"Moats" are the most BS thing in startups. No such thing exists when you start. Google, Apple, Meta can always "just build it". Defensibility is built in increments. Small, immensely focused teams outpace the biggest companies on earth. Investors, get over the moat obsession.

Google needs to buy Instinct, they need that product DNA, Notebook isn't going to cut it. Instinct, Muse, Grok Bot, etc., are social ai. I've seen this play out before... I was at Google+ for 3-months running mobile, I tried buy instagram but I was two steps down from Larry, so I didn't have the pull (Kevin had told me Zuck was sniffing around), my SVP said it was 'too expensive.'.. killed me. I bounced to Google Ventures.

Today @inductive_bio is launching Beacon-2, which can predict human dose directly from chemical structure. A dirty secret of AI for drug discovery is that most systems optimize the wrong reward, making them near useless in practice. Human dose is the right reward – it’s what every drug program is already optimizing. Making it computable will unlock the real-world impact of agentic drug discovery. Beacon-2 builds on our Beacon-1 models that beat 750+ competitors to win all three OpenADMET blind challenges. Whereas Beacon-1 provided a suite of models for individual molecular properties, Beacon-2 is a single system that predicts human dose end-to-end. It has three configurable modules: an ADMET-PK foundation model, a potency module that can use our fine-tunable co-folding affinity model or physics-based methods like FEP, and a PK/PD model with physiologically-informed mechanistic models of pharmacokinetics. We share validation results from Beacon-2 in a blog we are releasing today. We show that across 20 real-world drug programs running through Inductive, dose predictions from Beacon-2 agree with those from experimental data with a Spearman’s ρ of 0.61. And in a similar study on 325 publicly available compounds from the ExpansionRx OpenADMET competition, we show a Spearman ρ of 0.79. As a proof-of-concept, we gave Beacon-2 to Indy, our medicinal chemistry agent, which used it over 5 autonomous design cycles on a recently disclosed SARS-CoV-2 program to cut predicted human dose 17x, which can be the difference between a drug program that gets killed and that makes it to clinical trials. We compared the compounds that Indy designed using Beacon-2 against compounds from an optimization loop that used a potency-only reward function. The Beacon-2 compounds were favorable across three independent measures: they were preferred by chemists in blinded comparisons 87% of the time; were more druglike according to QED; and had a lower projected dose when computed by alternate methods relying on in vivo rat models and allometric scaling. Based on these encouraging results, we are now running prospective studies where compounds optimized by Beacon-2 will be validated in the lab. Read the full post here: inductive.bio/news/beacon-2 At Inductive, our long-term goal is to build superhuman chemical intelligence, and by completing the reward function for autonomous drug discovery, Beacon-2 is an exciting step toward that goal. Reach out if you’d like to get involved.

Heads up: On Thursday @jakek @eliblee and I are hosting an AMA and sneak peek at the redesigned format for Character Labs, including the new 5-day "Everything Week" in San Francisco. luma.com/3jhf9wde

Big news: Fathom is now part of @Superhuman! We’ve always believed the real value of meetings isn’t the notes – it’s what happens after. Joining Superhuman gives us the opportunity to bring meeting intelligence into more of the places where work gets done and take that vision much further. A big step toward what we’ve been building from the start: helping people show up at their best and move work forward. Read the full announcement: fathom.ai/superhuman

For about the 40th year in a row, we're being promised that the ultimate 'personal assistant' technology is around the corner. But is it? AI certainly helps, but we still feel very far from a killer use case, let alone product... spyglass.org/the-swiss-assis…