Foundation Model Labs
topic on 6 shows · 8 statements across 6 episodes
Cheeky Pint
Latent Space
No Priors
Sourcery
the a16z Podcast
20VC
8 statements about Foundation Model Labs, every show
Zhang: Vertical AI applications will outperform general lab-built agents
“The labs themselves will have more application capabilities, but those will be fairly general. Like they're, you can maybe build general agents that can do this thing or that thing. But for a lot of these like core verticals, like ours, our thesis is that, you…”
Weinberg: Every AI company is competing against foundation model labs
“And I really do think at the end of the day, it is a race against the labs, and I think every single company on earth is competing against them.”
Weinberg: Foundation labs will acquire startups in high-traction verticals
“I think that they will start acquiring in any space where they see a significant amount of traction.”
Randle: AI labs set the baseline competition for application startups
“For a lot of these categories, the labs set the baseline in terms of customer experience. They're like, they're your competition at your base layer. And so whatever you can get from ChatGPT or whatever you can get from anything directly from the labs apps them…”
Zhang: Foundation model labs will target consumer applications before enterprise software
“I think it makes a lot of sense for them to push into application layer, and I think they will. In terms of what applications, I mean, generally they'll probably start with applications where it's more consumer prosumer-y because there's, it's just more self-c…”
Osika: Agentic orchestration and UX are the hardest parts of AI products
“The hardest part to get right is this inter interaction between like the AI, the complex agentic systems of like how the models are used and the user experience.”
Reddy: Test-time scaling currently works best for verifiable domains like math
“It seems like OpenAI has cracked a version of this that works, and we think A, Foundation Model Labs will come up with better ways of doing this, and B, so far it largely works for very verifiable domains, things that look like math and physics and maybe secon…”
Reddy: Mega model labs absorbed $30B-$40B of 2024 AI venture funding
“If you break out the numbers here a bit more, the red is actually just a small number of foundation model labs, like what you would think of as the largest labs raising money, which is upwards of 30 to forty billion dollars this year, and so the reality of the…”