RIP Scott, one of the brilliant. 68 is far too young, wish you could have seen how far we'll go.

Hey @wired.com , as a umm...tech magazine, it would be wise to acknowledge your data breach ;) www.brightdefense.com/news/wired-b... Can confirm - my alias email was in the dump (notified today by a third party), and it was only used for Wired since a couple months ago.

Types of economic models: 1. Discriminative (distill a couple variables for a simple decision boundary, model-based) 2. Generative (distill a generative process for more complicated model, model-based)

Is something unique interesting or small? A fundamental fork that leads to a large difference in how we think about value.

Turbulence in the confused middle is now a constant feature of the new plotline (smaller variance models ftw). But you can really feel when the right plot clicks in.

Seems like it compiles and runs now. Nifty. A friend said tonight, "Thanks!" I said, "but I haven't done anything yet." "No, but you gave me hope."

Finally. While we were all looking at AI, USDC on Solana became a credible tradbank replacement. 1-2 min, $0.50 (eth) -> ~15s, <$0.01 (sol) NB: Transactions visible on chain (obv) and easy to fat-finger funds to the wrong chain (not ready for grandma yet), but still, for geeks, it just works.

Longevity metrics: Rather than talking about expected lifespan, it's probably more intuitive/useful to think about marginal cost to extend lifespan by one year. Right now, it's cheap in early age, much more expensive in old age. If we invest together, the cost will get much cheaper in the future.

Have a 10-year bet running now to never read a newsfeed in person again (using AI summarizers to stay informed and newsfeed-blocking extensions/UI hacks to enforce). Doable now, increasingly efficient over time.

Newsfeeds are probably dead (for human consumption). Replaced them with AI summaries for ~a month (scheduling utilities/async flows like Lutra/OAI helpful here). Same events, but the world feels calmer/contextualized, like reading an investor newsletter. End of an era, probably for the better.

Would be neat to see a leaderboard re: implicitly personalized AIs (those with memory-based adaptation methods) on common benchmarks? Pre-training still the biggest factor of AI intelligence by far, but how much does implicit prompting (via memory) change the intelligence between users?

Why do biotechs fail? TL;DR - scale matters, hedging matters, efficiency of a trial matters. Often the science fails first, leading to cascading management/funding failures. A lot of knobs here that can be tweaked (some obvious, others less obvious). www.librariesforthefuture.bio/p/why-do-bio...

Re: AI markets, would much rather see new markets for new asset classes and geos, rather than new markets for new actors (AI agents, humans w/ AI tools). Even with algos running 75% of trades in the market now, few markets have been created only *for algos.*

Typically, new ideas come from (different) fringes of the network where diverse threads start to intersect, then travel towards the center to get power (but may pick up competitors in the process).

For how similar they are in world models, VC and founders diverge quite a lot in actions. VC - horizontal, power accumulation, knows everyone. Founder - vertical, deep, iterates, knows users, team and funders. Growthco - horizontal x vertical (a la OpenAI/Google/Alibaba).

Hedging: $, portfolio, iteration, expertise, (sometimes) specialized contracts. Key insight into founders is how they react uncertainty - when you encounter uncertainty, do you raise more to hedge (portfolio hedge), or do you raise less, think more (expertise hedge)?

The Internet right now looks like a global market on the surface (anyone can read!), but it's actually a bunch of local markets disconnected from each other, unless you're already shipping at scale. What are your short growth paths to resource and user communities?

1. The economic value of prediction scales with your (real) action space. 2. What you predict about the world also depends on your (simulated) action space. Explains a lot about value systems in the modern, hyper-scale world vs. the 150-person village.

The line between investment and cognitive labor is starting to get a bit blurry. Using AI agents to do work directly, yielding $, is not that different from investing money in another human verifier to do the same thing, except ownership fraction and control (which does, of course, matter).

High-variance techs often lead to a multimodal future (not necessarily, but often).

If you can with >70% confidence, build the vertically integrated thing (definitely optimistic). Otherwise, build the personal tools that upgrade the tech era, which makes the vertically integrated thing possible, and be more indefinitely optimistic.

Arguably enough money earmarked for AI companies now that we can start talking about momentum vs. fundamental strategies in VC. True for the AI labor markets too. The music will probably stop for some big names in 1-2 years in dramatic ways, but the winners do have 10x-100x growth left.

Re-posting from Engage Bio (personal portfolio) Exciting news from Engage Bio! We’re proud to announce that the Cystic Fibrosis Foundation has made an equity investment in Engage to support development of durable, non-viral genetic medicines for cystic fibrosis.

Objectively valuable milestones - a conversation that comes up again and again in hardtech. Hardtech cos/intrinsically motivated scientists often have complex intermediate goals and unique theory. The market, though, is (on average), not enlightened and not patient. youtu.be/aG8_AeiwDPA?...

Investment learnings from the last few years: 1. Contrastive distillation works better than most theories as a model of reasoning and writing. It's simple, it scales. 2. But data/experience increases precision. Hang out near the reefs. PhD-led startups with good coaches do unreasonably well.

Only 24 hours in a day - focusing on flow with portcos and family matters more than one might think.

Scientists we co-fund at @CambridgeUni.Bsky.Social have developed an algorithm that could pave the way for more personalised cancer treatments! It can pinpoint patterns of mutation in cancer cells and could help identify the patients who could benefit most from immunotherapy. Read more 👇

This is probably right: www.economist.com/finance-and-...

www.linkedin.com/posts/ruairi... Starting tomorrow - drop by if you're in Tokyo!

Naive, high-level take on aging - we understand some of the key variables, but not yet the regulatory dynamics. You need these for precise control (and therapeutics that pass clinical trials).

IC 410 is located 12,000 lightyears from Earth in the Auriga constellation, and is nicknamed the Tadpole Nebula because of the tadpole-shaped clouds of dark dust that appear to be swimming towards the centre. #astrophotography . I took this last night with HA,S2 and O3 filters.

Strong agree: www.cnn.com/2025/03/24/b...

Not just stocks or valuation - strong fundamentals. www.reuters.com/markets/asia...

RNA xkcd.com/3056

赞： arxiv.org/pdf/2501.12948

Exciting to support these bio x ML AI collabs which are creative and broadly beneficial: www.technologyreview.com/2025/01/17/1...

It replicates: www.biorxiv.org/content/10.1...

Regulatory genomics is highly underinvested. May unlock cures to aging within reasonable timespans, starting to get dense predictive data (w/ single-cell datasets), contrastive distillation can help in sorting the information dynamics out. All quite early, but promising.

Design for Democracy - useful frames on AI and society from Prof. Alex (Sandy) Pentland: youtu.be/fypgHxmfapg?...

A little bit of action makes up for a lot of learning.

Lo-fi molecular dynamics

Will tech eat politics or politics eat tech? 2000s were definite tech wins (as politicians both didn't care and didn't know how to control tech), while 2020s have been politics ascendant, although not outright dominant yet.

It's clear at this point that it's the *right* startup teams in combination with scaling from the right trad value systems who are going to save the world from some pretty gnarly, fast-moving problems, but we have like 10 different crises to deal with simultaneously. Oi.

Horizontally-integrated, loosely integrated economies generally optimize for creativity, vertically integrated structures optimize for war and building big things (protected supply chains, etc.)

2013 was the year that the gangs of scammers discovered that they could run them on the Internet. A lot of the current problems (now gone metastatic) trace back to then.

The AI -> AGI -> ASI ordering was always a fictional story spun up in some sci-fi blogs, a long time ago. Treating it as anything other than a fictional tech tree is a mistake in ML comms (especially "the arrival of AGI", which is referenced so often in forums like r/singularity).

Hiring checklist. Ignoring the brand: 1. Do you have the skills/experience? 2. Can you learn quickly? 3. Are you aligned with values (short and long-term)? The challenge, however, is that assessing these often requires more data than an interview, at least several weeks if not months.

Without money, your action space is limited by the min(predictive abilities of those in your community), from which values are derived. With money (and the will and skill to create a value system), it can expand to max(predictive abilities). Huge difference.