Zico Colter

custom-trained machine learning model for this. But the idea is that once you have a task, a rote task that you're repeating again and again enough times, and you know a small model can do it, it probably does become valuable to specialize a small model for that task only.

custom-trained machine learning model for this. But the idea is that once you have a task, a rote task that you're repeating again and again enough times, and you know a small model can do it, it probably does become valuable to specialize a small model for that task only.

I think that actually has much more to do with our benchmarks and the way people typically are used to using these models than the models themselves. If you look at some of the hardest problems that models sort of face, we are still seeing gains to larger models of different techniques, things like this. Part of the problem here actually is sort of these models are a victim of their own success.

I think that actually has much more to do with our benchmarks and the way people typically are used to using these models than the models themselves. If you look at some of the hardest problems that models sort of face, we are still seeing gains to larger models of different techniques, things like this. Part of the problem here actually is sort of these models are a victim of their own success.

I think that actually has much more to do with our benchmarks and the way people typically are used to using these models than the models themselves. If you look at some of the hardest problems that models sort of face, we are still seeing gains to larger models of different techniques, things like this. Part of the problem here actually is sort of these models are a victim of their own success.

People have started to use these very regularly in their daily lives and they probably have a suite of questions that they ask these models. You know, when they first interact with a model, they'll probably ask it to write a biography of history of your school or a biography of yourself or something like this, but you have a suite of questions you sort of ask these models.

People have started to use these very regularly in their daily lives and they probably have a suite of questions that they ask these models. You know, when they first interact with a model, they'll probably ask it to write a biography of history of your school or a biography of yourself or something like this, but you have a suite of questions you sort of ask these models.

People have started to use these very regularly in their daily lives and they probably have a suite of questions that they ask these models. You know, when they first interact with a model, they'll probably ask it to write a biography of history of your school or a biography of yourself or something like this, but you have a suite of questions you sort of ask these models.

And on a lot of these pre-formatted questions that you know models already kind of do well on, the newer models don't do notably better, right? So, if I say, write a history of Carnegie Mellon University, Lama's 7 billion can do that just fine, right? Or 8 billion now can do that just fine, right? There's no need. I mean, maybe it'll be a little bit better with the largest closed source models, but

And on a lot of these pre-formatted questions that you know models already kind of do well on, the newer models don't do notably better, right? So, if I say, write a history of Carnegie Mellon University, Lama's 7 billion can do that just fine, right? Or 8 billion now can do that just fine, right? There's no need. I mean, maybe it'll be a little bit better with the largest closed source models, but

And on a lot of these pre-formatted questions that you know models already kind of do well on, the newer models don't do notably better, right? So, if I say, write a history of Carnegie Mellon University, Lama's 7 billion can do that just fine, right? Or 8 billion now can do that just fine, right? There's no need. I mean, maybe it'll be a little bit better with the largest closed source models, but

These aren't the kind of questions that are relevant. The domain I use models for most probably is coding and also doing things like transcribing lectures and stuff like this. On those tasks, I am absolutely not seeing plateauing gains. The latest models, they are notably better than the previous iteration and just make my life easier.

These aren't the kind of questions that are relevant. The domain I use models for most probably is coding and also doing things like transcribing lectures and stuff like this. On those tasks, I am absolutely not seeing plateauing gains. The latest models, they are notably better than the previous iteration and just make my life easier.

These aren't the kind of questions that are relevant. The domain I use models for most probably is coding and also doing things like transcribing lectures and stuff like this. On those tasks, I am absolutely not seeing plateauing gains. The latest models, they are notably better than the previous iteration and just make my life easier.

Let me move up to sort of higher and higher levels of abstraction when I give them instructions, when I interact with them, and when I work with them. So This perception has more to do with people's limited imagination of what they can do with these models and less to do with the models themselves. But that will evolve over time.

Let me move up to sort of higher and higher levels of abstraction when I give them instructions, when I interact with them, and when I work with them. So This perception has more to do with people's limited imagination of what they can do with these models and less to do with the models themselves. But that will evolve over time.

Let me move up to sort of higher and higher levels of abstraction when I give them instructions, when I interact with them, and when I work with them. So This perception has more to do with people's limited imagination of what they can do with these models and less to do with the models themselves. But that will evolve over time.

People will start figuring out you can use them for better and better things.

People will start figuring out you can use them for better and better things.

People will start figuring out you can use them for better and better things.