Stefano Ermon

“I felt like this is going to be very hard as a problem. So it's going to keep me busy for my whole career and it's a good problem.”

Expects: Ermon expected generative modeling to be difficult enough to occupy his entire career. · no date given · not yet resolved

“I think everyone cares about speed in the sense that if you can give me the same quality but faster, people will always pick the faster solution.”

Expects: People will choose a faster solution when it provides the same quality as a slower one. · no date given · not yet resolved

“That's why it's so exciting because things are changing and then this technology is so important and so valuable that having something differentiated, I think will create value.”

Expects: The speaker thinks that a differentiated offering based on this technology will create value because the technology is important and valuable. · no date given · not yet resolved

“So being able to scale better along that axis will also matter.”

Expects: The speaker expects the ability to scale test-time compute more effectively to matter. · no date given · not yet resolved

“And so that's why we decided to bet on a diffusion-based LLM because it's inherently more parallel and the bitter lesson is that the more parallel solution is the one. And is the one that is eventually going to win.”

Expects: The speaker predicts that the more parallel solution will eventually win. · no date given · not yet resolved

“And so at the very least, as a lower bound, I think it could be addressable by models that are within a given latency budget, they would give you the highest possible quality.”

Expects: At least some latency-sensitive workloads could be served by models that maximize quality within a specified latency budget. · no date given · not yet resolved

“uh we still use a lot of the public data sets that people have created and evals and benchmarks so you know we're a startup we try to be scrappy we try to use existing things as much as possible and kind of like focus on the on the the aspects where we can have the highest impact and then where we can be the most differentiated and right now it's speed in the future who knows like it's possible that a diffusion based language model will be be maybe significantly more intelligent than an autoregressive one like nobody knows that that's why i think this is very exciting because we're developing these really powerful ai systems but it's all very fresh it's all very new uh i doubt we've discovered the best way of building these systems there's got to be alternative there's got to be other ways of building these models and and eventually yeah efficiency will be very important like if you think about the ai factor”

Expects: A diffusion-based language model might eventually be significantly more intelligent than an autoregressive model. · no date given · not yet resolved

“uh we still use a lot of the public data sets that people have created and evals and benchmarks so you know we're a startup we try to be scrappy we try to use existing things as much as possible and kind of like focus on the on the the aspects where we can have the highest impact and then where we can be the most differentiated and right now it's speed in the future who knows like it's possible that a diffusion based language model will be be maybe significantly more intelligent than an autoregressive one like nobody knows that that's why i think this is very exciting because we're developing these really powerful ai systems but it's all very fresh it's all very new uh i doubt we've discovered the best way of building these systems there's got to be alternative there's got to be other ways of building these models and and eventually yeah efficiency will be very important like if you think about the ai factor”

Expects: Whether a diffusion-based language model will eventually be significantly more intelligent than an autoregressive model is possible but unknown. · no date given · not yet resolved

“be maybe significantly more intelligent than an autoregressive one like nobody knows that that's why i think this is very exciting because we're developing these really powerful ai systems but it's all very fresh it's all very new uh i doubt we've discovered the best way of building these systems there's got to be alternative there's got to be other ways of building these models and and eventually yeah efficiency will be very important like if you think about the ai factor”

Expects: The speaker expects efficiency to become very important for AI systems. · no date given · not yet resolved

“be maybe significantly more intelligent than an autoregressive one like nobody knows that that's why i think this is very exciting because we're developing these really powerful ai systems but it's all very fresh it's all very new uh i doubt we've discovered the best way of building these systems there's got to be alternative there's got to be other ways of building these models and and eventually yeah efficiency will be very important like if you think about the ai factor”

Expects: Efficiency will eventually be very important in AI systems. · no date given · not yet resolved