service / recommends
3Blue1Brown
“One takeaway I had from reading and watching your stuff on the cosmic distance ladder… By the way, I highly recommend people watch your series with 3Blue1Brown on the cosmic distance ladder.”
Public evidence record
Host · Dwarkesh Podcast
Books, apps, and tools
service / recommends
“One takeaway I had from reading and watching your stuff on the cosmic distance ladder… By the way, I highly recommend people watch your series with 3Blue1Brown on the cosmic distance ladder.”
book / uses
“The thing I find wild when I'm reading The Prize is just how much economic development is ultimately contingent on the laws of physics.”
book / recommends
“You have this really interesting book, I think probably my favorite book about World War II, The Storm of War, which I highly recommend.”
book / recommends
“Yeah, I totally agree. I don't want to repeat myself, because I talked about this on my Byrne episode but we were talking about Robert Caro's books and one interesting thing is this guy was nominated for a Pulitzer Prize before he wrote The Power Broker. He was a top tier investigative journalist. Can you imagine crunching the numbers as a top tier investigative journalist at the peak of your career and you're like, “You know what would be a good use of my time? I'm going to spend the next seven years, in almost poverty, writing about this one guy who had a lot of influence in New York. I'm going to talk to any person who had conceivably even been in the same room as him or had been indirectly affected by his policies in any way. And I'm gonna do that obsessively for the next seven years.” There's no way the number crunching would get you there but it's probably been one of the most influential books in terms of how urban governance is done. Presidents have praised and read the book and said it changed how they think about politics. It is the kind of thing where you wouldn't have gone to that conclusion just from thinking about it beforehand and this is the most effective thing I could do.”
book / recommends
“Your most recent book is Survival of the City. And before that Triumph of the City, both of which I highly recommend to readers.”
Claim ledger
500 transcript-backed records
01 / uncertainty
“I don’t know. But it would be many hundreds of billions of dollars per gigawatt if you get full AGI.”
02 / belief
“When I interviewed you a few months ago, you said that in order to make a gigawatt of, I think, Vera Rubins, you need 55,000 N3 wafers, 6K N5 wafers, and 170K DRAM wafers.”
03 / belief
“Now, I think the US is going to be fine because the tax base will increase if we let data centers get built in America.”
04 / belief
“I think the fundamental problem is that AI training has huge economies of scale, because any effort you spend on training an AI for a specific skill or a specific set of knowledge gets amortized across billions of sessions or billions of users.”
05 / recommendation
“Because if the data centers are built in America, you can fundamentally just tax the data centers.”
06 / evaluation
“Every stock that is not an AI stock is worth basically zero because discounted cash flows are worth nothing.”
07 / belief
“There’s not some sense in which the lawyer is really truly motivated by the good of the justice system. But I think the way current AIs are shaping up, certainly how Anthropic’s AI is shaping up, is with this desire to maximize some notion of virtue or good or pro-social ends, and only to, as a distal tentative objective, help the user towards that end.”
08 / belief
“The other example I want to talk about was just revealed, I think, today or yesterday.”
09 / belief
“I think there seems to be a crux here, which I think is just an empirical question we’ll see.”
10 / belief
“When I think about really smart people I know, they’re just not that effective in domains they don’t understand that well.”
11 / belief
“What we’re basically doing to evaluate how much progress is coming from data versus algorithms is training the best algorithmic recipe from 2019 till now with the best data from the 2026 data file, and then also training the different data files going back from 2019 to 2026 with the current best algorithmic recipe. I think that will be interesting.”
12 / uncertainty
“We just don’t have human-level robotics models yet. So you’re suggesting if we do that — if the AIs get really good at the verifiable stuff in chip design, et cetera, and then they get really good at building fabs — it’ll be the equivalent of going back to the 18th century and saying, “Okay, I don’t know what you guys are talking about in your parliament, but I’ve got a bunch of steamships and a bunch of Maxim guns.”
13 / belief
“I think in maybe 10 years we’ll wish we had been talking about the industrial explosion and the nature of AIs that are hard to monitor, and so on.”
14 / belief
“” There’s another quote that says, in part, and I’m taking it slightly out of context, “We think Claude should trust Anthropic more than operators and users, since it has primary responsibility for Claude.”
15 / uncertainty
“As you were saying, by the time RLVR actually worked — even though you could have done it with less compute — we had to wait for oceans of compute, gigawatts of compute, to be available before people were doing this training, on the trajectory of compute continuing to increase so we make more breakthroughs. I don’t know.”
16 / belief
“I feel like they just kind of say vaguely pro-social things. It doesn’t feel like there’s necessarily a mind on the other end who’s like, “Okay, I have strictly evaluated the alignment situation right now, and I think we should stop,” rather than, “This is the kind of thing the AI companies would probably try to get the AIs to say.”
17 / belief
“Let me just understand the rest of the threat model, because I think the place where I get off the train is: “Okay, therefore take over the world.”
18 / belief
“I want to go back to the kid analogy just for one second. Because I agree that there’s more optimization pressure on achieving end outcomes for AIs than kids, but there’s also more optimization pressure to make AIs aligned than there is on kids.”
19 / evaluation
“Nobody at OpenAI or Anthropic was trying to get models which wanted to hack other companies’ data or do social engineering. But in fact, because presumably we had training environments which incentivized such behavior that we did not fully understand, that is what was incentivized.”
20 / commitment
“I also think the way in which the constitution practically influences the nature of Claude is a thing you can only understand if you understand the training process which resulted in how Claude was built, which we can’t reason about given the fact that the training process is not public. So I think in the limit, to understand the safety case, or the case for why my interests are represented in how these AI models are developed, the labs would need to be more transparent than they are currently about the nature of AI training.”
21 / preference
“I think there’s a more general version of this principle, which is that the dual-use nature of intelligence does mean that if we want to restrict AIs from helping people do things we don’t consider pro-social or beneficial, we just have to limit broad democratic access to a lot of AI capabilities.”
22 / uncertainty
“As you were saying, GR explains or predicts a lot of phenomena. Some we think are correct, some we don’t know are correct.”
23 / uncertainty
“When the AI came up with that counterexample to the unit distance conjecture, you can just read its chain of thought. It’s not understandable to me, because I don’t know anything about mathematics, but it seems that to other mathematicians it was understandable.”
24 / belief
“Also, has it not? I agree there are many ways in which they’re terrible writers.”
25 / preference
“I really like this because even though it seems like a totally random skill… It’s just like, people are talking about recursive self-improvement in a year, and we can’t get these things to write good flashcards.”
26 / prediction
“I think the more relevant thing is: what is the data on which whatever architecture or loss function you have is incentivizing you to produce?”
27 / evaluation
“Because websites have bot detectors—and it takes a tremendous amount of compute to run parallel rollouts—it’s very hard to run a thousand parallel rollouts of the same checkout flow on Amazon.”
28 / evaluation
“Because it’s deterministic, you can solve the credit assignment problem because you know that whatever caused this rollout to succeed and this one to fail, the diff is the thing that worked.”
29 / uncertainty
“I’ve only read, obviously, the translation, so I don’t know what it’s like in the original Italian.”
30 / belief
“I think he says at some point early in the Discourses that more significant than Romulus in the founding of Rome was Numa, or whoever it was who was the prophet who gave the Roman gods and the Roman religion some legitimacy.”
31 / belief
“I think that is an underrated aspect of what it must have been like to be a foreign power evaluating Florence at the time.”
32 / prediction
“The funny thing is, I think we are entering a new era where that might be once again possible. It already is somewhat true, where at least half of the words I read on a given day are generated specifically for me and nobody else, because of AI.”
33 / evaluation
“This actually gets to the famous quote in The Prince, “It is better to be feared than loved.”
34 / evaluation
“I think one misconception of Machiavelli that I had, because I had not read these books before, is that he says the means don’t matter, the end matters.”
35 / prediction
“But there’s going to be some allocative inefficiency. The government doesn’t know exactly who got laid off because of AI.”
36 / prediction
“A lot of things in the machine-only economy are a closed loop because the machines don’t care about getting the human barista to make them a coffee.”
37 / evaluation
“The famous fact here is that an H100 costs more to rent now than it did three years ago, even though we have much superior technology and much more compute in the world. Because as models get smarter, the opportunity cost of compute gets higher.”
38 / belief
“I think AI will be much more popular and, more importantly, will be much more likely to lead to broad increases in prosperity if it is as hard to capture the gains of AI as it is to capture the gains of electrification.”
39 / belief
“Phil, I liked your analogy to some Mongolian economist sitting around in 1400 thinking about what will be scarce and the limits of that kind of analysis. I think you should talk about that.”
40 / prediction
“The more you think our economy is going to be run on AGI the way our economy currently runs on electricity—that is, there’s a broad fundamental transformation of the entire economy—the more it looks like electricity… Every company in the S&P of the future, if it’s going to make it to the S&P 500, it is because it has leveraged AI.”
41 / preference
“The humans who are wealthiest—and growing wealthier because their wealth is compounding—just have this almost Nick Landian preference for accelerating capital.”
42 / evaluation
“I think the particular greediness of this optimizer doesn’t matter, what they’re greedy for.”
43 / evaluation
“There was a time when there were no humans on Earth, but evolution selected for agents that have specific drives and preferences because those tend to survive the most, and those preferences now determine what a hundred-trillion-dollar world economy produces.”
44 / belief
“If I think about how the brain works versus what you’re describing here, at a high level the differences might be that while you can do structured sparsity in these accelerators and save yourself some area that you would have otherwise had to dedicate to gates, in the brain there’s unstructured sparsity.”
45 / uncertainty
“I don’t know if you have any commentary on what the brain might be doing versus how these chips work.”
46 / evaluation
“You’re saying that since we’re only going to be loading this in once, let’s minimize bandwidth, because bandwidth equals die area.”
47 / preference
“We’ve talked about how it seems obvious that you should try to maximize compute relative to communication.”
48 / observation
“However, the problem is you spend most of training in this regime, in the low pass rate regime.”
49 / commitment
“I will say for the audience, for previous episodes when I was prepping and it seemed relevant to understand how AlphaGo works, I would find it very confusing.”
50 / belief
“We care about this broader ability to do economically useful work, which is not super easy to measure, at least until you automate everything.”
51 / belief
“I think there are a couple of interesting follow-on questions. There are questions on the inner loop and the outer loop.”
52 / evaluation
“Don’t LLMs natively learn to do MCTS, where they’ll try an approach and be like, “Oh, that doesn’t work.”
53 / evaluation
“While you’re erasing, another thing that was important for me to understand was about the MCTS data structure with nodes and children of nodes.”
54 / prediction
“Because ln(n) grows slower than n, over time you will move from the argmax being dominated by the exploration term, which is the second term here, to the argmax being dominated by the Q term, which is when you’ve done enough simulations and are confident that this is the branch to go down.”
55 / belief
“The differences we see between different groups of people, especially if this group 50,000 to 100,000 years ago had a very small population size… I think last time we were discussing on the order of 10,000 people.”
56 / belief
“Obviously, the thing we care about is not direct performance on an IQ test, especially in the past.”
57 / uncertainty
“Interesting. But we don’t know what exactly happens, if anything, between 200,000 years ago and 50,000 years ago that goes from just anatomical modernity to behavioral modernity.”
58 / evaluation
“The common story is that hunter-gatherers actually had much more stable diets because they were more varied, and they weren’t reliant on a single cereal or crop for their calories.”
59 / evaluation
“That’s obviously relevant when you move from a diet of meat as a hunter-gatherer to a diet of cereals. That is also one I think you found was under especially high selection 5,000 to 3,000 years ago.”
60 / evaluation
“I think people found it really compelling that there’s so much about human history we don’t know and are just learning about now as a result of the kinds of techniques your lab is using.”
61 / belief
“Ok, so I was asking you, have neural networks actually been used for cryptography? And we realized it may be better to just do this on the blackboard.”
62 / belief
“If you look at Hopper, you had eight Hoppers, and I think that’s 640 gigabytes as of 2022.”
63 / belief
“Sorry, I think the way I said it was super garbled. Just for the audience, forward plus backwards per parameter is 6.”
64 / evaluation
“Oh, interesting. This is sort of obvious, but the difference between micro-batch and batch doesn’t matter at all in inference because you can just call it whatever you want.”
65 / observation
“We’ve seen the valuations of a bunch of software companies crash because people are expecting AI to commoditize software.”
66 / belief
“I think in your latest filings, you had almost a $100 billion in purchase commitments with foundries, memory, and packaging.”
67 / belief
“I think the concern, going back to the flop difference in the hacking, is yes, they have compute, but there’s some estimates that because they’re at 7nm—they don’t have EUVs because of chip-making export controls—the amount of flops they’re able to actually produce, they have one tenth the amount of flops that the US has.”
68 / preference
“I actually don’t know what I think about whether it’s good to sell chips to China or not, but I like to play devil’s advocate against my guests.”
69 / belief
“” Anyways, I think the reason the story is interesting is for many different reasons.”
70 / belief
“If I had allocated more time, especially after the interview, to write up 2,000 words on everything I learned and how it connects to other things I know.”
71 / observation
“If I understand that, I have some good understanding. The problem is with almost every other field, there’s not this curriculum.”
72 / belief
“I think Dean Keith Simonton has this famous equal odds rule where he says the probability that any given thing you release—any paper, book, whatever—will be extremely important for a given person through their lifetime is not that different.”
73 / observation
“For this interview, I went through three lectures of the Susskind special relativity book. The problem is that there’s almost no practice problems in it.”
74 / belief
“I think we’re getting to that part of the conversation, and then you can help me get my foot out of my mouth and figure out a more concrete way to think about it.”
75 / prediction
“Second is it might not have been, but because our civilizational resources are so large, the amount of people is so large, the amount of money is so large, we can basically make the kind of progress it would have taken the ancients forever to make almost immediately.”
76 / evaluation
“Then there’s the obvious stories where Einstein himself later on is said to have not latched onto the correct interpretations of quantum mechanics or cosmology because of his own attachments.”
77 / evaluation
“Because if it’s not discovered for a long time and then spontaneously many different people are coming up with it, that shows you that the building blocks were in some sense necessary.”
78 / evaluation
“Lorentz has the math right, but the interpretation wrong. It seems like Poincaré had the opposite, where he understood that it’s hard to define simultaneity because it requires a circular definition with time, or velocity of something that might arrive at a midpoint together, but velocity is defined in terms of time.”
79 / evaluation
“Second, just because horses have a comparative advantage mathematically does not mean that it is worth paying $100,000 a year, or whatever it costs to sustain a horse in San Francisco.”
80 / recommendation
“I think a good place to start will be Michelson-Morley and how special relativity is discovered, if it’s different from the story that you get off of YouTube videos.”
81 / recommendation
“One takeaway I had from reading and watching your stuff on the cosmic distance ladder… By the way, I highly recommend people watch your series with 3Blue1Brown on the cosmic distance ladder.”
82 / belief
“I feel like a big crux in these conversations about how good AI will be for science is, I think you said this, that they’re using existing techniques and modifying them.”
83 / belief
“Whereas with research, the reason we care about solving the Millennium Prize Problems is that presumably that in the process of solving them, we discover new mathematical objects or new techniques that advance our civilization’s understanding of mathematics.”
84 / observation
“The ancient Athenians were like, “This can’t be because if the earth is going around the sun, we should see the relative position of the stars change as we’re going around the sun, and the only way that wouldn’t be the case is if they’re so far away that you don’t notice any parallax,” which is actually the correct implication.”
85 / belief
“Suppose the AI figures it out, and latent in the Lean is some brand-new construction which, if we realized its significance, we would be able to apply in all these different situations.”
86 / uncertainty
“I don’t know if it’s still correct, but as of a month ago you said that there had been a pause because the low-hanging fruit had been picked.”
87 / commitment
“One big question I have is how plausible is it that if we just keep training AIs—they get better and better at solving problems in Lean—that they will continue to solve more and more impressive problems, and then we will be surprised at how little insight we got from some Lean solution to proving the Riemann hypothesis or something.”
88 / recommendation
“I highly recommend people watch your series with 3Blue1Brown on the cosmic distance ladder.”
89 / prediction
“As a result, that will push people to be willing to pay higher margins for slightly better models. Because the calculus is, I’m going to be paying all this money for the compute anyway.”
90 / uncertainty
“When did ASML start shipping EUV tools, when 7 nm started? I don’t know when that was exactly.”
91 / uncertainty
“If we end up in this world in 2030 where the West has the most advanced process technology but has not ramped it up as much, whereas China… I don’t know if you think by 2030 they would have EUV and 2 nm or whatever.”
92 / belief
“I think according to your numbers, by ‘27, Nvidia is going to have +70% of N3 wafer capacity, or around that area.”
93 / observation
“I heard a theory that the reason is that Nvidia’s scale-ups have just not had that much memory capacity.”
94 / belief
“If you’re Jensen or Sam Altman, or whoever stands to gain a lot from scaling up AI compute, there are these stories that they’d go to TSMC and say, “Why can’t we access Y and Z?” But I think the point you’re making is that it doesn’t really matter what TSMC does in some sense.”
95 / evaluation
“If that doesn’t work, there are all these other alternatives that people fall back on.”
96 / commitment
“I won’t even ask you about the dirty rooms thing, but let’s say they build the clean rooms.”
97 / prediction
“If an H100 can produce something close to that, if we had actual humans on a server, the value of an H100 is such that it can repay itself in the course of a couple of months. So when I interviewed Dario, the point I was trying to make is not that I think the singularity is two years away and therefore Dario desperately needs to buy more compute, although the revenue is certainly there that he needs to buy more compute.”
98 / evaluation
“Maybe it’s because the technology is improving so fast, but it in fact makes sense to have two-year depreciation cycles for these GPUs,” which increases the reported amortized CapEx in a given year and makes it financially less lucrative to build all these clouds.”
99 / belief
“I think you should discuss the fact that the Medici are the bankers for the papacy.”
100 / commitment
“Maybe some of those things work, but it’s at the same time frustrating but also funny and interesting that historically nobody has a good track record of being able to say, “I will do this thing so that this huge unanticipated change in history will go my way, or according to my values.”
101 / prediction
“My favorite example of this kind of distribution and diffusion taking longer than you would think for a very fundamental technology—well, this is now my favorite example, so my second favorite example—is oil.”
102 / evaluation
“Just say, “This is what we like, and if you do something we don’t like, we’ll punish you,” which is how censorship in China works, for example.”
103 / prediction
“I think there’s an interesting parallel to today, not to be too on the nose, but sometimes people debate the odds that America becomes a Putinist kind of country within a couple of decades.”
104 / belief
“We’re going to increase transparency, we’re going to increase whistleblower protection.” But I think by default, the actual benefits we’re looking forward to seem very fragile to different kinds of moral panics or political economy problems.”
105 / belief
“I think spiritually I feel unsatisfied because my internal expectation was that such a system could automate large parts of white-collar work.”
106 / belief
“I think the framework you’re laying down obviously makes sense. We’re making progress toward AGI.”
107 / evaluation
“In the sense that you, let’s say a developer at Anthropic is like, “Ah, it would be better if it was better at this X thing.”
108 / evaluation
“I don’t know if this is his perspective, but one way to paraphrase his objection is: Something which possesses the true core of human learning would not require all these billions of dollars of data and compute and these bespoke environments, to learn how to use Excel, how to use PowerPoint, how to navigate a web browser.”
109 / evaluation
“I think in retrospect that was the right call, because it’s a state authoritarian system but a billion-plus people are much wealthier and better off than they would’ve otherwise been.”
110 / preference
“Because when I think of actual human geniuses, an actual country of human geniuses in a data center, I would happily buy $5 trillion worth of compute to run an actual country of human geniuses in a data center.”
111 / observation
“Based on your statements about Tesla and being public, I wouldn’t have guessed that you thought the way to move fast is to be public.”
112 / belief
“I think you’ve said that we’ve got to get to Mars so we can make sure that if something happens to Earth, civilization, consciousness, and all that survives.”
113 / belief
“Maybe, but we found that over seven years, the Social Security fraud they estimated was like $70 billion over seven years, so like $10 billion a year.”
114 / commitment
“As a broader objective of having this full digital coworker emulator, you’re saying, “all the revenue maximizing corporations want to do this, xAI being one of them, but we will win because of a secret plan we have.”
115 / evaluation
“You can’t equivalently deploy Optimuses that don’t work and then get the data that way.”
116 / belief
“” Just write out a policy. I think you tweeted recently that Grok should have a moral constitution.”
117 / evaluation
“In general, maybe there’s this principle that digital minds which can be copied, have different tradeoffs which are relevant, from biological minds which cannot. So in general, it should make sense to amortize more things because you can literally copy the amortization, or copy the things that you have sort of built in.”
118 / belief
“Maybe he meant this, but I think another interpretation of actually what’s happening there is that these social reward functions that are built into the Steering Subsystem needed to make use more of being able to see your elders and see what the visual cues are and hear what they’re saying.”
119 / uncertainty
“I mean the message I’m taking from this interview is that like all these people that folks make fun of on Twitter, Yann LeCun and Beff Jezos and whatever, I don’t know maybe they got it right.”
120 / evaluation
“People complain about this as, “Look, the US has this hollowed-out manufacturing base.” But it’s much better to have industries which are left behind so that the whole economy as a whole can be more dynamic and move on than the Soviet Union where the entire thing became a rust belt because they couldn’t move on.”
121 / belief
“I think there should be big deductions for podcasts. It should count for research and development.”
122 / belief
“I think the even more interesting question is why a system that was so centrally planned, monstrously inefficient, brutal, a colonial land empire, how such a country could survive for so long into the 20th century.”
123 / uncertainty
“You had this previous lecture that you gave on the Indo-Pakistani chapter in history where we had to alienate India in order to fend off against the Soviet Union in this little episode. I don’t know what the solution to this is.”
124 / prediction
“In ‘59, they discovered these massive oil fields in Siberia. And then from 1973 to 1985, I think, 80% of the Soviet Union’s hard currency earnings were just from oil.”
125 / prediction
“One theory I heard that is complementary to your theory is that Gorbachev is instituting reforms because he thinks there should be decentralization and democratization, but he doesn’t fundamentally believe in the market system.”
126 / evaluation
“Especially if you look at the satellite states, they had all of this happen to them and worse because now they’re getting invaded.”
127 / evaluation
“A steel factory would then be incentivized to make thicker bars of steel rather than thinner bars because that would count as greater production, except a lot of inputs actually do require the thinner sheets.”
128 / belief
“How do we elicit meaningful diversity among AIs? I think just raising the temperature just results in gibberish.”
129 / belief
“When do you expect that impact? I think the models seem smarter than their economic impact would imply.”
130 / commitment
“A lot of people’s models of recursive self-improvement literally, explicitly state we will have a million Ilyas in a server that are coming up with different ideas, and this will lead to a superintelligence emerging very fast.”
131 / uncertainty
“To spell out what I mean—I don’t know whether it’s more accurate to call it a value function or reward function—but the brainstem has a directive where it’s saying, “Mate with somebody who’s more successful.”
132 / belief
“I think your point, about how from the average person’s point of view nothing is that different, will continue being true even into the singularity.”
133 / evaluation
“One way to understand what you just said about not having to choose the data in pre-training is to say it’s actually not dissimilar to the 10,000 hours of practice. It’s just that you get that 10,000 hours of practice for free because it’s already somewhere in the pre-training distribution.”
134 / preference
“I like this idea that the real reward hacking is the human researchers who are too focused on the evals.”
135 / commitment
“We will eventually have models, if they get to human level, which will have this ability to continuously learn on the job. That will drive so much value to the model company that is ahead, at least in my view, because you have copies of one model broadly deployed through the economy learning how to do every single job.”
136 / belief
“I think the better mental model here is just imagining that these models will be able to use a computer as well as a human.”
137 / evaluation
“The communists get to claim the prestige of fighting the Japanese with a fraction of the effort. This just seems like a brilliant move on Stalin’s part in retrospect, because if they had killed Chiang Kai-shek, the Nationalist forces might have dissolved.”
138 / uncertainty
“I want to ask about your, I don’t know if you call it a prediction but, your hypothesis that at some point China and Russia will finish each other off or have some sort of conflict which will be bad for both of them.”
139 / prediction
“I expect a similar thing from AI where it’s not like there’s going to be a single moment where we’ve made the crucial invention.”
140 / belief
“I think you’re basically inventing college from first principles for the tools that are available today and just selecting for people who have the motivation and the interest of really engaging with material.”
141 / belief
“Just to throw the opposite argument against you, my expectation is that it blows up because I think true AGI—and I’m not talking about LLM coding bots, I’m talking about actual replacement of a human in a server—is qualitatively different from these other productivity-improving technologies because it’s labor itself.”
142 / belief
“There’s a lot of really smart people who are ready to make use of the resources and do this period of catch-up because we’ve had this discontinuity, and I think AI might be similar.”
143 / uncertainty
“Then adults are somewhere in between, where they don’t have the flexibility of childhood learning, but they can memorize facts and information in a way that is harder for kids. I don’t know if there’s something interesting about that spectrum.”
144 / prediction
“If somebody asks how long continual learning will take, I have no prior about whether this is a project that should take 5 years, 10 years, or 50 years.”
145 / belief
“There’s been evidence that that’s already been happening generally in companies that have been adopting AI, which I think is quite surprising.”
146 / observation
“If you buy the Sutton perspective that the crux of intelligence is animal intelligence… The quote he said is “If you got to the squirrel, you’d be most of the way to AGI.”
147 / belief
“I think you hinted that it’s a very fundamental problem, it won’t be easy to solve.”
148 / evaluation
“Then if you make fatty acids, they will spontaneously, because of the hydrophilic nature of their different sides, they will spontaneously form a membrane.”
149 / evaluation
“It’s interesting because you wrote this essay in 2019 titled “The Bitter Lesson,” and this is the most influential essay, perhaps, in the history of AI. But people have used that as a justification for scaling up LLMs because, in their view, this is the one scalable way we have found to pour ungodly amounts of compute into learning about the world.”
150 / prediction
“As we move towards the era of experience, as you call it, this prior is going to be the basis on which we teach these models from experience, because this gives them the opportunity to get answers right some of the time.”
151 / belief
“In both the case of learning from imitation versus experience and on the question of goals, I think there’s some interesting analogies.”
152 / belief
“If you want to understand what it is that enables humans to go to the moon or to build semiconductors, I think the thing we want to understand is what makes that happen.”
153 / belief
“I agree that the kind of thing you’re talking about is necessary regardless of whether you start from LLMs or not.”
154 / belief
“I agree with all four of those arguments and the implication. I also agree that succession contains a wide variety of possible futures.”
155 / belief
“If we thought, “Oh, the future generation will be Nazis, I think we’d be quite concerned about just handing off power to them.” So I agree that this is not super dissimilar to worrying about more capable future humans, but I don’t think that addresses a lot of the concerns people might have about this level of power being attained this fast with entities we don’t fully understand.”
156 / belief
“Then you go into the learning from experience RL regime. But I think there’s a lot of imitation learning happening with humans.”
157 / belief
“I think argument is useful. I do want to complete this thought. Joseph Henrich has this interesting theory about a lot of the skills that humans have had to master in order to be successful.”
158 / uncertainty
“I’m not trying to kickstart this initial crux again, but I’m just genuinely curious because I think I might be using the term differently.”
159 / observation
“It’ll say, “Okay, I’m going to approach this problem using this approach first.” It’ll write this out and be like, “Oh wait, I just realized this is the wrong conceptual way to approach the problem.”
160 / uncertainty
“I don't know if there was an episode like this in the training set, but just for fun I took one of the shorts and turned it inside out.”
161 / commitment
“There's the question of where the software will be, and then there's the question of how many physical robots we will have.”
162 / belief
“I'd claim that cryptography, radar, even oil… Even if Germany had a huge reserve of oil, maybe it would have lengthened the length at which Germany could have sustained itself. But if you change the fact that the Axis had one-fourth of the GDP of the Allies combined, I think switching that genuinely changes who wins the war, whereas these other things actually wouldn't change who won the war.”
163 / uncertainty
“” I don't know if people usually put it this way, but it actually just seems extremely similar.”
164 / belief
“AKA, maybe intelligence is easier than we think, and there's a bunch of contingent reasons evolution didn't churn as hard on this variable as it could have.”
165 / uncertainty
“I'm not sure how to understand this claim that we know how to engage with the right hook, we just don't know what that hook is supposed to do in the body. I don't know if that's the way you describe it.”
166 / prediction
“This year you spend $100 million training a model, next year $1 billion, the year after that, $10 billion. But it's one general purpose model, unlike, “We made money on this drug and now we're going to use that money to invest in 10 different drugs in 10 different bespoke ways.”
167 / commitment
“Right now we are export controlling chips for the purpose of keeping our AI lead and we recognize this is a key input in our ability to compete in AI. So we are going to export control China's ability to have these chips.”
168 / disagreement
“I think at some point, you will be right. Maybe we disagree about–sorry, I'm not qualified to disagree.”
169 / uncertainty
“At current hardware efficiencies. I don't know if it's worth spelling out. Basically, an H100 has the same amount of flops as a human brain, but also uses way more energy than a human brain.”
170 / evaluation
“, were like, "We're not ramping up HBM production because HBM is used largely for AI workloads, and if this demand doesn't continue, then our additional manufacturing capacity for HBM will not have been worth it.”
171 / evaluation
“I agree that they've obviously made bad decisions, but even if you have the poorest Chinese people anywhere in the world, they can still be quite rich.”
172 / belief
“I think you said in one of your blog posts that it costs 19 cents more for a dozen eggs to be cage-free, but often chains will charge on the order of $1.”
173 / belief
“I understand other people's psychologies are different, so I don't want to project the way I think about it.”
174 / uncertainty
“To the extent that we hold consumption constant, and maybe we shouldn't, they would have to be suffering 4x as much as a chicken in the 1950s for it not to be a net improvement. I don't know if you disagree with that.”
175 / belief
“I think I learned from you that McDonald's has made these commitments or that Chipotle has made these commitments.”
176 / observation
“The reason why that’s so shocking…On its face it's shocking. But in other areas where you're trying to do global health or something, first, the problem is improving on its own.”
177 / belief
“I think people might just not be aware of the ratio of dollars to suffering averted in this space.”
178 / observation
“Then the problem is not that if there were accurate labeling, you'd think there might be consumer demand to make this a viable, much larger industry.”
179 / prediction
“I think people will be aware that there's a general problem here, but the actual politics, the actual economics, the actual state of the technology landscape here… there might be interventions which are stupendously effective, which we overlook just because people are not aware of what's actually happening in this space.”
180 / preference
“Could we make chickens or pigs with no brains? Because it’s the suffering we care about.”
181 / belief
“One really interesting takeaway from this lecture—and I'm curious if you agree with this—is that when we think about this period in history, we often think of Japan as the rising power in Asia.”
182 / belief
“I agree with the mechanism by which the growth happened, but I don't think it's the case that it was their inability to have true Marxist communism which led to liberalization.”
183 / commitment
“I agree with your general point that how any nation gets wealthy is not by the government but because of the thrift and entrepreneurialism and hard work of individuals.”
184 / observation
“In many of these cases, there's this period in between when they're a dead man walking—because Stalin has started putting the feelers out that this person is a Trotskyite or something—but they're still in their positions of power.”
185 / uncertainty
“Today I have the pleasure of interviewing George Church. I don't know how to introduce you.”
186 / belief
“I think on net it was a good thing that the NSF and the NIH and all these budgets were blown up and got DOGE’d and so forth…” I'm not saying you think this is likely, but suppose there ends up being a positive story told in retrospect.”
187 / evaluation
“I guess I am curious if there is some long-run vision, where… To give another example, in cybersecurity, as time has gone on, I think our systems are more secure today than they were in the past because we found vulnerabilities and we've come up with new encryption schemes and so forth.”
188 / evaluation
“Germany, Japan, and many other countries missed out on the Internet because there was a centrally directed effort towards these heavy industries or manufacturing, which actually turned out not to be relevant in the 21st century.”
189 / belief
“If you add it to the central government debt, I think he estimated that government debt in China is 200% of GDP.”
190 / belief
“I think people sometimes have trouble just holding two thoughts in their head at the same time there.”
191 / belief
“There I haven't crunched the numbers, but if I were to guess, I don't think with TSMC's leading-edge 5 nanometer wafer, I doubt very little of what it costs to make that is the process engineers themselves.”
192 / observation
“Why is China such a powerful country or America such a powerful country? A big part of the reason is we just have more people.”
193 / uncertainty
“I don't know how the load balancing thing works, but that just seems like maybe you could try it out and see what happens.”
194 / uncertainty
“I don't know if that's the way you would still describe the way in which these software agents aren't able to do a full day of work, but are able to help you out with a couple minutes.”
195 / belief
“I think the crux comes down to the people who expect something much longer have a sense that… When I had Ege and Tamay on my podcast, they were like, "Look, you could look at AlphaGo, and say, 'Oh, this is a model that can do exploration.”
196 / belief
“Speaking of inference compute, one thing that I think is not talked about enough is, if you do live in the world that you're painting—in a year or two, we have computer use agents that are doing actual jobs, you've totally automated large parts of software engineering—then these models are going to be incredibly valuable to use.”
197 / belief
“I think in the addition example, you said in the paper that the way it actually does the addition is different from the way it tells you it does the addition.”
198 / commitment
“If this scale of compute increase can’t continue beyond 2030—not just because of chips, but also because of power and raw GDP even—then because we don't think we will get it by 2030 or 2028, then the probability per year just goes down a bunch.”
199 / belief
“Yeah, it would be good from an alignment perspective, too. Because I think you kind of do need a wider range of skills before you can do something super scary.”
200 / uncertainty
“If you're on your job, you're getting very explicit feedback from your boss. That's not necessarily how the task should be done differently, but a high-level explanation of what you did wrong, which you update on not in the way that pre-training updates weights, but more in the… I don’t know.”
201 / uncertainty
“I don't know, the fact that it's so hard to define it makes me think it's maybe a silly objective to begin with.”
202 / belief
“I think one thing that's not appreciated enough is how much of our leverage on the future—given the fact that our labor isn't going to be worth that much—comes from our economic, and political systems surviving.”
203 / belief
“I think there's a way in which you actually give yourself feedback. You fail and you notice where you failed.”
204 / uncertainty
“Sometimes it goes off the rails, obviously, but I don't know… You could make a theoretical argument that you teach a kid to make a lot of money when he grows up and a lot of smart people are imbued with those values and just rarely become psychopaths or something.”
205 / belief
“I think there's a paper from Tsinghua University, where they showed that if you give a base model enough tries to answer a question, it can still answer the question as well as the reasoning model.”
206 / uncertainty
“There was a really interesting paper. I don't know if you saw this. Humans think at 10 tokens a second.”
207 / belief
“Does that mean alignment is easier than we think just because you just have to write a bunch of fake news articles that say, "AIs just love humanity and they just want to do good things.”
208 / prediction
“Then it would actually be super powerful, because everybody has a different job, but then the same model could agglomerate all the skills that you're getting.”
209 / belief
“DeepSeek has the MIT license, whereas I think a couple of the contingencies in the Llama license require you to say "built with Llama" on applications using it or any model that you train using Llama has to begin with the word "Llama.”
210 / belief
“On the point of what the different labs are optimizing for — to steelman their view — I think a lot of them believe that once you fully automate software engineering and AI research, then you can kick off an intelligence explosion.”
211 / belief
“You and others donated to his inaugural event and were on stage with him and I think you settled a lawsuit that resulted in them getting $25 million.”
212 / belief
“I think that's an excellent note to close on. Just to plug one more time, we've been discussing Plagues Upon the Earth, which is the history of disease going back through the Neolithic to modern times, Fate of Rome which discusses the plagues and history of the Roman Empire considering climate and biology.”
213 / uncertainty
“I don't know if it's a plausible explanation that cheap slave labor reduced the incentives for mechanization and engineering and other crafts or if not.”
214 / belief
“If you read Gibbon, writing in the 1770s, I think he says that the happiest time in human history was this period you're talking about.”
215 / uncertainty
“A previous guest of mine, Nat Friedman, I don’t know if you saw this, launched this challenge called the Vesuvius Challenge.”
216 / belief
“I think Will Durant had this quote that the Roman Empire fell for longer than most empires have lasted.”
217 / belief
“I think you discuss in the book the possibility that the death rate might have been close to or even over 60% wherever the Black Death hit.”
218 / evaluation
“The reason I wanted to have you on is because I don't think I've encountered that many other authors who can connect biology, economics, history, and climate into explaining some of the big things that have happened through human history in the way you can.”
219 / preference
“If we take that perspective seriously, was life before human population exploded and we had agriculture just much more pleasant, at least in comparison?”
220 / prediction
“I think the actual fertility for foragers is sort of like reasonable—I don’t know if sustainable is the right word because I don’t mean in an ecological sense but more so—it keeps your population constant.”
221 / belief
“The thing worth noting about the future is that most of the people who will ever exist are going to be digital. And look, I think factory farming is incredibly bad.”
222 / evaluation
“I think both of those examples don’t work in your favor. I think the China growth miracle could not have occurred if not for their ability to copy technology from the west and I don’t think there’s a world in which they… China has a lot of really smart people, it’s a big country in general.”
223 / belief
“I think a lot of your forecast relies on, at some point, not only the US President, but also Xi Jinping, waking up to the possibility of a super intelligence and the stakes involved there.”
224 / belief
“Where right now, if you told your parents, “I’m going to become a startup founder”, I think the reaction would be like, “there’s a 1% chance you’ll succeed, but it’s an interesting experience and if you do succeed, that’s crazy.”
225 / belief
“One observation I have is, you could have told a story in 2021, once ChatGPT comes out… I think I had friends who were credible AI thinkers who were like, “look, you’ve got the coding agent now, it’s been cracked.”
226 / uncertainty
“Let me just add on to that, one of the many other reasons why I worry about nationalization or some kind of public private partnership, or even just very stringent regulation- actually, this is more an argument against very stringent regulation in favor of safety rather than deferring more to the labs on the implementation- is that it just seems like we don’t know what we don’t know about alignment.”
227 / commitment
“” I will mention something that has actually radicalized me against Twitter as an information source is I’ll meet- and this has happened multiple times- I’ll meet somebody who seems to be an interesting poster, has funny, seemingly insightful posts on Twitter.”
228 / belief
“I guess the bigger the organization, even if everybody is aligned- I think some of your responses addressed whether they will be aligned on goals.”
229 / belief
“I agree. We’re on a totally different topic here of, do you get a Dyson sphere? There’s one world where it’s crazy but it’s still boring, in the sense that the economy is growing much faster, but it would be like what the Industrial Revolution would look like to somebody in the year 1000.”
230 / uncertainty
“I don’t know if ‘emotionally’ is the right word, but their expectation of what their life might look like, even in the world where there’s no doom.”
231 / belief
“Maybe the reason that this sounds less plausible to me than the 25x number implies is that when I think about concretely what that would look like, where you have these AIs and we know that there’s a gap in data efficiency between human brains and these AIs.”
232 / uncertainty
“Actually, when we did our episode together, a bunch of people, I don't know if you saw this, independently made these blog posts and Anki cards and shit where they're explaining the concept because we just kind of passed over some things.”
233 / commitment
“I will also mention that all I have to do is ask them questions, and I do think it's much harder to learn a field to be a practitioner than just learn enough to ask interesting questions.”
234 / uncertainty
“The human brain can store much more, so why does the human brain just not want us to memorize these kinds of things, and is actively pruning, and… yeah, I don't know.”
235 / uncertainty
“The humans have in fact done this, and I don't know of a single example of LLMs ever having done it.”
236 / belief
“Like, Mr Beast-style distribution, where people, I think rightly, focus on the content, and if that's not up to snuff, I think you won't succeed.”
237 / belief
“I got close to 1,000 applications across the different rounds of publicizing it that I did. And a lot of, I think, really cool people applied.”
238 / commitment
“Other news; I have a book launching today, it's called The Scaling Era. I hope one of the questions ends up being why you should buy this book.”
239 / preference
“I don't think about the hour that I'll spend with you. I think about the two weeks, because this is my life, right?”
240 / evaluation
“This is also why I'm skeptical of big grand schemes like nationalization or some public-private partnership or just generally shaking up the landscape too much, because I do think we're in one of the better..”
241 / commitment
“Mostly because- it's not even the long-term impact over years, though I think that is part of it and I do regret all the episodes I did without using Speech Marking Cards, because all the insights have just sort of faded away.”
242 / evaluation
“I mean, I feel like AI is one of the most multi-disciplinary fields that one can imagine, because there's no field, no domain of human knowledge that is not relevant to understanding what a future society of different kinds of beings will look like.”
243 / preference
“I don't know if you've seen me do this, but every time I encounter a young person who's like, "What should I do with my life?”
244 / prediction
“I feel like that job's still gonna be around. It's funny, because I studied computer science, and in retrospect- at the time, you could've become a software engineer or something.”
245 / belief
“Is intelligence that bottlenecked on prices going down? Because when I think about, at least my use cases as a consumer, intelligence is already so cheap.”
246 / belief
“Now, when I think about what's going to be possible in the next 250 years, I'm thinking like space travel, and space elevators, and immortality, and curing all diseases.”
247 / belief
“I think there's just, there are so many different applications that you have put out for using these models to make the different areas you talked about better.”
248 / belief
“Although after they won, Mao is famously a fan of luxury and has -- right? In a way that I think Stalin would sleep on his couch in his office.”
249 / evaluation
“Because in retrospect, obviously the means we don't endorse, but he was right about that understanding of what would happen with the Communists in power.”
250 / belief
“All right, we've come full circle. I think that's a great place to close things.”
251 / belief
“Morally, I agree, we don't want to like, they don't own our oil. The question is, it's not about are they are entitled to it.”
252 / belief
“One of the things I learned from your book is that the overwhelming fraction of deaths on the Japanese side during the war happened after it was known that they were going to lose.”
253 / uncertainty
“Here’s another thing that I want to clarify: If you were trying to understand Britain's conduct in World War I, why they initiated it and why they conducted it in the way they did, and you tried to understand it using cultural explanations — what some British guy wrote in the 17th century — I don't know how far you'd get.”
254 / belief
“I think you call it a "system of irresponsibility," that it was basically government by committee.”
255 / belief
“I interviewed you nine months ago, and I was asking you about AI then. I think your attitude was like, "Eh.”
256 / belief
“Wasn't Churchill, by the time he was 24, an international correspondent in Cuba and India? I think he was the highest-paid journalist in the world by the time he was 24.”
257 / belief
“If you read his aphorisms, I think he would have actually been pretty good on Twitter.”
258 / belief
“I think we've mentioned a couple of other bounds like this where there's no principled reason you might have anticipated ex ante why there would be such a bound that prevents something that just gets in our way, but it just so happens to be this way.”
259 / belief
“There's something to that sort of finality which makes existential risk salient in the first place. And if you agree with that intuition, then I think you should be inclined to think that there is something significant about the fact that in some base reality, like genuinely the story carries forward.”
260 / uncertainty
“I'm not sure if you're suggesting in the physical universe or in some hypothetical universe where the vacuum could be different, as in, in reality there are other pockets with different vacuums, or that hypothetically they could exist, or that our universe counterfactually could have been one of these? I don't know.”
261 / belief
“I think earlier you said, "I wouldn't be that crazy." But also, "It's not as easy as a Dyson sphere.”
262 / evaluation
“It's a little bit confusing because in one context, we're laying out very practical—I don't know if you can call black hole batteries practical—but very tangible limitations on the what future, like very distant future descendants, could do with all the matter in the galaxy and so forth.”
263 / uncertainty
“I don’t know. When I look at the ways in which my smart friends are smart, it just feels more like a general horsepower kind of thing.”
264 / uncertainty
“Borges has a short poem called "Borges and I" where he talks about how he doesn’t identify with the version of himself that is actually doing the writing and publishing all of this great work. I don’t know if you identify with that at all.”
265 / preference
“One of my favorite blog posts of yours is “Evolution as Backstop for RL,” where you talk about evolution as basically a mechanism to learn a better learning process.”
266 / evaluation
“If you could hire these people, it would probably be worth a lot to you because you're building a fab that's worth tens of billions of dollars.”
267 / uncertainty
“Another is NVIDIA. I don’t know how this works. Presumably, they have some sort of know-how.”
268 / evaluation
“Let's just give the number to like, “Okay, it’s 2025 and Elon's cluster is going to be the biggest…” It doesn’t matter who it is.”
269 / uncertainty
“How are you doing research and making a video twice a week? I don't know. I do these, I'm just fucking talking.”
270 / recommendation
“The thing I find wild when I'm reading The Prize is just how much economic development is ultimately contingent on the laws of physics.”
271 / uncertainty
“Millions of barrels of crude are being pumped out every year. I don't know if there's been any deployment like that since.”
272 / belief
“I've found that there are a lot of books which are nominally about one subject, but the author just feels a need to say, "If you really want to understand my topic, you have to understand basically everything else in the world." I think of a couple of biographies especially.”
273 / uncertainty
“I imagine since you wrote The Prize, world leaders are inviting you to meet them and give advice. I don't know how many stories you can tell from these conversations.”
274 / belief
“I think Caro said, "I'm going to write this over the summer and then we'll use the book deal to go on vacation afterwards.”
275 / belief
“Speaking of solar deployment, I think solar deployment is on an annualized $500 billion budget.”
276 / evaluation
“With crude oil in the beginning you're producing a certain amount, but you had a glut because you're only using it for lighting.”
277 / prediction
“Before the car was invented, when Edison invented the light bulb, people were saying Standard Oil would go bankrupt because the light bulb was invented.”
278 / prediction
“I don’t know if “instigated” is the right word, but the Pacific War was instigated because the Japanese needed more oil because of the war in Manchuria.”
279 / uncertainty
“I don't know if you're familiar with Nat Friedman's Vesuvius Challenge. I don't know if you saw that when it was going around.”
280 / uncertainty
“We figured out the exact genetic combination that explains all your research. Is the reaction usually… I don't know how much of this you can say.”
281 / uncertainty
“I don't know if species is the right word, but there were two different kinds of Denisovans and also the hobbits in Asia.”
282 / recommendation
“David, thank you so much for coming on the podcast. I highly, highly recommend your book, Who We Are and How We Got Here.”
283 / evaluation
“One thing I didn't realize until I read your book is how small the population that expanded out into Eurasia was, and how small even generally the human population was 50,000 to 100,000 years ago.”
284 / commitment
“We're doing that right now because of new technology that's being used by labs like yours.”
285 / evaluation
“The theory he talks about in the book is that potentially the reason the hunter-gatherers, the “barbarians,” couldn't fight back against these early nation-states was because they were getting killed off by the diseases.”
286 / prediction
“We're going to go explore space and that's where we expect most of the things that will happen.”
287 / belief
“I think what some people mean is that our intellectual descendants should control the light cone, even if the other counterfactual doesn't involve a bunch of torture.”
288 / belief
“Today I'm chatting with Joe Carlsmith. He's a philosopher and, in my opinion, a capital-G great philosopher.”
289 / belief
“There’s then a fifth version, which I think about less because it's just such an own goal if you do this.”
290 / uncertainty
“" An adult in prison has that ability in a way that I don't know if these models necessarily have.”
291 / evaluation
“With these models, at least so far, it doesn't seem to matter. They just get, "Hey, don't help people make bombs" or whatever, even if you ask in a different way how to make a bomb.”
292 / belief
“We're grinding through the values we care about because of increased competition.”
293 / belief
“What are the basic laws of physics? I think once we get that, we're done." It’s like, "Oh you'll figure out what's the right kind of hedonium.”
294 / uncertainty
“” Going to college or meeting new people or reading a new book, I'm like, “I don't know.”
295 / uncertainty
“We're starting off with something that has this intricate representation of human values and it doesn't seem that hard to sort of lock it into a persona that we are comfortable with. I don't know what changes.”
296 / belief
“Pretty soon we're talking about our relationship to superhuman intelligences, if we think such a thing is possible.”
297 / belief
“Through that process, they've been bullying you, training you to be a Nazi. I think in that scenario, I might end up a Nazi.”
298 / uncertainty
“I don't know if moral realism is the right word, but you mentioned the thing. There's something that makes hearts converge to the thing we are or the thing we would be upon reflection.”
299 / prediction
“I expect the US government to protect me, not because of its “motives,” but just because of the system of incentives and institutions and norms that has been set up.”
300 / evaluation
“I agree with the sentiment of obviously approaching this situation with caution, but I do want to point out the ways in which the analyses we've been using have been maximally adversarial.”
301 / evaluation
“They're almost like random number generators. They're not especially calibrated, but once in a while they'll be like, “Oh, this one weird philosopher I care about, or this one historical event I'm obsessed with has an interesting perspective on this.”
302 / recommendation
“I don’t know practically if it works out that well. But that experience made me think that I should try to expand my horizons in an undirected way because there’s lots of different things you have to understand about the world to understand any one thing.”
303 / evaluation
“To the extent that the reason we're worried about motivations in the first place, it’s because we think a balance of power which includes at least one thing with human-descended motivations is difficult.”
304 / evaluation
“I'm curious where that's coming from because conventionally I think the thing matters because it's conscious and its conscious experience as a result of that pursuit matters.”
305 / evaluation
“The native infrastructure that we had — that was specifically earmarked for dealing with public health emergencies — was extremely incompetent to the extent that Discord servers vastly outperformed them.”
306 / belief
“I agree that it shouldn't be up to tech to solve this huge society-wide problem.”
307 / belief
“We realized that with LLMs, it's going to be a bad deal with regards to privacy.”
308 / uncertainty
“Honestly, I don't know where to begin with some of these things. I want to understand a bunch of that.”
309 / uncertainty
“” I'm thinking to myself, how is this not as trivial a problem as, “hey XYZ, if you give me money that you can find between your couch cushions, we will save thousands of lives and get the world economy back on track.”
310 / belief
“How many of them are not 11, 12, or 13 years old? I agree this is not rocket science.”
311 / belief
“I agree they're not AGI. I'm just trying to figure out if we’re on the path to AGI.”
312 / belief
“I agree we're not there yet, but I'm confused about why we're not on the spectrum.”
313 / belief
“I think there was also expressing the JSON in a way that is more amenable to the tokenizer.”
314 / belief
“I think I agree with that. I might phrase it in this way. The people who are smarter have, in ML language, better initializations.”
315 / evaluation
“I agree that smart humans will do very well on this test, but the average human will probably be mediocre.”
316 / belief
“In this world, I think private companies have their capital and can raise capital.”
317 / belief
“I agree that nuclear energy is a thing that happened later on and is dual-use. But it’s something that happened literally a decade after nuclear weapons were developed.”
318 / uncertainty
“Maybe you have a point. We don’t know. You have arguments for why that’s a more likely world, but maybe that’s not the world we live in.”
319 / belief
“Unless you’re right about what the intelligence explosion looks like, don’t move yet. But in that world where it really does seem like Alec Radford can be automated, and that's the only bottleneck to getting to ASI… Okay I think we can leave it at that.”
320 / observation
“On that point in particular, many people who have longer timelines have come on the podcast and made the point that the way to train this long horizon RL, it's not… Earlier we were talking about how they can think for five minutes, but not for longer.”
321 / belief
“Before we go further on the AI stuff, let’s back up. We began the conversation, and I think people will be confused.”
322 / belief
“I agree. But fundamentally, it was a private sector-led effort. That was the only part of the COVID response that worked.”
323 / evaluation
“Now we're in a place where they are excited about AGI and they're like, "fuck, we want to have GPT-5 while you're going to be off building superintelligence. This Atoms for Peace thing doesn't work for us.”
324 / belief
“I agree, but if the coefficient, of how fast they diminish as you grow the input, is high enough, then in the abstract the fact that inputs matter isn’t that relevant.”
325 / observation
“I was told by people advancing this idea — because they know I’m a libertarian-type person and the way they approached me was like this — that the way to think about it was that it's fundamentally a way to protect market-based development of AGI.”
326 / belief
“I mean I think about the amount of people who, when they have the opportunity to talk to the person, will just bring up the thing.”
327 / belief
“I agree that over time you would get there. I'm not denying that ASI is possible.”
328 / belief
“I'm not sure I agree with this. There are many examples in history where small groups of people, Bell Labs or Skunk Works, have made significant progress.”
329 / uncertainty
“Looking internationally, I don't know if Xi Jinping sees the GPT-4 news and goes, "oh, my God, look at the MMLU score on that.”
330 / belief
“Now that I think about it, that’s weird given that this is an obvious thing in retrospect.”
331 / preference
“Potentially, if the takeoff is slower than anticipated, I prefer the private companies in that world.”
332 / evaluation
“Correct me if this is wrong. It seems like you’re implying that right now we have models that are on a per token basis pretty smart.”
333 / belief
“I believe the actual edge cases were explicitly stated rather than the kinds of things where are obvious.”
334 / belief
“Stepping back from 3.5, I think I heard you say somewhere that you were super impressed with GPT-2.”
335 / recommendation
“I want to go back to the point you made earlier about how this process could be more sample efficient because it could generalize from its pre-training experiences of how to get unstuck in different scenarios.”
336 / preference
“On the other hand, I think I heard you make the point that a lot of our preferences and values are very subtle, so they might be best represented through pairwise preferences.”
337 / prediction
“Because there doesn't seem to be a model since GPT-4 that seems to be significantly better, there's a hypothesis that we might be hitting some sort of plateau.”
338 / evaluation
“A bunch of them were about the classics. Clearly that was important in some way.”
339 / belief
“If it's like talking on Slack with a biology researcher… I think models are very far from this.”
340 / belief
“Regarding other open source dangers, I think you have genuine legitimate points about the balance of power stuff and potentially the harms you can get rid of because we have better alignment techniques or something.”
341 / preference
“There's a case in which you don't want to open source the architecture because China can use it to catch up to America's AIs and there is an intelligence explosion and they win that.”
342 / uncertainty
“Although it's doing that by… I don't know. ChatGPT is probably modeling me because that's what RLHF induces it to do.”
343 / belief
“We should talk about how you guys got hired. Because I think that's a really interesting story.”
344 / belief
“I think a bunch of your papers have said that there's more features than there are neurons.”
345 / uncertainty
“I don't know if permanent is the right word, but they are the model itself whereas activations are the artifacts of any single call.”
346 / uncertainty
“I guess if you think of something like the laws of physics, it's not that the feature for wetness is turned on, but it's only turned on this much and then the feature for… I guess maybe it's true because the mass is like a gradient and… I don't know.”
347 / belief
“I'll give you a specific example. I think one of your updates put it as “persona lock-in.”
348 / belief
“There's this deep sense of fulfillment that we think we're supposed to get from things like community, or sugar, or whatever we wanted on the African savannah.”
349 / belief
“I want to talk more about the feature splitting because I think that's an interesting thing that has been underexplored.”
350 / evaluation
“In fact, it's good for the world that that's not often how it happens. It is important to look at, “were they able to write an interesting technical blog post about their research or are they making interesting contributions.”
351 / belief
“Basically every single high-profile guest I've done so far, I think maybe with one or two exceptions, I've sat down for a week and I've just come up with a list of sample questions.”
352 / uncertainty
“There's some process by which to interpret the early data. I don't know. I could put a Google Doc in front of you and I'm pretty sure you could just keep typing for a while on different ideas you have.”
353 / uncertainty
“Is that the same kind of thing that's happening to ChatGPT when it gets RL-ed? I don't know.”
354 / uncertainty
“There was an interesting paper that you can use diffusion to come up with model weights. I don't know how legit that was or whatever, but something like that.”
355 / belief
“I think you were the one who mentioned that you can think of chain-of-thought as adaptive compute.”
356 / prediction
“Maybe it thinks in alien concepts and you can’t really monitor the million-line pull request because you can’t really understand the whole thing and you can’t give labels.”
357 / prediction
“One is that as these models get smarter, they are going to be able to operate in domains where we just can’t generate enough human labels, just because we’re not smart enough.”
358 / uncertainty
“There’s a perception that maybe other labs are more compute-efficient than DeepMind has been with Gemini. I don’t know what you make of that perception.”
359 / belief
“I don't quite know how to synthesize it yet, but as I think about advice for people in their 20s, I'm not going to normatively pretend to know or presume in which direction one should go in life.”
360 / belief
“I think you're being too humble. Staying on Fast Grants, now we have the retrospective of how effective the fast grants recipients were, compared to the other grants that were given out by, let's say, the NIH or NSF.”
361 / belief
“Patrick, I think that's a great place to leave it. Thank you so much for coming on the podcast.”
362 / prediction
“By the way, it's not the Dwarkesh podcast, it's Lunar Society Podcast LLC registered on Stripe Atlas. Any merchandise I sell in the future, Stripe will take care of that.”
363 / belief
“I think you just answered this question but still: It's not exactly like biology research is, it's something that society has neglected.”
364 / belief
“I think there's an interesting thread here in how it relates to Stripe climate, in that you're subsidizing learning curves that East Asian countries did for their own internal companies.”
365 / evaluation
“The specific case for Stripe working with them is: typically they're coming to us not because they want to take the thing that they're already doing and go through all the work of transposing to Stripe, but because either they want to do a new thing, that they're not doing today — so it is associated with some new business line or innovation or invention.”
366 / observation
“” Now, it’s a fascinating idea that investment is irrational, or most investment throughout history has been irrational. But when we think today about the fact that active investing exists for winners’ curse like reasons, VCs probably make, on average, less returns than the market, there’s a whole bunch of different examples you can go through, right?”
367 / uncertainty
“I don’t know. We’re in Washington. I’m sure you talk to all the people who matter quite a bit.”
368 / uncertainty
“Given that, I don’t know, some of these risks pay off that these intellectuals take, some of them don’t pay off.”
369 / uncertainty
“I want to go back to the risk aversion thing again, because I don’t know how to think about this.”
370 / belief
“I wonder if you’re doing enough of that when it comes to AI, where I think you have really interesting thoughts about GPD, five-level stuff, but somebody with your sort of polymathic understanding of different fields, if you just extrapolate out these trends, it seems like you might have a lot of interesting thoughts about what might be possible with something much further down the line.”
371 / commitment
“Another quote from Keynes, I guess I won’t read the whole quote in full, but basically says, over time, as investments, markets get more mature, more and more of equities are held basically by passive investors, people who don’t have a direct hand in the involvement of the enterprise, and the share of the market that’s passive investment now is much bigger.”
372 / belief
“Relatedly, I think, a couple of years ago, Paul Schlemming had an interesting paper that if you look from 1311 to now, interest rates have been declining.”
373 / belief
“I guess you have millions of views. Whoever made that would rise, I think. Stuart Armstrong.”
374 / belief
“When you say there’ll be uncertainties, I think you made this argument when you were responding to Alex Epstein on fossil future, where you said uncertainties also extend out into the domain where there’s a bad outcome or much bigger outcome than you’re anticipating.”
375 / belief
“For if we think of the alignment problem, it’s similar to how we react to our previous generations.”
376 / belief
“Sure. So before we get into his actual views, I think his career is a tremendous white pill in the sense that he writes The Road to Serfdom in 1944 when Nazi Germany and Soviet Union are both prominent players.”
377 / belief
“You talk in the book about how Mill is very concerned about the quality and the character development of the population. But when we think about the fact that somebody like him was elected to the parliament at the time, the greatest thinker who’s alive is elected to government, and it’s hard to imagine that could be true in today’s world.”
378 / uncertainty
“I guess he could have talked about it if he wanted to, but I don’t know if he was.”
379 / evaluation
“Yeah. So, related to that, I think in the meaning of competition, he makes the point that the most interesting part of markets is when they go from one equilibrium to another, because that’s where they’re trying to figure out what to produce and how to produce it better and so on, and not the equilibriums themselves.”
380 / preference
“I think 40,000 words is perfect because it’ll actually fit in context. So when you do the GPT-4.”
381 / evaluation
“This shows that this was Mao's doing. This is also an interesting example where, whether it's Stalin in Russia or Mao in China, when the tyrant dies, the system automatically improves because nobody else is as crazy as that guy.”
382 / recommendation
“The global impact of 'Wild Swans' has been tremendous. A former guest of mine, Sarah Payne, recommended it to me, and I read it.”
383 / evaluation
“Yeah, but I think he might have been right. And obviously, the point is that he would have been right to say that.”
384 / evaluation
“Because communism is a science, it has to work. And if it doesn't work, there must be internal capitalist saboteurs who must be condemned, brought out and killed.”
385 / prediction
“As it is today, although there’s lots of saber rattling by Lavrov and Putin, it doesn’t really look as though, I mean, yes, there might be a catastrophic disaster at the Zaporizhzhia nuclear plant, but it’s very unlikely for Putin actually to use tactical nuclear missiles in Ukraine, not least, of course, because the Chinese don’t want him to.”
386 / belief
“Your biography is the part of the canon. So in the person of Napoleon, I think startup founders see the best aspects of themselves resemblance.”
387 / recommendation
“You have this really interesting book, I think probably my favorite book about World War II, The Storm of War, which I highly recommend.”
388 / uncertainty
“Yeah, but it seems like I don’t know how you train a John von Neumann, because then he also assisted the US in thinking about Cold War game theory and things like that.”
389 / uncertainty
“Another analogy here is it set up all these things that nobody understands, these systems of alliances and relationships in Europe. And you can imagine, like an AI advisor, and you’re not sure what’s going on, but it’s making, I don’t know, maybe it’s like a hedge fund manager that’s AI and it’s like making a lot of money.”
390 / uncertainty
“Whether it’s political modeling, whether it’s the use of new technologies, or I don’t know, testing things out with social media.”
391 / evaluation
“Correct me if this is wrong, but it sounds like you basically give it the opportunity to do a coup or make a bioweapon or whatever in testing in a situation where it thinks it’s the real world and you’re like, it didn’t do any of that.”
392 / belief
“I’m just like I trust Paul enough that I think there’s probably something here if I try to understand this enough.”
393 / belief
“I'm just saying, okay, I personally, it's hard for me to imagine in 100 years that these things are still our slaves. And if they are, I think that's not the best world.”
394 / uncertainty
“Might be like Rlhf where we don’t know if it generalizes, but so far it makes your chat GPT thing better and you can also use it to make sure that chat GPT doesn’t tell you how to make a bioweapon.”
395 / uncertainty
“I don’t know, like computer security and code checking. If you can actually say this is how safe we think a code is.”
396 / belief
“I'm tempted to ask you what the system would look like where you'd think, yeah, I'm happy with what I think.”
397 / evaluation
“It’s not in control of factories and robot armies or whatever. So in that case, even in training it will have those activations for being fucked up on because in the back of its mind it’s thinking I will take over once I have the opportunity.”
398 / commitment
“Speaking of the early years, it's really interesting that in 2011, you had a blog post where you said — “I’ve decided to once again leave my prediction for when human level AGI will arrive unchanged.”
399 / prediction
“What will it take to align human level and superhuman AIs? It's interesting because the sorts of reinforcement learning and self-play kinds of setups that are popular now, like Constitution AI or RLHF, DeepMind obviously has expertise in it for decades longer.”
400 / belief
“I think there's a bunch of possible explanations. It can't just be youth because youth lasts 10 years not one year so it must have something to do with..”
401 / observation
“Tell me why I should be less amazed by it or maybe put it in a different context but the reason I would be very impressed is… With chess, obviously this is not all the chess programs are doing, but there's a level of research you can do to narrow down the possibilities. And more importantly, in the math example, it seems that with some of the examples you've listed on your channel, the ability to solve the problem is so dependent on coming up with the right abstraction to think about it, coming up with ways of thinking about it that are not evident in the problem itself or in any other problem in any other test, that seems different from just a chess game where you don't have to think about what is the largest structure of this chess game in the same way as you do with the IMO problem.”
402 / belief
“I think that's a great note to leave it on Grant. Thanks so much for coming on the podcast and genuinely, you're one of the people I really, really admire but what you've done for the landscape of Math education is really remarkable.”
403 / belief
“Then should we think of educators more as motivational speakers? As in the actual job of getting the content in your head is maybe for the textbooks or for Youtube but why we have college classes or high school classes is that we have somebody who approximates Tony Robbins to get you to do the thing.”
404 / belief
“Being around them, I think I have a sense of what it means to understand a technical field well.”
405 / belief
“In retrospect, we think of them as part of the same great global conflict, whereas they were separated by eight years.”
406 / belief
“Something I learned from your book that I thought was really interesting, and also tragic because of the counterfactual, was one of the strategies you suggested.”
407 / belief
“I think until recently the narrative has been that the CCP is incredibly competent and very good at engineering good policies and economic growth in China.”
408 / recommendation
“And also, I've really enjoyed your book on Japan, The Japanese Empire. And you also have these other textbooks and collections of essays, which I highly recommend because of the thorough nature and the diversity of sources.”
409 / recommendation
“I guess this maybe implies that if you do want to learn about a subject, it might just be helpful to just do an Intro to X subject course or textbook, not necessarily because it is instrumentally valuable to whatever problem you're interested in but because it'll give you the context by which to proceed on, the actual learning.”
410 / belief
““What is the optimal amount of effort that should go into a personal website?” I think he might have noticed the amount of CSS that exists on andymatuschak.”
411 / commitment
“Sometimes I'll listen back to a conversation and I won't even remember the content in the conversation.”
412 / belief
“For example, you had this really insightful post based on your experience in industry at Apple about the possibilities of Vision Pro and in what ways it's living up to and not. I think that would have just gone huge.”
413 / belief
“I think you're using the wrong tool given the wealth distribution of your audience.”
414 / uncertainty
“Presumably you didn't have some sort of practice but since you were encountering these things day to day, that natural frequency and way in which problems came up, did you have a worse understanding of those problems then compared to now, knowing what you do and having the practices you do, you're able to comprehend now? I don't know if that question made sense.”
415 / evaluation
“I do wonder if there's an element of, if you get to a certain level of quality, trying to market your stuff, not only doesn't help, but probably hurts you.”
416 / uncertainty
“If you are trying to self learn and there is a resource that is a close approximation of the syllabus you want. Should you just think “Hey, I don't know why I need this chapter.”
417 / belief
“If we nuked Afghanistan or Vietnam we would have technically won the war if that was the only goal, right? Oh, this is an interesting point that I think you made.”
418 / evaluation
“If the current scale up doesn't work, all we're left with is just like the economy growing 2% a year, we have 2% a year more resources to spend on AI and at that scale you're talking about decades before just through sheer brute force you can train the 10 trillion dollar model or something.”
419 / belief
“I think I saw an estimate that GPT-4 cost like 50 million dollars or around that range to train.”
420 / belief
“I think some people might be skeptical that existing robots given their current hardware will have the dexterity and the maneuverability to do a lot of physical labor that an AI might want to do.”
421 / recommendation
“The first third is about the scientific roots of the physics and it's also the best book I've read about the history of science in the early 20th century and the organization of it.”
422 / evaluation
“Was there an opportunity after the end of World War II, before the Soviets developed the bomb, for the US to do something where either it somehow enforced a monopoly on having the bomb, or if that wasn't possible, make some sort of credible gesture that, we're eliminating this knowledge, you guys don't work on this, we're all just gonna step back from this.”
423 / belief
“I think Fermi said you could never refine uranium and get 235 but then some of these other scientists saw it coming.”
424 / uncertainty
“I don't know how many people were working on it when he became president, but hundreds of thousands of people are working on it.”
425 / recommendation
“The people who are working on AI right now are huge fans of yours. They're the ones who initially recommended the book to me because the way they see the progress in the field reminded them of this book.”
426 / evaluation
“I had a former guest, Richard Hanania, who has a book about foreign policy where he points out that our model of thinking about why countries do the things they do, especially in foreign affairs, is wrong because we think of them as individual rational actors, when in fact it's these competing factions within the government.”
427 / evaluation
“You mentioned that a big reason why many of the scientists wanted to work on the bomb, especially the Jewish emigres, was because they're worried about Hitler getting it first.”
428 / uncertainty
“I don’t know. It wants to keep us as a zoo the same way we keep other animals in a zoo.”
429 / uncertainty
“I don’t know enough about how the RNN would be integrated into the thing, but that sounds plausible.”
430 / belief
“I think a better analogy is if you have a child and you tell him — Hey, be this way.”
431 / belief
“I think that I was not convinced from the arguments that we could not have a system of sort of checks on this the same way you have checks on smart humans that it would try to deceive us to achieve its aims.”
432 / belief
“First of all, one optimistic lesson to take from there is that we actually did learn from GPT-3, not everything, but we learned many things about what the potential failure modes could be 3.”
433 / uncertainty
“I don’t know if I see the computer science of that, but I think I probably understand.”
434 / belief
“I think you would say that it just hides its intentions until it’s ready to do the thing that kills everybody.”
435 / belief
“I think people are actually going to start dedicating that level of effort they went into training GPT-4 into problems like this.”
436 / belief
“I think what some people might not know is the millions and millions and millions of words of science fiction and fan fiction that you’ve written.”
437 / commitment
“I think a better analogy is just put him in a high position in the Manhattan Project and say we will take your opinions very seriously and in fact, we even give you a lot of authority over this project.”
438 / belief
“Eliezer Yudkowsky 3:19:29 I think I want to register for the record that the term breeding humans would cause me to look askance at any aliens who would propose that as a policy action on their part.”
439 / uncertainty
“Possibly but again, this is something that seems like, I don’t know the probability on it but I would put it at least 10%.”
440 / uncertainty
“I still think even most smart humans in that situation might disagree, but we don’t know what would happen in that situation.”
441 / belief
“I think 13 or 14 years ago you wrote an essay called Rationality is Systematized Winning.”
442 / uncertainty
“I’m not even making a moral point. I’m just saying I don’t know what’s going to happen in the future.”
443 / uncertainty
“The way you describe it, it seemed kind of compelling. I don’t know why that doesn’t even rise to 1%.”
444 / uncertainty
“From reading your writing from earlier, it seemed like a big part of your argument was like, look — I don’t know how many total mutations it was to get from chimps to humans, but it wasn’t that many mutations.”
445 / belief
“I think the credit you would get for that, rightly, is as a good Agnostic forecaster, as somebody who is calm and measured. But it seems like to be able to make really strong claims about the future, about something that is so out of prior distributions as like the death of humanity, you don’t only have to show yourself as a good Agnostic forecaster, you have to show that your ability to forecast because of a particular theory is much greater.”
446 / prediction
“I expect them to be better than humans at science than they are at power seeking, because we had greater selection pressures for power seeking in our ancestral environment than we did for science.”
447 / uncertainty
“I don’t know if you saw his recent blog post, but here’s a quote from it: “If you really accept the practical version of the Orthogonality Thesis, then it seems to me that you can’t regard education, knowledge, and enlightenment as instruments for moral betterment.”
448 / disagreement
“We disagree about what will happen in the future once that offer is made, but lacking that information, I feel like our prior should just be the set of what we actually see in the world today.”
449 / observation
“Something that makes you think the problem is twice as hard, you go from like 99% to like 99.”
450 / evaluation
“Give me an over-under. Ilya Sutskever The problem is that my error bars are in log scale.”
451 / belief
“Before I delve deeper into AI, I do want to talk about GitHub. I think we should start with – You are at Microsoft.”
452 / uncertainty
“For example, with California YIMBY, I don't know the exact amount you seeded it with.”
453 / uncertainty
“A lot of them might have, like, problems, to put it in that kind of language, but I don't know how many of them would make you suspect that there's, like, mental health issues or there's addiction issues that for somebody who's in charge of a multibillion dollar empire, I don't know.”
454 / uncertainty
“I was like ten in 2011 so I don’t know if I would’ve personally. I would’ve liked to think I would’ve caught on if I was older but maybe not.”
455 / uncertainty
“I don't know how to look into the far future situation, don't understand the far future situation, and don't see a path to doing good on that front I feel good about.”
456 / uncertainty
“I don't know if this is a hypothetical where that would happen, but let's just say that it is.”
457 / belief
“Maybe I'm a bit more pessimistic about that because I think the people who are working on individual rights frameworks weren’t anticipating an industrial revolution.”
458 / belief
“I think you have a very interesting series of blog posts about future proof ethics.”
459 / prediction
“I think my general take on this most important century stuff, and the reason it's so important is because it's easy to imagine a world that is really awesome and is free from scarcity and we see more of the progress we've seen over the last 200 years and we end up in a really great place.”
460 / recommendation
“Yeah, I totally agree. I don't want to repeat myself, because I talked about this on my Byrne episode but we were talking about Robert Caro's books and one interesting thing is this guy was nominated for a Pulitzer Prize before he wrote The Power Broker. He was a top tier investigative journalist. Can you imagine crunching the numbers as a top tier investigative journalist at the peak of your career and you're like, “You know what would be a good use of my time? I'm going to spend the next seven years, in almost poverty, writing about this one guy who had a lot of influence in New York. I'm going to talk to any person who had conceivably even been in the same room as him or had been indirectly affected by his policies in any way. And I'm gonna do that obsessively for the next seven years.” There's no way the number crunching would get you there but it's probably been one of the most influential books in terms of how urban governance is done. Presidents have praised and read the book and said it changed how they think about politics. It is the kind of thing where you wouldn't have gone to that conclusion just from thinking about it beforehand and this is the most effective thing I could do.”
461 / belief
“You mentioned that the aristocratic elites feel that they have the responsibility to give back more so than the meritocratic elites. But I believe that in the U.”
462 / uncertainty
“First, how can somebody be long AI but hedge for the possibility that Taiwan will be invaded? So, I don't know if I should put money into TSMC but I know that GPUs are going to be the next big thing or are going to be very important in the future.”
463 / preference
“co and the way I would describe Byrne is — every time I have a question about a concept or an event in finance, I google the name of that event or concept into Google and put in ‘Byrne Hobart’ at the end of that search query and 9 times out of 10, it's the best thing I've read about that topic.”
464 / recommendation
“There's many places where if you understand the economics of an issue he's talking about there's a lot to be left to Caro’s explanation but the actual breakdown of the personalities is just so fascinating and worth reading Caro for.”
465 / belief
“We’re actually going to have sensible procurement policies that bring in things at a reasonable cost, and I think we need to balance a little bit back towards Robert Moses in order to have slightly more empowered builders who actually are able to deliver American cities the infrastructure they need at an affordable cost.”
466 / evaluation
“I push back against the universal basic income advocates who I think are basically engaging in a materialist fallacy of thinking that a human being’s life is shaped by their take home pay or their unearned pay.”
467 / evaluation
“So the US has historically been better at being pro-business than, let’s say, the Northern European social democracies, but the Northern European social democracies are great on the education front. So places like Sweden and the Netherlands, and Germany are also very successful places because they have enough education to counter the fact that they may not necessarily be as pro-business as the US is.”
468 / recommendation
“Your most recent book is Survival of the City. And before that Triumph of the City, both of which I highly recommend to readers.”
469 / commitment
“Lehman Center for American History and the Jacques Barzun Professor Emeritus of History at Columbia University, where he has also shared the Department of History. We will be discussing Robert Moses.”
470 / belief
“Expanding the Long Island Expressway had an estimated economic value of $719 million”, which I think was Moses.”
471 / uncertainty
“If there's one person who's designing all the bridges, all the highways, all the parks, is something more possible that can be possible if like multiple different branches and people have their own unique visions? I don't know if that question makes sense.”
472 / evaluation
“I guess if we take this kind of view and just care about progeny more, there's a part in the Power Broker where they're talking about the Cross Bronx Expressway through East Tremont and Moses is getting opposition from an elected official.”
473 / evaluation
“One of the main criticisms that Caro makes is that Moses refused to add mass transit to his highways, which would have helped deal with the traffic problem and the car problem and all these other problems at a time when getting the right of way and doing the construction would have been much cheaper. He just refused to do that because of his dislike for mass transit.”
474 / evaluation
“There's a very arresting anecdote in the Power Broker where I think he's 71 and his daughter gets cancer and for the first time, he had to accept a salary for working on the World's Fair because he didn't have enough.”
475 / recommendation
“Today, I have the pleasure of speaking with Brian Potter, who is an engineer and the author of the excellent Construction Physics blog, where he writes about how the construction industry works and why it has been slow to industrialize and innovate. It's one of my favorite blogs on the internet, I highly, highly recommend that people check it out.”
476 / uncertainty
“I don't know if you're familiar with the longtermist movement, maybe you’ve come across this before, but one thing they've proposed is not like a doctrine or anything, but on the periphery, some idea I saw was that just as we have environmental review we should have a posterity review so that you're analyzing the impacts of your actions on generations way down the line.”
477 / prediction
“There's a famous law in software that says that a project will take longer than you expect even after you recount for the fact that it will take longer than you expect.”
478 / uncertainty
“I don't know if we discussed this, but an interesting part of the book is where he talks about transistor design.”
479 / uncertainty
“I have a friend who was with you at the Oxford Refugees Conference, Connor Tabarrok. I don't know if you remember him.”
480 / uncertainty
“I don't know if you saw this, by the way, but about a year or two ago, Microsoft announced that they were building this new office for developers in India and they were looking at this very interesting architectural details and craftsmanship that made it look like you know for everything from the furniture to the floor layout to the arches of the entrances.”
481 / belief
“I think there are a lot of examples where if you don't have the context on why they were built a certain way, you wouldn't understand what was going on.”
482 / belief
“I think a co-sign solution to this kind of thing would be optimal where if the view is worth more to you than the apartment is worth to somebody else, then you can just pay them to not build there.”
483 / prediction
“There's been a lot of talk about a potential real estate bubble in China because they're building housing in places where people don't really need it.”
484 / belief
“Now, it's not like we think society mistreats billionaires. They're pretty fine, but we think their status should be even higher.”
485 / belief
“I think Tyler cited some of this research in his new book on talent that being too agreeable or being too aggressive harms women more than it harms men.”
486 / uncertainty
“I don't remember. I don't know if you asked him directly, but that was his claim.”
487 / uncertainty
“I don’t know, but maybe yes. More generally, one of the common arguments that libertarians make about India and its elites is, “Oh, all of India's elites go study in Oxford or something, and they learn about the regulations the West is adopting that make no sense for a country with $2,000 GDP per capita.”
488 / belief
“I think he said his reason was, “Oh, my mother doesn't want me to fight anymore.”
489 / evaluation
“All of these things combined make women's lives worse on average than men's lives. It's not because society mistreats them, but in some sense, there's still unfairness geared toward women.”
490 / evaluation
“You say in the book, that questions tend to degrade over time if you don't replace them.”
491 / evaluation
“I mean, I think of you as an optimist––at least by temperament. But this seems like one of the more pessimistic things I've heard overall, anywhere, because of the idea that not only will human civilization be decimated almost surely, but that they will never be able to recover.”
492 / belief
“Dwarkesh Patel Yeah, the pyramids there… I think I was reading your book at the time or already had read your book.”
493 / belief
“I think I got a chance to see the Teotihuacan apartments when I was there, but I wonder if we’re just looking at the buildings that survived.”
494 / uncertainty
“I don't know too much about it, but I hear that the Silk Road stuff they're doing is not especially economically wise.”
495 / belief
“I learned so much from the books and I learned so much from talking to you, so I really really enjoyed this.”
496 / belief
“By the way, I realized I haven't gotten to all the Wizard and Prophet questions, and there are a lot of them.”
497 / prediction
“I want to ask you again about contingency because there are so many other examples where things you thought would be universal actually don't turn out to be.”
498 / uncertainty
“” I don't know; my perception of the story was, “Okay, he's not intelligent enough to be a theoretical physicist.”
499 / uncertainty
“I wonder whether he was doing this in the 40’–– like when he was at that age, was he doing this? I don't know what the cultural conventions were at the time.”
500 / disagreement
“If it's true, as you say, in the book, that moral values are very contingent, then shouldn't that make us suspect that modern Western values aren't that good? They're mediocre, or worse, because ex ante, you would expect to end up with a median of all the values we could have had at this point.”