Bret Taylor

And the insight around instruction tuning and the quality of sort of the GPT models after GPT-3 was pretty remarkably different. Similarly, when GPT-4 came out, I haven't done the math on it, but it certainly had a meaningful lead for quite a while. And now you're seeing a lot of models sort of catch up to that.

My sense is we see a lot of incremental improvement followed by step changes in quality. But going back to the market itself, I am inherently skeptical of companies doing pre-training, unless you are an AGI research lab. Doing pre-training on a model, I believe, is just burning capital.

My sense is we see a lot of incremental improvement followed by step changes in quality. But going back to the market itself, I am inherently skeptical of companies doing pre-training, unless you are an AGI research lab. Doing pre-training on a model, I believe, is just burning capital.

My sense is we see a lot of incremental improvement followed by step changes in quality. But going back to the market itself, I am inherently skeptical of companies doing pre-training, unless you are an AGI research lab. Doing pre-training on a model, I believe, is just burning capital.

It's roughly the equivalent of an entrepreneur coming to you and saying, you know, we're building this software solution, and the first thing we're going to do is build our data center by hand.

It's roughly the equivalent of an entrepreneur coming to you and saying, you know, we're building this software solution, and the first thing we're going to do is build our data center by hand.

It's roughly the equivalent of an entrepreneur coming to you and saying, you know, we're building this software solution, and the first thing we're going to do is build our data center by hand.

And I think for 99% of software companies, they should lease their servers from an infrastructure as a service provider, not because it's the most vertically integrated and efficient, but because it's not what their company does. Similarly, as you're exploring and finding product market fit, the last thing you want to do is have a big upfront investment to build a data center.

And I think for 99% of software companies, they should lease their servers from an infrastructure as a service provider, not because it's the most vertically integrated and efficient, but because it's not what their company does. Similarly, as you're exploring and finding product market fit, the last thing you want to do is have a big upfront investment to build a data center.

And I think for 99% of software companies, they should lease their servers from an infrastructure as a service provider, not because it's the most vertically integrated and efficient, but because it's not what their company does. Similarly, as you're exploring and finding product market fit, the last thing you want to do is have a big upfront investment to build a data center.

There was a number of companies that were started by incredibly talented AI researchers. And, you know, step one of their product plan was build, pre-train a model. And I think for especially with the existence of these high quality models like, you know, GPT-4.0,

There was a number of companies that were started by incredibly talented AI researchers. And, you know, step one of their product plan was build, pre-train a model. And I think for especially with the existence of these high quality models like, you know, GPT-4.0,

There was a number of companies that were started by incredibly talented AI researchers. And, you know, step one of their product plan was build, pre-train a model. And I think for especially with the existence of these high quality models like, you know, GPT-4.0,

mini that you can fine tune or the open source models like Lama 3.1 to spend capital on pre-training now, unless you're one of the behemoths, I think is nonsensical.

mini that you can fine tune or the open source models like Lama 3.1 to spend capital on pre-training now, unless you're one of the behemoths, I think is nonsensical.

mini that you can fine tune or the open source models like Lama 3.1 to spend capital on pre-training now, unless you're one of the behemoths, I think is nonsensical.

Do you remember in the early 90s, it went from like Windows NT to 95 to 98 to 2000, you know, or something like that. I might be mixing it up. So, you know, we could pull that out to start changing numbers up.

Do you remember in the early 90s, it went from like Windows NT to 95 to 98 to 2000, you know, or something like that. I might be mixing it up. So, you know, we could pull that out to start changing numbers up.

Do you remember in the early 90s, it went from like Windows NT to 95 to 98 to 2000, you know, or something like that. I might be mixing it up. So, you know, we could pull that out to start changing numbers up.

are distinct to me. So starting with the step function, I don't think it's a foregone conclusion that we'll have step function changes. I believe the most responsible way to develop AGI is responsible iterative deployment. The reason for that is I believe that as you're thinking about things like the societal impact, access to this technology and the safety side of AGI as well, that the