Tim Davis

But I think...

You know, you need to look at, there is significant revenue consolidation on who is paying.

You always look at where is the money coming from, right?

At the end of the day, the money is coming from, you know, essentially the magnificent seven technology companies, which represent roughly, I believe, 30% of the S&P 500 in terms of market capitalization.

Right.

So, you know, if they're the ones buying all the compute...

you would have to look at their businesses in the long term and say, is that sustainable?

I think the challenge, of course, is at least at that level, they're also building all their own chips.

In many ways, there's this purchasing of additional capacity from companies like OpenAI, but then

You know, it's been interesting to see in the media that OpenAI is also now trying to build its own silicon.

And traditionally, that's what you see, right?

Like you see, and I think, you know, this was true even at Google, you see, you start with sort of models and you train models.

And then what you do is you go up the stack and you go up into the cloud and you say, well, now I need to get mass distribution for my model and prove that this is an app, you know, one.

a compelling set of technology that has vast user adoption and that is economically viable.

And then you prove that there's large revenue generation and then very quickly you're like, now I need to go down because I need to figure out how do I get better costs, cost optimization across the silicon.

And so I think what you, and obviously OpenAI has been the most famous on this, you could compare it to Anthropic with Tranium and their relationship with AWS in a similar way.

But a lot of it is just this constant belief.

And I think that, I do personally think that we are right to challenge it.

Is the future of superintelligence just continuing to scale these models larger and larger and larger and larger?

Is that actually getting us on the path to some form of superintelligence?