Azeem Azhar

My own view is you probably would.

You generally have always needed scientific breakthroughs to improve things, even if it's a car engine or the way in which you build a bridge.

But Demis, who knows much more about this than me, will likely say, without putting words in his mouth, we don't know.

We don't know how far this will go.

We don't know whether it will necessarily take us there.

So all of those things, I think, are frictions on OpenAI.

They add to the bear case.

They talk about really, really deep scientific and technical risk.

They talk about some market risk.

They talk about general execution risk through which OpenAI needs to sail.

And of course, to the question that's just come in about the recent MIT paper, which, you know, pours cold water on the bull hypothesis.

It's worth saying that, you know, the evidence for actual value is, in my view, stacked toward there being value, but there is contrary evidence emerging.

That MIT paper, which made it into the Financial Times and elsewhere and amongst investors, is worth noting.

exploring.

I wrote about it in an issue of the newsletter a couple of weeks ago.

It said essentially that enterprises said that in 90 or 95% of the case, generative AI projects were not working.

But I had

some real kind of issues and problems with the methodology of that paper in terms of the way in which participants were sampled, the way in which the data was gathered.

It was not a representative sample.

It didn't feel like the questioning adhered to the kind of standard that you'd expect