I get capital vs labor and everything in between as it comes to AI but… The moment you hear “you can throw money at the problem” is the moment the market is telling you that pretty soon you should sell.

I get many philanthropic organizations suck but there is some irony in brian saying they suck because he can't think of any that haven't been captured by ideology when this is like the core thing that happened in crypto and he and his company also have spent 10s of millions of dollars trying to push ideology around crypto at the state and federal levels. It might just be that there are both useful and bad actors in any given industry. Disclaimer: i haven't watched full interview.

A bit of a rambling idea space on AI but: increasingly i do feel like these types of things (style/bias tweet below is written in, latest podcast with dwarkesh + dylan, other content) from a subset of insiders are a rorschach test for if you believe hyper narrow but incredibly deep insights win out in how one predicts the future versus one layer up but more well-rounded/mutli-disciplinary understandings. A lot of the takes kind of bridge the gap of understanding capitalism shifts very well but don’t understand how capitalism drives competition which drives margin compression and cost structure change which drives trajectory. It's why you see people like @alexolegimas or @stevehou quickly weighing in to lend some thinking in many cases, or more famously, Cowen's takes on diffusion. Admittedly, I have bias due to crypto, in which a subset of the industry got one thing very right (btc or eth mostly) and then extrapolated the learnings of believing in the first-order long-tail outcome to then get a bunch of things very wrong, or at a minimum, getting the timelines of change very wrong, while telling everyone how they just didn't get it. Obviously these are very different dynamics because the economic value and productivity from AI is so much larger than crypto today, but the level of hot takes and centralization of "those in the know" and how they think feels actually quite similar, and the dogmatic nature does as well. Perhaps this is the academic versus applied thinking, in which edges of academic theory can get direction of progress very right vs consensus but as that runs up against real-world complexities and human complexities, the applied thinking can get the second leg up of trajectory more correct. This shift is perhaps the heart of building an applied research organization. I know nothing about AMD internal politics, and so many companies in times of rapid technological change run into the problem of "we must try to do it our way, and then fail, in order to change our mind", and AMD definitely feels like one of those. But also this sounds very similar to many of the people who have now boomerang'd from "my bigco sucks, time to start my own co or join newco that is cooler" back to "my bigco was right/is good/turns out they had their reasons, newcos are not great." Anyways, am sure people will have lots of feels here and generally the tension across all of these is what makes company building, analysis, and investing so fun right now, especially because there are so many vectors in which one can be wrong, but still be very right, and vice versa. Just love that we get to see it all play it pretty publicly.

the guys at @CompoundVC write so well that it literally became my last trigger to finally download the Substack app. i've been aggressively uninstalling apps for the past few months, trying to limit my phone usage to basically just X. but i found another reason today to finally add a new one. everyone on their team is a must-follow. and in fact, i beg you to. it's hard to find people who have such a tasteful degree of culture paired with superb intellectual capacity. Compound is literally filled with ppl where you actually want to read everything they put out.

I believe if you are trying to anchor your company around a specific Theory of Belief, you also should have very precise views of who sits in the adjacencies to your theory, who is trying/has tried to own/build it, and what prior patterns have worked to corner a similar theory.

small molecule synthesis is stuck decades behind other modalities @satomic_ai is making it more engineerable to enable abundance and eventually abstraction. despite small molecule engineering difficulties, they still are 50% of drug approvals and could be more when Satomic increases the scale and speed of synthesis.