NewLimit paper just dropped @icmlconf showing our SOTA AI models can predict perturbed cell states. Helps to have the largest primary cell perturbation dataset in the world. Bonus points for one of the first demonstration of active learning in bio.

Using brainwaves to: ✔️ Play Call of Duty ✔️ Control robotic hands ✔️ Have a neural Mario Kart party ✔️ Regain one’s own natural voice       (+ more on eng and master plan) Hope you enjoy our update!

There are four horsemen of Foundation Models and only one is publicly listed. SEC has decided the revolution will not be ownable.

The capabilities compound. Software creation costs -> zero.

We’ve raised a $130 million Series B led by @kleinerperkins alongside new investors @natfriedman/@danielgross , @vkhosla, and @humancapital — joined by existing investors @foundersfund , @_DimensionCap, and @brian_armstrong (yes, the cofounders are doubling down). We also raised from some of the best angels who have supported the company over the first two years including @eladgil , @garrytan , @collision, @patrickc, @JoshuaKushner, @JTLonsdale, and @FEhrsam . NewLimit is building medicines to treat aging, the meta driver of nearly every major human disease. Once thought to be irreversible, the emerging science of epigenetic reprogramming has shown that aging is in fact malleable. This presents a therapeutic opportunity that is 100X larger than any biotech product that has come before. Our bet is that this combination of AI and scaled genomics can unlock medicines that give each of us more healthy years. We're deeply appreciative of investors who share our vision that addressing aging biology represents one of the most consequential projects of humanity.

.@newlimit is building medicines that target aging itself—not just individual diseases. Their approach is elegant and deeply technical: run the largest epigenetic reprogramming experiments and use the data to train frontier AI models. Proud to lead their Series B and back @brian_armstrong, @byersblake, @jacobkimmel, and Cathy O’Hare on this mission. Interested in joining their talented team on the journey? They’re hiring:

No code software creation is real.

A couple years ago @FEhrsam started talking to me about focused ultrasound for modulating the brain. I was initially too bandwidth pilled to see the near term opportunity. Over time I realized the power of their approach - manipulating brain states at larger scale than single neuron resolution. There are many times we are close to making the right decision for ourselves and need a little bit of help. On the verge of falling asleep, but can't quite doze off. On the verge of going for the vegetables but order the deep dish pizza instead. There can be massive life gains through even a subtle *Nudge* of our brain state. I'm excited to be along for the journey, even in just my small way, and get to watch @FEhrsam, @quintinfrerichs and Jeremy Barenholtz build @Nudge. Overall, bio remains underrated because nearly every bio company founded today works on very small patient populations. @nudge, @neuralink, @newlimit and a small group of others are building a new class of bio company that is built to enhance *everyone* - which is literally 100-1000x the patient population of a typical biotech company. I expect we will see many many more companies like this over the coming decade as the playbook is written by those audacious enough to start and talented enough to be successful.

GLP1s have added $1T in market cap to Eli and Novo over the last 5 years. That's 3x+ the market cap created by all biopharma startups over the last 30 years combined. This is a bit of an indicment of the biotech startup ecosystem. There are many $1T and even $10T drugs to be invented, we just don't fund them. Through no one persons fault, the biotech industry is stuck in a local performance maxima. Faced with lower multiples than tech, biotech funds have to pitch something other than straight multiple to LPs and the only other level is faster liquidity. Biotech has been good at this, with the average age of biotech companies at IPO being 2 years younger than tech companies at IPO (~5.5 years vs 7.5 years). This means biotech funds need to back companies that can get to IPO within a few years. This requirement constrains the types of companies funded by bio funds to 'linear bet' plays (where you buy at some reasonable multiple based on current performance, etc). As any experienced venture fund manager will tell you, a portfolio of linear bets underperforms a portfolio of asymmetric bets. Double unfortunately, no one firm can break this model because no one firm is the sole backer of a company to profitability. You must rely on an ecosystem of capital partners. So if you are the one firm that strikes out and funds asymmetric companies, no one will show up to fund the company downstream and your whole portfolio will fail. For this reason, I think the biggest plays in bio over the coming decade will be mostly backed by generalist funds rather than bio funds. *Note this will perpetuate the trend of sector specific funds underperforming generalist funds (by industry and geo!).