The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 20 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Dwarkesh: AGI requires further algorithmic progress, not just current model scaling
“I don't think we're just right around our corner from AGI and it's just a little additional dash of something. That's all it's going to take. I think, you know, people often ask if all AI progress stopped right now and all you could do is collect more data or …”
Patel: Meta treats Llama as a toy rather than approaching AGI correctly
“I think they're treating it as like a sort of like toy within the meta universe. And I don't think that's the correct way to think about AGI.”
AI scaling will not mysteriously halt halfway through the range of human intelligence
“It would just be bizarre to me that, like, you're halfway through the human range of intelligence, and now it stops getting better, so I do sympathize with Sam's statement in the sense of, like, why would it stop here, right? If it was gonna stop, why, it woul…”
Recursive AI self-improvement will require government intervention to pause development
“So I think in the world where you have really fast AI progress, and you are coming up to this point we're talking about where AIs can help improve themselves, then I think what you want to do is you might need a sort of government level actor to be like, all r…”
Dwarkesh: Slow enterprise AI adoption stems from model limits, not stodginess
“And so sometimes people say, well, the reason Fortune 500 isn't using LLMs all over the place is because they're too stodgy. They're not they're not like, they're not thinking creatively about how AI can be implemented. And actually, I don't think that's the c…”
Patel: Prompting alone cannot teach AI models complex capabilities
“I don't think prompting alone is that powerful a mechanism of teaching models, these capabilities.”
Patel: OpenAI's o3 is currently the smartest AI model on the market
“I do think O three is the smartest model on the market right now.”
Patel: xAI is slightly behind leading labs but has high compute per employee
“I think they're a serious competitor. I just don't know much about what they're going to do next. I think they're like slightly behind the other labs but they've got a lot of compute per employee.”
Patel: Effective Altruism's Reputation Remains in Tatters
“I do think the movement and the reputation of the movement is like still in tatters.”
Individual AI scientists are probably replaceable at large research labs
“Then I, you know, I think like the default perspective is listen, you've got thousands of scientists who are doing AI. Surely any one of them is replaceable. I think that's probably correct, but. I'm not in the field enough to know that.”
Claude 3 and Gemini are not significantly better than GPT-4
“So we've gotten Claude III, we've gotten Gemini. They're not significantly better, if at all, than GPT-IV, and certainly not the newer version of GPT-IV.”
Standard AI benchmarks like MMLU are becoming saturated and inadequate
“I mean, like, people will come out and say, here's what we got on MMLU and so on, but they're getting saturated, and they're not, often not that great to begin with, so I, I'm more eager to see what it feels like to talk to one of these things than learn what …”
Chatbot Arena fails to properly evaluate long-form conversational context
“And in fact, I think even chatbot arena has some deficiencies in terms of evaluation because from what I understand, you're doing these pairwise comparisons, but you're doing them you ask a question and two of them respond. And what I'm more curious about is w…”
Microsoft is repeating Google's mistake by splitting AI model training efforts
“Microsoft is basically reversing what Google has managed to do over the last few years. And in fact, making the same mistake that Google initially made, which was to have its training distributed or split up between two different corporations or institutions.”
LLMs match smart humans per token but lose coherence over time
“On a per token basis. They're actually really smart, potentially as smart as
Really smart humans. It's just that five minutes out, they lose their train of thought.”
Effective Altruism deserves credit for an early focus on AI and pandemics
“I definitely think they've been, like, right on a lot of things, right in the sense of, like, this is a big focus, and they've realized it before a lot of other people. Like, this AI stuff, right? The EAs have been talking about this stuff for decades, and, li…”
Effective Altruism was not a major factor in the OpenAI board drama
“I actually don't think EA was at, That big a deal of the board stuff. I think like from what I've heard, it was related to something separate.”
Children interacting with AI chatbots is preferable to using existing social media
“Potentially, but I think it'll honestly be better than what they're currently doing, which is YouTube and TikTok and Twitter, you know, Facebook and so forth. So I would prefer my kids are playing with chatbots than they're playing with what they currently hav…”
OpenAI likely leads frontier AI competitors in revenue by a wide margin
“It doesn't seem like there's a strong leader at the moment. I think in terms of revenue, probably open AI is leading by a lot.”
Anthropic's Claude has better post-training and persona than rival models
“Claude seems to have better post training, which is to say, which is the jargon for basically saying like, What kind of personality does it have and how does it break down your question and how does it act? How does it act as a persona of a chat bot? And so al…”