I am not too surprised by this, but I wonder if he still stands by what he said in the interview with Dwarkesh:

Some years ago, in the 2010s, I did some analysis with other people of — if this kind of picture happens then which are the firms and parts of the economy that would benefit. There's the makers of chip equipment companies like ASML, there's the fabs like TSMC, there's chip designers like NVIDIA or the component of google that does things like design the TPU and then there’s companies working on the software so the big tech giants and also companies like OpenAI and DeepMind. In general the portfolio picking at those has done well. It's done better than the market because as everyone can see there's been an AI boom but it's obviously far short of what you would get if you predicted this is going to go to be like on the scale of the global economy and the global economy is going to be skyrocketing into the stratosphere within 10 years. If that were the case then collectively, these AI companies should be worth a large fraction of the global portfolio. So I embrace the criticism that this is indeed contrary to the efficient market hypothesis. I think it's a true hypothesis that the market is in the course of updating on in the same way that coming into the topic in the 2000s that yes, they're the strong case even an old case the AI will eventually be biggest thing in the world it's kind of crazy that the investment in it is so small. Over the last 10 years we've seen the tech industry and academia realize that they were wildly under investing in just throwing compute and effort into these AI models. Particularly like letting the neural network connectionist paradigm languish in an AI winter. I expect that process to continue as it's done over several orders of magnitude of scale up and I expect at the later end of that scale which the market is partially already pricing in it's going to go further than the market expects.

> Dwarkesh Patel 02:32:28

Has your portfolio changed since the analysis you did many years ago? Are the companies you identified then still the ones that seem most likely to benefit from the AI boom?
> Carl Shulman 02:32:44

A general issue with tracking that kind of thing is that new companies come in. Open AI did not exist, Anthropic did not exist. I do not invest in any AI labs for conflict of interest reasons. I have invested in the broader industry. I don't think that the conflict issues are very significant because they are enormous companies and their cost of capital is not particularly affected by marginal investment and I have less concern that I might find myself in a conflict of interest situation there.

And chemistry??? Its mostly brought into the picture to talk about stoichiometry, the study of the rate and equilibria of chemical reactions. Still, what?

For what it's worth, deconfusing my patchy chemistry understanding from secondary school by reading proper university chemistry and biochemistry books paid off. For example, my chemistry class hadn't given me deep enough appreciation for the fact that sometimes a reaction might be thermodynamically favorable, but has horrible kinetics. The same is true for evolution in a lot of places, but I have not seen a lot of people using that intuition. Like in some sense that is obvious, but in another sense I think in a lot of subjects including evolution, econ and learning I was applying that intuition inconsistently, and I definitely didn't make the distinction that clearly. Since chemistry has explicit energies there that you can calculate, it's easier to not commit type errors.

I noticed the following paragraphs go into more detail about how the sources relate to the claim. So my example wasn't well chosen.

For all Arbital content, there is the Arbital scrape index. Most (all?) of that material has been incorporated into Lesswrong’s concept pages.

It is hard to do as a prefix in German, I think. It sounds a bit antiquated to me, but you could try "Jung war X". But yes, in general, I think you are going to run into problems here because German inflects a lot of words based on the gender.

Your German also gives away the gender. Probably use some language model to double check your sentences.

I queried my brain (I am German) and noticed my claim doesn't predict the result. Then checked online and I had male and female backwards from what I read in a dictionary once

After checking random words I noticed the bias is the other way around and female is more likely. Google gave me the same. Now I am confused.

I don't find it surprising. For example, IIRC in German 1/2 of nouns are male, 1/3 is female, 1/6 is neuter. I'd expect correlations/frequencies in English and other European languages, but harder to spot if you don't have gendered nouns.