Why the "SaaS is dead" narrative is completely wrong - Aaron Levie [box]

Super excited to have you on.

I know you have a very interesting take about AI.

I'm curious to get your last take on what happened with Anthropic recently, because I think you said it was a big win for open and lightweight models.

So can you maybe elaborate on your thoughts on the topic?

Yeah.

So so so I think what first of all, the fable model is is, you know, kind of an unprecedented level of of intelligence and capability.

So so the clearly anthropic, you know, designed an incredible and trained an incredible model.

But the US government effectively enacting an export control, which meant that non-US citizens aren't able to use the model, is really kind of a completely new precedent and moment in AI regulation.

where we've never seen that before for any kind of frontier model being held back legally from being available in the market.

And the implications are, first of all, it's almost entirely impractical for any AI lab to be fully responsible for you know, the nationality of the customers that are using it.

At a minimum, it would completely obliterate the API business of Anthropic because, you know, the idea that you would be able to control the end customer, you know, through your partner ecosystem is very, very difficult.

So it effectively has the impact of making the model unavailable to the world.

And so the risk is if you were either a major app developer and you want to be able to make this technology available to your customers, or you're a country anywhere around the world that wants to continue to ensure that your ecosystem is able to build on top of leading frontier AI, this poses an all new risk, which is at any moment, can that AI model get pulled back from one government or due to one government.

And we just never had that precedent before.

You know, AI has been this sort of very fast moving, very market based ecosystem over the past couple of years.

And so, you know, I think, first of all, the U.S. government probably very quickly needs to to improve the situation with Anthropic.

I think Anthropic is quite motivated to resolve whatever the particular issues are.

But even when that happens, it's easy to kind of think in a year from now or three years from now or five years from now, how many more versions of this might we see in this landscape that will play out? And so it sort of makes you wonder, well, if you're a country, Germany, France, Japan, UK, and you have the capability to be at frontier or near frontier AI from a talent and an infrastructure standpoint, do you need to be building these kinds of models yourself and make sure that you have them available to businesses and users within your country? I think it really kind of introduces that question in a much bigger way.

And we've already seen, obviously, examples of this China, obviously, developing, you know, kind of great open source models, Mistral, you know, doing the same.

But I think this highlights the increased importance in that dynamic and the idea that you can have sovereign AI or AI that you control.

Now, there's one there's sort of one caveat to all of this, though, which is which is.

You know, you're not going to you're not going to take that big of a of a sacrifice or a discount on your on the model's intelligence for that benefit.

So if Frontier from US in a in a kind of a closed model environment stays.

10, 20, 30, 50% better than the next best model that you could make sovereign, I think people will take that risk and they will use the frontier model at all times.

So this only works if open weights models or sovereign AI can remain close to the frontier and much closer that it has historically.

Super excited to have you on.

I know you have a very interesting take about AI.

I'm curious to get your last take on what happened with Anthropic recently, because I think you said it was a big win for open and lightweight models.

So can you maybe elaborate on your thoughts on the topic?

Yeah.

So so so I think what first of all, the fable model is is, you know, kind of an unprecedented level of of intelligence and capability.

So so the clearly anthropic, you know, designed an incredible and trained an incredible model.

But the US government effectively enacting an export control, which meant that non-US citizens aren't able to use the model, is really kind of a completely new precedent and moment in AI regulation.

where we've never seen that before for any kind of frontier model being held back legally from being available in the market.

And the implications are, first of all, it's almost entirely impractical for any AI lab to be fully responsible for you know, the nationality of the customers that are using it.

At a minimum, it would completely obliterate the API business of Anthropic because, you know, the idea that you would be able to control the end customer, you know, through your partner ecosystem is very, very difficult.

So it effectively has the impact of making the model unavailable to the world.

And so the risk is if you were either a major app developer and you want to be able to make this technology available to your customers, or you're a country anywhere around the world that wants to continue to ensure that your ecosystem is able to build on top of leading frontier AI, this poses an all new risk, which is at any moment, can that AI model get pulled back from one government or due to one government.

And we just never had that precedent before.

You know, AI has been this sort of very fast moving, very market based ecosystem over the past couple of years.

And so, you know, I think, first of all, the U.S. government probably very quickly needs to to improve the situation with Anthropic.

I think Anthropic is quite motivated to resolve whatever the particular issues are.

But even when that happens, it's easy to kind of think in a year from now or three years from now or five years from now, how many more versions of this might we see in this landscape that will play out? And so it sort of makes you wonder, well, if you're a country, Germany, France, Japan, UK, and you have the capability to be at frontier or near frontier AI from a talent and an infrastructure standpoint, do you need to be building these kinds of models yourself and make sure that you have them available to businesses and users within your country? I think it really kind of introduces that question in a much bigger way.

And we've already seen, obviously, examples of this China, obviously, developing, you know, kind of great open source models, Mistral, you know, doing the same.

But I think this highlights the increased importance in that dynamic and the idea that you can have sovereign AI or AI that you control.

Now, there's one there's sort of one caveat to all of this, though, which is which is.

You know, you're not going to you're not going to take that big of a of a sacrifice or a discount on your on the model's intelligence for that benefit.

So if Frontier from US in a in a kind of a closed model environment stays.

10, 20, 30, 50% better than the next best model that you could make sovereign, I think people will take that risk and they will use the frontier model at all times.

So this only works if open weights models or sovereign AI can remain close to the frontier and much closer that it has historically.