This wins my respect.

Back in grad school, when I realized how the “marketplace of ideas” actually works, it felt like I’d found the cheat codes to a research career. Today, this is the most important stuff I teach students, more than anything related to the substance of our research. A quick preface: when I talk about research success I don’t mean publishing lots of papers. Most published papers gather dust because there is too much research in any field for people to pay attention to. And especially given the ease of putting out pre-prints, research doesn’t need to be officially published in order to be successful. So while publications may be a prerequisite for career advancement, they shouldn’t be the goal. To me, research success is authorship of ideas that influence your peers and make the world a better place. So the basic insight is that there are too many ideas entering the marketplace of ideas, and we need to understand which ones end up being influential. The good news is that quality matters — other things being equal, better research will be more successful. The bad news is that quality is only weakly correlated with success, and there are many other factors that matter. First, give yourself multiple shots on goal. The role of luck is a regular theme of my career advice. It’s true that luck matters a lot in determining which papers are successful, but that doesn’t mean resigning yourself to it. You can increase your “luck surface area”. For example, if you always put out preprints, you get multiple chances for your work to be noticed: once with the preprint and once with the publication (plus if you’re in a field with big publication lags, you can make sure the research isn’t scooped or irrelevant by the time it comes out). More generally, treat research projects like startups — accept that there is a very high variance in outcomes, with some projects being 10x or 100x more successful than others. This means trying lots of different things, taking big swings, being willing to pursue what your peers consider to be bad ideas, but with some idea of why you might potentially succeed where others before you failed. Do you know something that others don’t, or do they know something that you don’t? And if you find out it’s the latter, you need to be willing to quit the project quickly, without falling prey to the sunk cost fallacy. To be clear, success is not all down to luck — quality and depth matter a lot. And it takes a few years of research to go deep into a topic. But spending a few years researching a topic before you publish anything is extremely risky, especially early in your career. The solution is simple: pursue projects, not problems. Projects are long-term research agendas that last 3-5 years or more. A productive project could easily produce a dozen or more papers (depending on the field). Why pick projects instead of problems? If your method is to jump from problem to problem, the resulting papers are likely to be somewhat superficial and may not have much impact. And secondly, if you’re already known for papers on a particular topic, people are more likely to pay attention to your future papers on that topic. (Yes, author reputation matters a lot. Any egalitarian notion of how people pick what to read is a myth.) To recap, I usually work on 2-3 long-term projects at a time, and within each project there are many problems being investigated and many papers being produced at various stages of the pipeline. The hardest part is knowing when to end a project. At the moment you’re considering a new project, you’re comparing something that will take a few years to really come to fruition with a topic where you’re already highly productive. But you have to end something to make room for something new. Quitting at the right time always feels like quitting too early. If you go with your gut, you will stay in the same research area for far too long. Finally, build your own distribution. In the past, the official publication of a paper served two purposes: to give it the credibility that comes from peer review, and to distribute the paper to your peers. Now those two functions have gotten completely severed. Publication still brings credibility, but distribution is almost entirely up to you! This is why social media matters so much. Unfortunately social media introduces unhealthy incentives to exaggerate your findings, so I find blogs/newsletters and long-form videos to be much better channels. We are in a second golden age of blogging and there is an extreme dearth of people who can explain cutting-edge research from their disciplines in an accessible way but without dumbing it down like in press releases or news articles. It’s never too early — I started a blog during my PhD and it played a big role in spreading my doctoral research, both within my research community and outside it. Summary * Research success doesn’t just mean publication * The marketplace of ideas is saturated * Give yourself multiple shots on goal * Pick projects, not problems * Treat projects like startups * Build your own distribution

The sad robot in is Grok 4. This shows again how careful one has to be with overblown claims from closed releases saying the usual "it's so over". Test contamination that cannot be checked makes benchs look great, but on novel problems, the crash comes.

I debated 20 far-far-far-right conservatives on Jubilee's 'Surrounded.' Below are some brief highlights of them unable to answer my basic questions or rebut the simplest of points. Not sure whether to laugh or cry. Here's the full eye-opening 'debate':

The majority of COVID-19 infections occur via near-field transmission (aerosols travelling 1-2m from infectious person). Sitting below a ceiling fan reduces aerosol concentration in the breathing zone by 87%. @ukhadds

Don't leave AI to the STEM folks. They are often far worse at getting AI to do stuff than those with a liberal arts or social science bent. LLMs are built from the vast corpus human expression, and knowing the history & obscure corners of human works lets you do far more with AI

the imo gold result is very cool. that said, i dont know why people are losing their minds. remember o3 and how we thought our jobs were all doomed and it was joever because of arc-agi and frontier math? hillclimbing math is going much faster (for now) than "general utility"

would be less misleading if you printed the entire graph I was definitely thinking AI IMO gold would happen this year (was close last year and FrontierMath results are suggestive of IMO gold)... not sure what brought the probability down in the final stretch

nb this was tweeted 7 hours before OAI announced their gold result

"Kids don't spread" Remember that?