Five major databases of human surface proteins agree on only 188 of them. So we had Claude read the literature instead. Today @deliverome is releasing an open atlas of the accessible human surfaceome, with claims traced directly to quotes from their source 🎯

Free coffee and free merch at SOHN right now?!

If you care about biotech and drug development watch this interview with Matt Gline, the CEO of Roivant, a biotech firm that is now worth $24 billion. He talks about why he thinks predictions about AI from people like Anthropic’s Dario Amodei are overly optimistic. “If Dario is right and I'm wrong, and he cures every disease in five years, man, are we all the winners from that outcome,” Gline said. “I think if you work in this industry, it is very hard not to be skeptical of any of those claims. Because, and I've said this in other settings recently too, biotech is a wood chipper that like is built to like ingest souls and shred them. It's just like such a hard business that like someone comes and they're like, oh, but I've built a computer and I'm going to push a button and all of that goes away and it just works. Like that is probably not the way that's going to go.”

Wood is the rarest material in the Universe.

1/3 🚨 WATCH: MAGA uses bots to hack the ALGORITHM and REALITY, The James Talarico Story PART 2 🚨 After the James Talarico post blew up, I did a follow-up analysis on the MAGA influencer sphere on Twitter. I adjusted the last chart to fit the new data, and came up with what I'm calling a “Music Drop visualization” to show something I only briefly covered last time. Repost bots. In this post, you can see some of the biggest accounts outside Elon Musk, are MAGA “influencers” who are very high traffic on twitter, but don’t have much reach beyond it. xitter.cf/datboislendie/status/2… credit: slendie (@DatBoiSlendie) A small number of accounts drive an incredible amount of traffic with fairly crude bot networks as I will show. Over Oct 11 and 12, 294 accounts posted 1,575 word-for-word copies of just seven MAGA accounts. 134 of them copied Eric Daugherty 960 times, and every one of his 121 posts got copied. The busiest copier posted 141 copies in two days. All of these dots falling off the top line are mostly word for word copies of the original, and a smaller amount within 10% variance. This is nearly, if not 100% manufactured, and it works very well. To pour some cold water on another theory that's been going around, I've also seen NO drop in post volume I could pin on the Russian data centres being hit. That's only from what I've seen on Twitter and on the topics I looked at, I can't speak for reddit or other topics outside maga. However, I think there is ANOTHER reason things feel different in the last few days. Algorithm changes. If I'm correct, algorithm changes explain more of the posting patterns and feed changes people have noticed or felt. Including what may have changed, and what to watch for from the MAGA accounts in the next month. More on that below. For now, enjoy (headphones recommended).

i hate to be the one to say this, but taste won't be the moat it'll be the reputation, trust, and audience you've spent years building anyone can copy your work overnight they can't copy the years you spent making people care

“AI allows us to use the tools of physics, not just chemistry, more effectively in medicine. Basically nobody is investing in the former right now.”

Cheeky Pint is back! Mark Zuckerberg @finkd and Alexandr Wang @alexandr_wang came to the pub to discuss their new frontier model, Muse Wonder. 00:00:24 Muse’s breakout use cases 00:07:28 The model is the product 00:14:35 Muse Wonder 00:24:56 How frontier models are built 00:48:26 Betting $100B 01:07:21 Agentic commerce 01:19:34 OpenRouter 01:20:06 Beyond the smartphone 01:27:00 Funding 01:34:06 Why AI won’t be winner-take-all 01:40:46 Meta Superintelligence Labs (MSL) 02:08:11 Working for Mark Zuckerberg

Google DeepMind's Pushmeet Kohli says AlphaFold's useful structure predictions did not solve protein dynamics: "Proteins are extremely complex. They are disordered. Their shape might change depending on the context." "What we are trying to do is basically someone got a structure, deposited it in the PDB, and we are trying to replicate and get the same structure. That's what we did, right? And it just so happens that it's useful. But that does not mean that we have understood all of protein dynamics." "Let's not stop the funding of protein structure prediction and protein dynamics because we are just getting started." - Pushmeet Kohli, Google DeepMind, at Biohub, via Latent Space (@swyx)