The Ledger, every show

“I do think at some point you get to LMs can, they can do Everything, every single thing a human can do for cheaper. Like, I don't see a reason why we don't eventually get there. That may take five, 1015 years.”

“I don't think so. I mean, I think there are certain things like memory and learning, like continuous learning that are not very easy with the current architectures. I think even those you can sort of fake and maybe are, we're going to be able to get them to wo…”

“I think the current paradigm is pretty good. And I think we're nowhere near the sort of like diminishing returns of continuing to push on it. And I bet. Yeah, I guess I would just bet that you can keep doing different innovations within the paradigm to get the…”

“Nothing seems fundamentally so hard that it couldn't be solved by the smartest people in the world working incredibly hard for the next five years.”

“And then there's some things like computer use that are still not quite there, but I think we'll almost definitely get there in the next year or two. And when you have that, I think we're gonna be able to automate a large portion of what people do.”

“One definition I kind of like is if you say that you have a remote worker, a human, any job that can be done by someone whose job can be done remotely that, that's AGI.”

“I think that's going to be more a function of when we can produce something that is as good as human intelligence, even if it takes a lot more compute, a lot more energy, a lot more training data. We could just put in all that energy and still get to software …”

“I think you're gonna get to much more than four to five percent GDP growth in that world.”

“CS majors graduating from college, there's just not as many jobs as there used to be, and LLMs are a little more substitutable for what they previously would have done, and I'm sure that's contributing to it.”

“Recommender systems, the system that ranks your Facebook or Instagram or Quora feed, those recommender systems are already superhuman at predicting what you're gonna be interested in, in reading.”

“And if you imagine that they're going to get there, and I think there's no reason why they wouldn't, it'll take a few years, but then it's like everyone in the world is going to be able to create any things that would have taken a team of a hundred professiona…”

“As these models continue to scale up, the quality is going to go higher and higher to the point where it actually will be as good as human quality in, in a lot of cases.”

“And I think hallucinations are gonna, the rate is gonna go down as the models get better, but it's never gonna get to the point where it's a hundred percent perfect.”

“So far they have held. My prediction would be there are some issues that need to be overcome, but there's just this incredible industry, so many talented people right now who are trying to Make this technology advance, and there's so much money behind it. The …”

“And so it's, you know, right now it's OpenAI, Google, maybe Anthropic. Maybe, maybe Meta can be there. Those who can get there, I think it's going to be good business. You'll be able to make a lot of money. You can have good profit margins. You'll have to work…”

“I think when you go six months behind the frontier, even definitely one year, it's brutal. There's just way too many people that are able to get the capital and the resources to train those models. And so it's going to be either fully open source or there will…”

“The hallucination problem, that's in some ways a good thing for startups because a lot of the existing products out there have zero tolerance for anything that's going to have a risk of producing something wrong.”

“I think with perplexity getting share from Google right now.”

“I think a lot of what's holding back the models these days is not Actually, intelligence. It's getting the right context into the model so that it can Be able to use its intelligence.”

“I think if you had an environment more like we had in, say, like the nineties, I think this would actually be more disruptive than the current hyper, hyper competitive world that we're in now.”

“I think network effects are playing much less of a role now than they did in the web two era also, and that, that makes it easier for competitors to get started. There's still a scale advantage because, you know, if you have more users, you can get more data. …”

“As you have, you know, as intelligence gets cheaper and cheaper and more and more powerful, the bottleneck, I think, is increasingly going to be on the data and what do you need to create that intelligence? And so that's going to cause this, that's going to ca…”

“We have relationships with some of the AI labs and we're gonna sort of play the role, Quora will play the role that it is meant to play in this ecosystem, which is a, as a source of human knowledge.”

“Having these skills to understand the sort of fundamentals of what's possible with algorithms and data structures, I think that actually really helps you in, in managing agents when you're using them. And I, I'm guessing that it will continue to be a valuable …”

“If you're a large model creator and you have You know, you have tens of employees that you can allocate to building a consumer product, and you have the culture to do that, then you can, you know, you can go direct to consumer and you can build a good product.…”

“And I think different startups will choose different paths here, but I think for a lot of them, the right path is going to be to just set up an API or plug into the PO API and use that to get to a lot of consumers very, very quickly.”

“Too much of the Quora product has been built up around this publication model that is sort of fundamentally premised on the idea that expert time is going to be scarce. And the AI, the LLM time is not scarce in the same way.”

“There's enough competition among the hyperscalers that the... As an application level company, you have choice and you have alternatives and the prices are coming down incredibly quickly. But there's also not so much competition that the hyperscalers and the, …”

“Like you couldn't build a good ad business until you got to 1,000,010 of millions of users. And now with subscriptions, you can just charge right away. I think especially thanks to things like Stripe that are making it easier. And so that, that, that's also ma…”

“The way we got to it was we, in early, we started experimenting with using GPT-III to generate answers. For Quora. And we compared them to the human answers and sort of realized that they weren't as good, but what was really unique was that you could instantly…”

“We ran some experiments using GPT-III to generate answers and compare them to the answers that, that humans had written on Quora. And a lot of the time, GPT-III could not write as good of an answer as what the best human answer was that, that, that had been wr…”

“A chat kind of experience, where you can write a question and then get an answer instantly from AI, Was more likely to be the best paradigm for interacting with AI as opposed to this kind of like publication paradigm that, that Quora had.”

“There's actually a lot of this kind of, like, consumer internet know-how that's important in getting a product to mass market. So this is things like building applications across iOS and Android and Windows and Mac, localization of the interface, A-B testing, …”

“I think what we're going to see over just the next year or two is going to be incredible. This will go from being sort of useful to some people right now to being something that's just critical to many different tasks that, that anyone is going to try to accom…”

“We're spending millions of dollars already on, on inference. It's mostly going to the large model providers right now, but we want to let as much of that as possible go off to these independent creators.”

“There's knowledge that people have in their heads that is not in, is not on the internet and is not in any book. And so no LLM is going to have that knowledge.”

“I expect that that is going to lead to some kind of product or some kind of user experience where the LLM is helping you sort through your sources and quoting exact experts or exact sources, as opposed to just synthesizing it all and giving you something where…”

“So I think there's going to be this kind of choice where you're either competing on scale by being on the frontier, or you're competing on some kind of, like, Feature differentiation, and in that case, you don't need a frontier model, and in some cases, you'll…”

“I think it's very hard to just kind of, like, think top down about where there's demand in the market. I think experimentation is really the way to go to generate ideas and to set up a, you know, a startup that's going to be able to build something really valu…”

“There's a data point that the people playing chess is up since computers got better at human than humans at chess.”