The Ledger, every show

“So in any case where we can be very precise about what a great result looks like, we'll be able to make that task automatic much more easily than tasks that are much more nuanced and have a lot of complexity.”

“I see a lot of people using it as a tool, more than as a companion. You know, people have this, you know, Swiss knife in their work life all of a sudden that can be super helpful, but that's really most of what I see.”

“We don't have all the answers of how it should be used. That's gonna come from people on the field.”

“In terms of agents, you know, we worry a lot about hallucinations in LLMs. The parallel in agents is impersonation.”

“I do think it's healthy that there are models that are getting built in different places around the world, not just in the US and China right now. I think this is healthy in terms of diversity of thoughts. I think it's healthy in terms of having a greater amou…”

“If you have too much talent and not enough compute, you're wasting your time, so usually like an equilibrium between those two pieces.”

“The days of like having data labelers who can say this is a cat and this is a dog or somewhat over like the easy test the AI can do. So we're getting in a space where we need more specialized tasks.”

“I think for me, the even bigger trend we're seeing is the moving from just labeling data to crafting environments to produce new, new tasks.”

“So in some domains, if you think like images, languages, like LLMs talking to each other at some point, you definitely get the degradation and that degradation is due to essentially like a loss of diversity of your data.”

“If I think of coding, we can generate synthetic code. You take normal code and we know how to inject diversity into the code. Like I can take a couple of repositories, mix and match, apply an LLM to transform it. And so there's a way to generate synthetic data…”

“But language is incredibly powerful. So if you think of prompt as being more language as a way to express ideas and communicate with a machine, that's a powerful paradigm. I mean, as humans, we, so much of our communication is based on language. I don't think …”

“We build AI systems that go into enterprise. None of our clients ask about, like, are you able to win the math Olympiad with this model? That's not what they care about. They care about bringing value to their business.”

“You go to the major international conferences, Nureps, ICML, and others, and often the best paper awards are actually won by researchers out of universities.”

“There's a lot of good ideas that you need to test out at small scale. And in a university, you have a lot more freedom to pick pretty risky ideas at a small scale, but still, you know, no one's asking you to justify your research in, in ways that, that often h…”

“He is incredibly deep into understanding the work. Like, he does not coast, you know. When he started getting into AI, just the depth of the question that he'd ask, he just gets really interested in the topic and goes super deep, and that then just informs eve…”

“We were in, in the frenzy of large language models, and I pulled the stats on, you know, most downloaded models of last month. We had a model like Roberta from 2019, small language model, was getting twenty million downloads a month.”

“We've talked a lot this year about safety, for example, about how to make sure that we have models that are performing well, but also are aligning with the values of peoples and the needs of people which I consider sort of a much more grounded problem that we …”

“The thing about general intelligence is you have to solve many different problems to have, you know, the ability to claim general intelligence, and fortunately, there are a lot of use cases across Meta, across our family of products, and so that's giving us wo…”

“One of the things that has changed in the last year or so is mostly on the startup scene. I would say, you know, three years ago we Didn't feel much competition with a startup scene. Now we do a lot more.”

“In some ways, that's still the hardest question in AI. How do we have different components working together in a very coordinated way?”

“In five years, we're gonna see really strong systems across a broad set of tasks. I have some strong conviction that, that we're on a path there. After that, you know, I don't want to bin any intelligence into narrow box, whether human or AI, but we will be am…”

“That pivot towards so much energy, literally people energy, as well as computation energy, and progress being devoted to generative model is what's completely changing conversations on this.”

“Whether you pick this path of building AI technology to solve these shorter term problems, or you take an approach that, that is more geared towards general AI. Right now, where we stand, the types of problems that we have to solve are very similar. This notio…”

“It's awfully limited, and, you know, prompts can mean a few different things, but the idea of, like, typing in a box, that to me is very limited, and we're gonna break out of that box already. We're seeing a lot of cases where voice is a lot more natural as an…”

“There's a lot of verticals, whether healthcare or scientific discovery that I think have increased Incredible promise where we're going to see real tangible progress within five years that are going to change completely the face of what we can do. So that's pr…”

“We have a research team that, that's dedicated to this. They do some work in robotics in particular because that's the best agents we have to consider physical embodiment, spatial constraints. It's not necessarily because Meta intends to commercialize robots. …”

“LAMA on its own doesn't make for the best, ah, the best assistant on, on glasses, because it doesn't have enough of an understanding of the physical world of images, ah, and so on.”