail with Patri pretty soon. For now, you should know that Patri is a champion for innovation in governance.

Our economy thrives because there’s continuous innovation happening when new products and services are brought in the market. That innovation is mostly driven by startup companies who challenge the status quo of established companies. But this dynamic doesn’t exist in governance – we’re stuck with the legal systems and constitutions we’re born into.

What if we could kick-start a new city with an entirely fresh take on society? That’s the topic of today’s discussion.

== What we talk about ==
00:00 - Introduction to the podcast
01:13 - What led Patri to start the Seasteading Institute (a non-profit that explores the creation of sovereign ocean colonies)
05:44 - The current status of the project
07:29 - What is the legal status of putting a house, in the middle of nowhere?
16:30 - Definition of a Charter City
19:13 - What type of governments would allow Charter Cities?
21:30 - Are some governments fearful of giving up control?
24:50 - Have you made any investments in Charter Cities? What are the exciting things that are happening in this space?
29:20 - How do you motivate these incredibly smart, talented, and motivated people to move to a new city?
32:45 - What does a seed investment/early stage investment mean for a charter city or a community?
35:30 - Are there any focus areas or geographical regions you're interested in that entrepreneurs can reach out to you with their pitches?
39:30 - How did your father David D. Friedman's and grandfather Milton Friedman's thinking shape your thinking?
45:10 - What is the basic principle of Anarcho-capitalism?
51:20 - Are ideas like DAO in crypto inspired by Anarcho-capitalism?
52:44 - Have you thought about what governance systems will make sense when we become interplanetary species?
55:45 - Any laws on who claims a part of Moon or Mars?
56:20 - What is Jhana Meditation, and how does it differ from other styles of meditation?
1:04:00 - Is there anything else that you want to add, that you wanted me to ask, but I didn't ask?
1:05:12 - Concluding Thoughts

I interview Dr Stephan Guyenet, who is a researcher and science communicator in the field of neuroscience of obesity. He has written an excellent book on the same topic - The Hungry Brain. In his book, he explains how the brain is the central organ responsible for gaining weight and body fat.

Stephan finished his PhD in neuroscience from the University of Washington, and then spent 12 years as a full time researcher exploring the science of obesity and its link to the brain.

Stephan is also the founder and director of a non-profit called Red Pen Reviews, an online publication where he and his fellow researchers review popular nutrition books for scientific accuracy. Nutrition is an area where unfounded claims are often made, so I’m grateful for Stephan and the team for putting in effort to help sift scientifically grounded nutrition books from pseudoscience.

In this podcast, I explore with Stephan the neuroscience of why we get fat, and what we can do to stay fit.

== What we talk about ==
00:00 - Introduction to the podcast
01:20 - What is obesity and why should anyone care about it?
05:12 - The Ideal Body Mass Index & the Relationship between BMI and Ethnicity
10:24 - What exactly fat does in our body which make us unhealthy?
16:48 - What actually causes insulin resistance?
23:14 - How do excess calories that we eat ultimately end up into the fat cells?
29:15 - Why is ketogenic diet so popular? How does it really work?
31:07 - Why do we over-eat even when we don't want to?
58:14 - Non-homeostatic systems that make us overeat
1:07:38 - Is food addiction real?
1:17:15 - What people can really do to not get fat?
1:20:52 - Concluding Thoughts

In a world dominated by big companies with billions of dollars in investible capital, why should tiny startups be successful with anything?

After all, startups are less capitalized, have a non-existent brand, and often the products they release are basic.

Our today’s guest, Jerry Neumann, spends his time thinking about why startups are able to grow despite being surrounded by big companies. Without giving out too much, his ideas revolve around the concept of “uncertainty” and how, counterintuitively, it is the key to a startup's success.

He’s a venture capitalist with investments in popular companies such as DataDog and BankSimple. He also teaches entrepreneurship at Columbia University’s engineering school. He writes a blog called reactionwheel.net, which I will highly recommend everyone to read after they’re done listening to this podcast.

== What we talk about ==
0:00 - Introduction
1:23 - How did you become a venture capitalist and after that how did you end up teaching entrepreneurship at Columbia University?
7:59 - Can entrepreneurship be taught? What exactly are you teaching your students?
13:22 - Why should entrepreneurs embrace uncertainty & how does it fuel startups?
23:44 - Why big companies are obsessed with certainty?
30:22 - How should an entrepreneur handle uncertainty?
32:40 - Do you think if an opportunity or an Idea is too obvious, should an entrepreneur not pursue it?
39:32 - Can you talk about how market uncertainty is different than technical uncertainty?
44:15 - What is your thought when people say that the culture of innovation & the pace of innovation is itself a moat?
48:17 - Do have a framework to think about what are strong moats?
50:44 - How should an entrepreneur proceed to resolve uncertainty in an optimal way?
57:55 - Can you share your thoughts on what entrepreneurs should know about how VCs work?
1:04:16 - Closing of Podcast

I interview Gregory Zuckerman, who is a journalist with The Wall Street Journal and author of several award-winning non-fiction books.

His book on The Man Who Solved the Market profiled Jim Simmons of Renaissance Technologies which is perhaps the most profitable quant fund ever. The book was the #1 best-seller on the NY Times list and won the 2019 FT/McKinsey book of the year award.

His most recent book - A Shot to Save the World is a behind-the-scenes account of how covid-19 vaccine was developed and launched within a year of the pandemic’s start. This achievement is unprecedented in history as vaccines generally take many years and sometimes even decades to get developed.

What did we do differently this time? Well, that’s the topic we’re going to explore today.

== What we talk about ==
0:00 - Introduction
1:15 - How do you select the topic to write a book on?
4:15 - Do you seek a challenge in finding out what does not exist in the public view and getting it out in the public?
6:10 - Can you give a high-level history & timeline of the covid-19 vaccines?
10:56 - What is that startups (and not big corps) ended up creating the vaccine?
16:41 - What did you observe about human nature during vaccine development?
21:06 - Is it ethical to make a profit during the times like pandemics?
24:30 - Academics do all the fundamental R&D but they don't get to share the profit. Is it fair?
27:27 - What are the three types of vaccines basis on how they are different?
34:20 - Is the adenovirus approach different from previous approaches?
35:24 - In terms of vaccines do you prefer putting investment in one project or this diversity is helpful?
40:02 - Do you think there was anything we could have done to accelerate the clinical trials?
42:00 - What are your views on what led to the anti-vax movement, particularly in the US?
47:31 - Are we better prepared to handle the next pandemic?
48:52 - The journey of writing this book
53:08 - Did you have several endings in mind about how the vaccine approval would have turned out?
56:39 - Closing of Podcast

In this episode, I talk to Brain Naughton who’s the founder and head of data at Hexagon Bio. He is a Ph.D. in biomedical informatics from Stanford University and before starting Hexagon Bio, he was the founding scientist of 23andMe - the company that brought genetic testing into mass awareness.

At Hexagon Bio, Brain and the team are taking a refreshing new approach to discover new medicines. They’re sequencing the DNA of thousands of microbes and then using machine learning to predict which molecules could those microbes be making that will turn out to be effective medicines.

This approach of studying genomes of a wide variety of organisms at once is called metagenomics. What it is and how it helps in discovering new medicines is the topic of today’s podcast.

== What we talk about ==
0:00 - Introduction
1:11 - How did you get interested in genomics?
2:57 - How does traditional drug discovery work & what do you do differently at Hexagon Bio?
8:54 - Why would a plant have a small molecule that could treat cancer in humans when there is no evolutionary pressure on plants to do that?
12:55 - How are you discovering the right natural molecules from fungi out of the almost infinite number of natural products they produce?
15:37 - Are you sequencing genomes by yourself or are using public databases? How are you targeting which species of fungi to start with?
16:48 - From the time you have DNA sequence until mapping what drugs they are producing, what is the hardest problem you're tackling?
18:57 - Many genes are involved in making a molecule. How can you predict which molecule will be produced from a set of genes?
24:52 - There may be some gene clusters that we have no idea about what they do. How do you tackle them?
30:35 - At what stage are you in terms of discovering drugs that might proceed to clinical trials?
34:27 - Are you also trying to explore a much simpler way for producing some molecule that’s very hard to make synthetically?
38:29 - Since you are a big fan of automation are you experimenting with any lab equipment or protocol at Hexagon Bio?
42:45 - At Hexagon Bio, do you prefer doing all the work in-house or do you outsource it to other organizations?
50:04 - Thoughts on biotech startups
51:58 - How important are the grants for you?
54:45 - Can you give some tips for biotech entrepreneurs?

The dominant view of evolution is that of natural selection. But is it enough to generate all the complexity we see around us?

Natural selection suggests that those organisms who outcompete others survive and end up passing their genes to the next generation. According to our today's guest, Richard, there is another mechanism at play which is something he calls Natural Induction. This view explains how adaptions can arise in biological systems without natural selection. Evolution is the reason why we see all the complexity around us, so understanding it from a new lens is going to be very enriching.

== About the guest ==
Richard Watson is an Associate Professor at the Institute for Life Sciences at the University of Southampton. His research interests span artificial life and mechanisms of evolution.

== What we talk about ==
0:00 - Introduction
1:10 - How did you get interested in the mechanisms of evolution?
4:43 - What is natural selection?
8:57 - Your take on the debate on the unit of natural section
17:10 - What made you question natural selection?
26:05 - Can you talk more about your thesis on random accidents in cooperation evolution?
40:27 - Do you mean if individual species do not compete and go their own way, it is beneficial for the group as a whole?
45:23 - What is generalization or induction?
48:08 - Is the ecosystem robust or catastrophic to changes?
49:40 - When an ecosystem, at any moment of the time, is in a particular configuration, what is it really anticipating?
56:08 - In what way natural selection explains the emergence of higher levels of units from cells to organisms or from genes to chromosomes?
58:47 - Is ‘collectively increasing the biomass’ the implicit goal of natural induction?
1:01:37 - Natural selection in the world of businesses
1:09:20 - More about the page you have on your website - ‘What’s love got to do with it?’

Out of the 90 billion neurons in your brain, how many are active right now?

Mark Humphries is the Chair in Computational Neuroscience at the University of Nottingham. His group interrogates how the joint activity of many neurons encodes the past, present, and future in order to guide behavior.

He’s recently authored a book called “The Spike”, which details what really happens in our brain from an information flow perspective. In this podcast, I’m going to ask Mark how information flows inside the brain and some of the surprising discoveries made in neuroscience in recent years.

== What we talk about ==
0:00 - Introduction
1:11 - How did you get interested in studying the brain from a computational perspective?
4:09 - How is cognitive modeling different from computational neuroscience? Do they overlap?
6:44 - What is a spike? And how and why did it evolve as a mode of communication between neurons?
13:57 - How does a neuron integrate thousands of incoming inputs?
21:31 - What is your take on the existence of so many connections in the brain even though most of them are silent?
26:26 - What are dark neurons?
32:37 - What is the grandmother neuron (a.k.a. Jennifer Aniston neuron)? And how did it become popular?
42:44 - Is it possible for a brain to be comprised of a single neuron?
44:59 - How many hops in the brain does it take for the information to go from one part to another in the human body?
48:21 - Why is there spontaneous activity in the brain? How is it generated?
57:01 - What are neurons doing when we are in deep sleep?
58:18 - How much do you rely on these grand unified theories of the brain?
1:06:24 - What is consciousness? Your take on how the brain generates the subjective experience we are having?

What can artificial neural networks teach us about our own brains?

I interview Patrick Mineault, an independent scientist working at the intersection of neuroscience and deep learning. On his famous blog xcorr.net, he writes about the rapidly accelerating merger of techniques in AI and neuroscience. This field - neuroAI - aims to study how the brain works by studying artificial neural networks.

Patrick did his PhD in visual neuroscience from McGill University. He has worked at Google as a scientist and then worked with Facebook to build brain-machine interfaces. Most recently, he has helped build Neuromatch Academy, an online summer school on computational neuroscience.

== What we talk about ==
0:00 - Introduction
1:27 - How do you define neuroAI?
4:10 - What does ‘"understanding" something even mean?
14:20 - Are there any recent cases of neuroscience learning from deep learning/AI?
23:12 - Why have the evolution-inspired methodologies not been able to match the performance of straightforward deep learning models like GPT-3?
28:33 - How can unsupervised and supervised learning methods have similar performance in modeling the brain’s vision system?
36:50 - The difference between the amount of data given to process to supervised model vs unsupervised models
43:10 - Is anyone trying to model AI embedded in a 3D environment like we are?
51:15 - Do you think neuroAI can lead us to understand consciousness much more scientifically?
55:58 - Is anyone attempting to model consciousness in an artificial network?

== Useful links ==
Patrick's blog: https://xcorr.net 

Neuralink has made brain-machine interfaces cool, but what's beyond it?

I talk to Ladan Jiracek about the kinds of neural implants available in the market today and what we should expect in the future. Ladan is a graduate student at the University of Florida and the host of the most famous (and perhaps the only) podcast dedicated to brain-machine interfaces called the neural implant podcast.

== What we talk about ==
0:00 - Introduction
1:19 - What is a brain-machine interface (BMI)?
3:29 - What are your views on invasive vs non-invasive techniques for BMI?
5:37 - How hard is it to convince people to get brain surgeries done?
9:08 - How well do we have to understand the human brain in order to create an effective BMI?
15:04 - Are there any brain-machine Interfaces available for use today?
16:52 - How strongly science-backed are the devices that are available in the market today?
22:12 - How can we push the progress in this field to move faster?
33:18 - Who is currently pushing this field forward currently?
35:07 - What do you think about Neuralink?
40:48 - What are your views on Elon Musk’s plan of using neural implants to "merge with AI"?
43:12 - Will we ever be able to use neural implants to live in a virtual reality that exactly feels like physical reality?

== Useful links ==
Ladan's podcast: https://neuralimplantpodcast.com/

Do aliens exist?

Robin Hanson has developed a mathematical model called "Grabby Aliens" that not just predicts that they exist also suggests that they're rapidly expanding in the universe.

Robin is an associate professor of economics at George Mason University and a research associate at the Future of Humanity Institute of Oxford University. Personally, I’m a fan of his book “The Elephant in the Brain”; it had a major impact on how I view the world.

What Robin says in this episode is both provocative and grounded in logic.

== What we talk about ==
0:00 - Introduction
1:10 - What made you interested in aliens?
1:44 - What is the Fermi paradox and what is its relation with the Great Filter?
5:45 - Thinking about the future is the same as thinking about the aliens
7:09 - How does the Great Filter lead to the model of Grabby Aliens
15:48 - The Grabby Aliens model
25:13 - When can we expect to meet the aliens as per your model?
30:19 - What might be some of the observations/evidence that, if found, will decrease confidence in your model?
32:32 - What if the Grabby Aliens encounter conflicts with each other during expansion?
41:43 - Why competition is a good thing
45:29 - What are your views on the work SETI is doing?
48:04 - Why do you think that finding alien civilizations or UFOs is a matter of concern for us?
1:02:07 - Did your research findings change your worldview?
1:05:34 - With all the technological advancements we are making, is there any tiny chance that we might be able to see the Grabby Aliens in the near future?