Bret Taylor

bad at, for good reason, I don't think it's necessarily what we do, is actually helping companies manage the adoption of this technology. Most software companies try to be trusted advisors to their companies, but at the end of the day, they have a vested interest in the product that they're selling. And it often helps to have a third party there to help you actually manage that change.

bad at, for good reason, I don't think it's necessarily what we do, is actually helping companies manage the adoption of this technology. Most software companies try to be trusted advisors to their companies, but at the end of the day, they have a vested interest in the product that they're selling. And it often helps to have a third party there to help you actually manage that change.

bad at, for good reason, I don't think it's necessarily what we do, is actually helping companies manage the adoption of this technology. Most software companies try to be trusted advisors to their companies, but at the end of the day, they have a vested interest in the product that they're selling. And it often helps to have a third party there to help you actually manage that change.

So I do think that there's probably some short-term professional services spend that reflects the lack of the maturity of the AI applications market right now. When there are solutions like Sierra and others for specific domains available, you shouldn't have to spend as much to deploy those effectively in your business.

So I do think that there's probably some short-term professional services spend that reflects the lack of the maturity of the AI applications market right now. When there are solutions like Sierra and others for specific domains available, you shouldn't have to spend as much to deploy those effectively in your business.

So I do think that there's probably some short-term professional services spend that reflects the lack of the maturity of the AI applications market right now. When there are solutions like Sierra and others for specific domains available, you shouldn't have to spend as much to deploy those effectively in your business.

However, I think that as AI changes and disrupts the way companies operate, you know, I would hope that the best professional services firms have consulting arms that can help companies with that change management and it might compensate it for a different way. So I think if you itemize the receipts, the revenue might change over time.

However, I think that as AI changes and disrupts the way companies operate, you know, I would hope that the best professional services firms have consulting arms that can help companies with that change management and it might compensate it for a different way. So I think if you itemize the receipts, the revenue might change over time.

However, I think that as AI changes and disrupts the way companies operate, you know, I would hope that the best professional services firms have consulting arms that can help companies with that change management and it might compensate it for a different way. So I think if you itemize the receipts, the revenue might change over time.

let's start with the high level i really like reid hoffman's framing of this market as foundation models and frontier models so foundation models are any of these large language models that aren't necessarily the best of the best or the higher highest parameter count but particularly now where you have relatively low parameter count models that are meter exceed the quality of say gpt 3.5

let's start with the high level i really like reid hoffman's framing of this market as foundation models and frontier models so foundation models are any of these large language models that aren't necessarily the best of the best or the higher highest parameter count but particularly now where you have relatively low parameter count models that are meter exceed the quality of say gpt 3.5

let's start with the high level i really like reid hoffman's framing of this market as foundation models and frontier models so foundation models are any of these large language models that aren't necessarily the best of the best or the higher highest parameter count but particularly now where you have relatively low parameter count models that are meter exceed the quality of say gpt 3.5

That market of foundation models is quite important and quite commoditized in that market. If you need a model like that, you should download Lama. That's the answer. It's like you don't need much of a cheat sheet on that, you know, or maybe Mistral, but pick one of the open source models that are adequate and fine tune it.

That market of foundation models is quite important and quite commoditized in that market. If you need a model like that, you should download Lama. That's the answer. It's like you don't need much of a cheat sheet on that, you know, or maybe Mistral, but pick one of the open source models that are adequate and fine tune it.

That market of foundation models is quite important and quite commoditized in that market. If you need a model like that, you should download Lama. That's the answer. It's like you don't need much of a cheat sheet on that, you know, or maybe Mistral, but pick one of the open source models that are adequate and fine tune it.

The frontier model market is a little different when you talk about this, the experience you've had being dizzy using these tools. My perspective is that we've seen real leaps there. So when ChatGPT came out, that was a meaningful step function change that lasted for a while.

The frontier model market is a little different when you talk about this, the experience you've had being dizzy using these tools. My perspective is that we've seen real leaps there. So when ChatGPT came out, that was a meaningful step function change that lasted for a while.

The frontier model market is a little different when you talk about this, the experience you've had being dizzy using these tools. My perspective is that we've seen real leaps there. So when ChatGPT came out, that was a meaningful step function change that lasted for a while.

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.

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.