Very proud of this paper-I think it’s the bee’s knees. Check it out.

Every French🇫🇷 passenger train, on an ordinary Tuesday, from first departure to last

It is important to remember when people say “this is what they took from you”, that it’s this. This is what they took from you:

It's important to learn math not because you may need to do long division as an adult, but because it promotes rigorous thinking. IMO, history and causal inference are among the most important subjects a young person can study — math being central to the second. A significant problem in public discourse right now is people's inability to critically evaluate causal claims (e.g., vaccines cause autism, deporting immigrants will solve the housing crisis, etc.). The less able people are to critically evaluate causal claims, the worse our democracy functions because people can be preyed upon for votes. You should promote anything that improves rigorous thinking, even if it doesn't have market value. In fact, we should stop thinking of education only in the context of what improves the economy. IMO, this is distinct from knowing your own address (which Huang can avoid because he's wealthy). Memorizing facts like this may or may not be important, but it's distinct from rigorous thinking.

The past tense of “lead” is “led,” not “lead.”

To me the biggest risk of AI is brain rot. I have more and more situations like this. Some coworker shares a report on something they did. I read, and find something fishy. I ask about and get no answer. I ask again and I'm told: the agent said that. And no follow up. It's clear form the interaction that they did not read the report they shared. Their brain is not used as it should be. I am not against AI at all (fortunate for something working at NVIDIA). I use AI a lot. But I use it as a tool. I own the result and whenever I see something fishy I ask about its output I force a change if I am not convinced. I wish there was a way to force people to read the AI output they share with others.

We need to bring back the notion of "evil" in public discourse, because this is what this is.

As someone who did this kind of genome mining work during my PhD, some thoughts on this Anthropic announcement: First, the very simplified version of what they did is that they noticed two genes (one known, one new) sitting next to a weird repeating piece of DNA. More specifically, they described an unusual reverse transcriptase (RT) associated with a repetitive DNA array and an unknown accessory protein. This kind of process was used to understand CRISPR back in 2002 and was key to the gene editing tools we use today. To put this into context, though, people have been finding RTs associated with CRISPR arrays since 2008, and this general kind of genome-neighborhood mining has been used to discover new biological systems for decades. The basic genome-mining strategy is well established, and there are now mature tools and published pipelines for doing much of this. There are papers that discover and experimentally validate dozens of new systems using this approach in a single study. Doing it in bacteriophage genomes is also nothing new (eg CasPhi). Finding a weird cluster of genes and repeats is often the easy part. The hard part, and where the real discoveries come from, is figuring out what the system actually does. Eg for the bridge-RNA discovery in 2024 from @arcinstitute or the discovery of CasPhi in 2020 from @DoudnaJennifer they figured out the pieces of the system and the rules for what makes it work so it can be used. Anthropic does not yet know what this does. They’ve shown that the repeat array produces RNAs, but not what those RNAs do, what the RT does with them, or whether the system has any of the programmable properties that make the CRISPR comparison justified. I’m genuinely rooting for all of the frontier labs to seriously get into biological discovery, and I’m excited about what comes out of it. But announcing these very early, incremental findings with the framing of a major discovery doesn’t help. I’d much rather they set the bar high now, so that when an AI actually discovers a fundamentally new biological mechanism, everyone appreciates how big a deal it is.

This is *exactly* why I say we need *more* human mathematicians now than ever, not fewer! I watched the video, start to finish. I'm not a combinatorialist, but I understood every word, and could have understood every word as an undergrad. (The idea of counting things and showing that the count is positive, and therefore concluding that the things actually exist, is very familiar to number theorists!!..) I'm embarrassed I never even heard of this problem, despite my great Rutgers colleagues Szemeredi and Komlos and others (the Hungarian mafia) having worked on it. It's a beautiful problem, and beautiful solution. "From the BOOK", as a certain Hungarian might say :) If AI keeps coming up with amazing arguments like these, we, again, need many more mathematicians to go through them, make sense of them, incorporate the ideas in new research and textbooks, etc etc. So much work to be done; all hands on deck!

Really nice report. Follow up: why has the fall in AI prices been so fast? When you plot the price decline against cumulative R&D investment rather than time, you get the elasticity of price declines to R&D investment. By this margin, AI is not unusual – its price elasticity to R&D investment is squarely in the middle of Epoch's considered technologies. So the AI price fall is historically unprecedented because we've dumped money into AI R&D at a historically unprecedented rate – and that R&D has paid off at a very average rate.

A few weeks ago Astra gave a stunningly simple proof of the Erdős-Sós conjecture in graph theory (previously thought to be very difficult). It has been a good example of how the lifecycle of AI proofs should be: after the AI formalisation posted at erdosproblems.com/548 1/

the plan? fire all of our profitable customers

Writing is thinking. It is completely reasonable to have an academic journal policy that requires submitters to prove that at least one academic has thought about the topic enough to write a few pages of their own words about it.

It's bizarre how casually Republicans now accept massive government intrusions into the free market, not because of a national-security emergency, but because stuff is expensive.

Two kinds of drift I see when students rely heavily on agents in research (even when overall use is reasonable): 1. Project direction drifts & more effort is needed to bring things back to initial goals. Easy to spend wks talking thru nuances of tangential aspects of the work. 1/

On this note; we have updated our paper on the local effects of data centers. We now have a 🚨new instrument for data center development🚨 leveraging historical determinants of fiber connectivity and foreign growth in large scale facilities. Effects are substantial, and qualitatively align with those of our earlier draft. nitter.net/nberpubs/status/205611…

The US took a big step toward greater state ownership or control of the economy—a form of socialism—in 2025. This change is occurring under unified Republican domination of the US government. #PIIECharts

Agree that ethics are socially constructed. But at least the Deontologist-Consequentialist split, if not natural law, seems like a Natural distinction. Deontological systems assign moral weight to considerations ex ante of actions, & Consequentialist to considerations ex post.

en.wikipedia.org/wiki/Funes_… as always Borges is worth a re-read

This is the dumbest government in history

Astonishing how many posts like this there are about Tao, someone with no apparent arrogance who has spent his life sharing his gifts with the world.