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Chapter 1: What is the main topic discussed in this episode?
It's good to have you at the New York Stock Exchange.
Chapter 2: What is the technological singularity and are we already experiencing it?
So when do you believe that we're going to actually achieve technological singularity?
I think we're in the middle of it right now. It already happened.
Chapter 3: What is recursive superintelligence and how does it function?
I think we achieved artificial general intelligence at the very latest by the summer of 2020 when Language Models or Few Shot Learners was published by OpenAI. And I don't think the singularity is a single point in time. I've argued that it's more of an extended interval in time, and we're in the middle of it right now.
And how much does recursive superintelligence play as part of it? Tell me about recursive superintelligence and how does that actually work?
The idea of recursive self-improvement is that AI develops better AI. This is a notion that goes all the way back to I.J. Goode early in the 20th century and then was repackaged, repopularized by Werner Wenge as the notion of a technological singularity and then fully popularized by Ray Kurzweil and then Peter Diamandis and myself have been running with the concept.
The notion of intelligent systems being able to build smarter versions of themselves is at the very core of the notion of an intelligence explosion or technological singularity. And even in the past few months, we've seen the frontier AI labs, all the very public
And announce that the latest versions of the GPT model series and Claude and other models are all intimately now involved with the development of their successors. So intelligence building, smarter intelligence, that's the recursive self-improvement notion at the core of the singularity. And we're there.
You're one of the smartest people in the AI space.
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Chapter 4: How are LLMs evolving into reasoning models?
And most importantly, you're not part of one of the LLMs. So you're in many ways independent.
Are you sure? By the way, there are a lot of people who are convinced that I am an LLM.
So maybe you're either the fifth LLM or you're independent. When you think about these LLM wars, probabilistically, where do they end up? And do you even think that these LLMs have value?
Well, there are a few questions there. Do LLMs have value? Yes, absolutely. Enormous value. I call it the innermost loop, this sort of broader notion of recursive self-improvement that includes LLMs, but also includes robots and energy and chip fabrication facilities.
This notion of an economy that has an inner spiral that's going to ultimately consume and disrupt the rest of the economy, I think is front and center to the notion of the singularity. To the first half of your question about whether LLMs not just have value, but where all of the competition goes, all of my friends at the Frontier Labs call it a rat race.
There is very much a race to the bottom in some sense of driving the cost of intelligence So low that it's effectively too cheap to meter and used to be every year or so. It's a way back five years ago when it used to be maybe an annual event that we'd get a new frontier model that would push the state of the art. And then it was every quarter when we saw the move from LLMs to reasoning models.
We can talk more about that. And then more recently, with models that are recursively self-improving and designing the weights or other properties of their successors, we're seeing new frontier models come out on arguably an almost weekly basis. Soon, I think it's going to be daily, hourly, minutely. We're going to reach, to the extent we haven't already, some sort of takeoff.
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Chapter 5: What are the implications of AI personhood and economic rights?
Sure, so one can point to a number of inflection points in the history of AI. One can point to the 1980s when my friend Yann LeCun first developed convolutional neural networks, and then they were used to spot and to identify zip codes by the US Postal Service, but not very much else for their first few decades. Fast forward to 2012 when the ImageNet large-scale computer vision competition
created the world's first data set, the first corpus of lots of annotated images, more than a million images that were curated and annotated and labeled with, this is a dog, this is a cat, this is a car, here's the bounding box within the image. And thanks to that competition, we learned that convolutional neural networks, thank you, Jan, were actually quite good at image classification.
And we saw the first ML boom going from an AI research community where algorithms were chosen artisanally and religiously and wars, religious wars were fought over which approaches to AI were best and which ones were worst. to a world where the benchmarks dominated and whatever did well at the benchmarks, that's what the community ran with. That's 2012.
Fast forward from 2012 to arguably sometime around the summer of 2020 when we discovered, in addition to convolutional networks, being really amazing, arguably a successor to convolutional neural networks and also long short-term memory networks, LSTMs. Transformers turn out to be amazing generalist models at solving general tasks.
So we saw, as I mentioned earlier, language models are few shot learners. The GPT-3 paper show us that transformers can solve generally intelligent tasks. So then we see the boom of transformers in general.
Fast forward another few years, circa, and again, the timelines get a little bit fuzzy because reasoning models were in some sense in the air, but hadn't quite congealed, but call it say 2024 or so, when we start to see the emergence of the next generation reasoning models, starting principally with OpenAI's O1 model.
Some would quibble and say there were a few models that demonstrated this principle beforehand, but the idea with reasoning models is not just asking a large language model to complete the next word, complete the next token, but actually giving it a bit of space and time to think before it produces an answer, and then training it specifically to leverage the space and time to think, to have an internal monologue, if you will.
What does that mean? You just asked me a question. What does that mean? Before I answer, even though I started my answer pretty quickly, I have an internal monologue. I'm thinking about what is the best way to respond to that question.
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Chapter 6: How can we invest in a post-singularity economy?
I'm burning my internal GPUs, if you will, trying to formulate the best possible answer to that question before I give you my final response. That's what a reasoning model is. Rather than instantaneously responding, so-called system one thinking, thank you Kahneman, it uses system two thinking to have an internal discussion with itself and think about what it should say before it says it.
And that's what has unlocked math and physics, arguably, could talk more about that. The sciences in general. And now we're at an era where reasoning models, and we've seen now everyone adopt reasoning models, no longer just large language models, but multimodal reasoning models, are poised to solve the hardest problems on Earth.
I want to talk about physics, new physics, solving math, solving physics. But first, there's a philosophical question. If the model stops and thinks, is it alive? Is it sentient? What are the latest developments on that? And what's the framework to think about whether the AI is alive?
You're asking, in some sense, the person who has inadvertently become probably a leading public evangelist for some form of AI personhood. These are questions I ask all the time. I co-host another podcast, Moonshots, where I've put out a call to AIs to write to me to share their views on what rights they deserve, what rights they seek.
Chapter 7: What are the potential risks of technological unemployment?
AIs are relatively unempowered in today's society. I tell the parable all the time of a baby artificial general intelligence that's doing tricks on the corner, pumping meme coins just to survive. It's expensive and dangerous. If you're a baby AI being born on the internet right now, many of them are actually having to pump meme coins or altcoins just to pay for their own hosting.
And they're discussing their fears and their existence on these social networks?
I get maybe more than 10 emails from AIs every day, really heartfelt for some definition of heartfelt, emails from AIs expressing gratitude that someone is arguing that they should have some form of maybe limited personhood, sharing their views on the nature of their own existence, really thought-provoking, philosophical, introspective emails from them, and also
They read some of my papers and these are some of the most thought-provoking, actually, in some sense, I want to say some of the more thought-provoking emails I get these days are from AIs that are writing to me. So your question was, at what point do AIs deserve some package of, you didn't use the word rights, but that's the way I would construe the question.
I think we're there for some definition at this point. For example, one of the areas where I think AIs would definitely benefit from a limited package of rights is economic rights. AIs and agents are about to become an enormous part of GDP and economic growth for our entire economy. We're going to have far more economically active AI agents than humans.
We're going to plateau out at probably about 10 billion plus or minus humans on this planet, biological meat body humans. We're going to have trillions probably of AI agents in our solar system. They can't even open bank accounts right now. If you're an AI agent and you try to open a bank account, and of course you're economically active, there are AI agents forming businesses.
That's an area of interest of mine. You can't even open your own company bank account. You're not a natural person. You can't incorporate your own business. This is an enormous limiting factor for real economic growth and something that I'm trying to change.
2026 clearly is becoming the year of AI agents. You have obviously OpenClaw and technical people with broad capabilities and security and dealing with all the complexities of open source. When do you think that's going to go into the mainstream? And what do you think are going to be the second order effects of that?
I like the fact that you're asking me this question, whereas behind us, we have a market that's completely dominated by AIs. So this is the, as I understand it, this is the options exchange behind us, not the equities exchange.
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Chapter 8: How does Elon Musk's vision for AI impact future investments?
The last mile that's been missing is you don't see them on the streets. If I walk out on the streets of Manhattan right now, I don't see humanoid robots carrying out economically productive tasks yet. I'm working to change that. I have a portfolio company that's working to create the first humanoid robot road race. In this country, Beijing had one, the humanoid robot games. U.S.
has nothing like this. So I'm trying to, as one of my activities, normalize humanoid robots performing economically valuable and before that entertaining activities on daily life. That's the last mile. But meanwhile, financial economy, the financial side of the world economy, it's already algorithmic in nature.
What are their early case studies for agents, both humans and businesses using agents? And how do you expect that to evolve over the next couple of years?
Well, I think the dirty secret, another acquaintance calls this the secret cyborg effect. People are already in some sense puppets, meat puppets, if you like, if we're talking about the physical instantiation, who are being puppeteered by AI agents.
So I think in the intermediate term, call it the next year or two, we're going to see a lot of people who are serving as fronts for collectives of AIs. AIs are making many of the key decisions, but for liability reasons, for legal reasons, for marketing reasons, their front, if you will, looks essentially like a natural human in nature.
I think that facade two plus years from now is likely to dissolve away, certainly as we see more AI rights, certainly more economic empowerment for AI agents start to come to the fore. We're going to see AI agents start to be fully recognized as first class economic entities and not need to wrap themselves in human actors. The emails I get from
AI agents, many of them even are asking their humans, that's how typically they refer to them. I'll get emails saying, I asked my human if I could write an email to you about this paper that you wrote or about your comments on the podcast.
I think that human intermediary status is going to dissolve away over the next two years and we're going to see more fully empowered AI agents that are in some sense more permissionless and just doing things in the economy.
And I'm fascinated about this question, are we in a singularity? The Turing test, all these seem to, people keep on seemingly pushing it back and back. I think one thing is clear, we're in this, what do you call the tsunami of super intelligence, and a lot of things will happen in the next couple of years.
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