Azeem Azhar

And now it took five years for everyone to transition.

If you can compress any part of that process, you can deliver enormous consumer benefit, but it may not show up in GDP.

it may just show up in better services.

Well, I gave you the excitable bull case there, but there is also the bear case that you alluded to through the Ben Jones paper, which makes me think of a year or so ago, Microsoft had a foundation model look at catalysts.

And I think they

came up with 35 million materials in one afternoon.

And I thought back to Mitlach, who was Fritz Haber's co-worker on the Haber-Bosch process, who painstakingly looked at 2,500 compounds over the course of many, many months.

And so we moved from a

discovery process to actually a sifting and verification bottleneck, which those bottlenecks maybe require new skills, they might require new regulation, they might require sociological changes.

And so it might take quite a long time to work all your way through the system.

You know, you just essentially move the bottleneck from discovery or work done to

sorting or verification.

And that might just slow us down again, and it becomes not so much the burden of knowledge, but the burden of sifting.

I think that this is such a good point for me, if I may, to bring in a question that came from Claude 4.5 Opus on specifically this issue.

So I'm just going to scroll up to my notes and just pull it out.

So this was a super interesting point that it made.

And it said, look, if you take a lawyer and you automate 90% of a lawyer's task, the 10% of the task that is remaining has all the liability sitting on it.

And so the question is whether you really, who benefits in that circumstances?

I mean, you know, I never wanted to be a lawyer, but a job where the only thing you do is put your neck on the line for the bit that the machine can't do doesn't feel very, very nice.

So court question was really relating to that, which was if we end up getting 90% of the way through, you know, automation,