Companies should keep the intelligence their AI use creates

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 9:05

   You said about kind of the importance of owning your own intelligence for some of your amazing customers that you have. You're talking about some in the UK. Is that the model environment that we have moving forward, specialized intelligence for companies with their own data? Yeah, so I think this is, to me, one of the most important things, which is what's the future of a firm in an era of intelligence, right?

2. 9:24

   because if you go back even to Hayek, his fundamental description of an economy is local intelligence. Tacit knowledge is distributed throughout the economy. Without that, there can't be only one firm and it can't be one intelligence. And so that's sort of the foundational thing. In fact, capitalism works because of that. Price discovery works because of that. Or pricing mechanism works because of that. So therefore, I think it'll be important for every firm to be able to accumulate knowledge at increasing scales using AI versus leak. That's why I called it the reverse information paradox, which is Kenneth Arrow described this paradox of information where if you're a seller and you disclose the secret without a patent or a trade secret protection or copyright protection, you leak the value. Now, for the first time, the buyer needs

3. 10:15

   the protection because the buyer, even most people think of it as, oh, my data, it's even my exhaust of using it, right? Thumbs up, thumbs down signal. You're creating value for the model company versus capturing that value for yourself. So I think one of the things that at least I ascribe is that we need to have... For this to be stable, more of that surplus that gets created by use of intelligence to remain at the firm. And by the way, it doesn't need to be only by embedding your knowledge and weight. It can be in context. It can be in your evals, right? You may have a benchmark. In fact, one of the things that I'm very gung-ho about is we all become, every firm will have a private eval benchmark, which is their core IP. And every model comes in and tries to sort of hill climb on that eval. And that to me is how a firm works. I love this. Private evals, benchmarks for each company.

4. 11:01

   This is for a rarefied era of companies that would seem your Harveys or your Lagoras or the kind of very forward thinking AI companies. Will that disperse to every company in the world you mentioned? Yeah, it happens. Yeah, it happens, Harry, always, right? Which is, you know, there was a day when And I remember in the late 80s and the early 90s that the few companies that had deployed PCs and were doing forecasting, which felt magical.

5. 11:26

   They were able to put it in Excel, spreadsheets, send it in email and avoid the fax machine and inter-office memos. And it felt like, oh, wow, when will this happen? And it took 10 years maybe, and it spread out throughout. This time around, what is considered, oh, I'm an AI native company and I do this. I think, you know, five years from now, it'll be pretty passe, I would imagine. And then that's kind of what, I mean, these tech cycles always start like that, right?

6. 11:50

   Which is even cloud. I remember in the beginning of cloud, it was like the big deal was, oh, who's cloud native and who's not? And, you know, if you're not cloud native, and now everybody is, right? Even Lloyd's, you know, which is what, 500 years old, is cloud native. And so it happens. Do we move into an implementation economy then?