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Thrilled to announce Dimension III, a fresh $800M fund which takes the firm up to $1.6B AUM.
Even since we launched the firm a few years ago, the overlapping exponential curves of science, AI, infrastructure, and hardware have continued to scale at staggering rates. We are more certain than ever that a research-led, long-term oriented investment practice is the right capital partner to ambitious founders in this era. If you are building something technically ambitious and possibly a little crazy, you are in good company here.
While the fund, our team, and our ambitions continue to grow, we remain steadfast on our mission to partner with founders building at the frontiers of science and compute.
Excited for the future ahead, let’s go build it!
Nan Li retweeted
Today, in collaboration with Anthropic, we’re excited to share rapid initial progress towards an antibody treatment for food allergy, which affects over 200 million people worldwide, discovered with the help of Claude.
At Divergence Labs, we believe that AI can unlock the next generation of antibody therapeutics with more effective mechanisms than before. Such mechanisms are urgently needed in food allergy, which involve overcoming one of the tightest affinity protein pairs in immunology, IgE and its receptor FcεRI, on mast cells.
Treatment with Xolair—the only approved antibody for food allergy—sequesters circulating IgE, but mast cells remain sensitized for weeks to months due to the extraordinarily slow dissociation of IgE from FcεRI.
We envision a treatment that actively pulls IgE off of FcεRI, without waiting for natural dissociation. Like picking a lock, this requires the right combination of geometry and force.
Our research team, working with Claude, ideated on mechanisms to accomplish this disruption, and converged on an antibody format with two arms with different functions and epitopes. Within one month, we designed, synthesized, and experimentally confirmed the biophysical function of the two arms, which we are now assembling into full therapeutic formats.
Nan Li retweeted
So pumped to share our third volume of the @_DimensionCap Research magazine!
These articles were enjoyable to write alongside my research colleagues @SimonDBarnett and @bauer_lesavage
In this volume, we dive deep into the foundations and applications of AI models, from pre-training, post-training, and agentic use to the emerging bio data market.
This volume also features my first research article on applying autoresearch for training machine learning models to predict protein thermostability. I assessed how frontier models approach hyperparameter tuning and discussed how such an approach can be synergistic with traditional Bayesian optimization sweeping and expert-guided search.
Since the article’s publication in April, we have seen a tremendous amount of progress in recursive self-improvement for closed-loop scientific discovery, and this is only the beginning!
Our goal here is to present these broad topics in a rigorous yet accessible manner for everyone, no matter if you’re a frontier ML researcher or a weekend biotech warrior. We very much hope you enjoy!
Nan Li retweeted
Excited to share our third volume of the @_DimensionCap Research magazine!
These articles were a blast to write with my research colleagues @SimonDBarnett and @ChemVagabond, and I feel so lucky to get to brainstorm, debate, learn, and write about these topics alongside them both on a daily basis.
You’ll probably notice a theme to a lot of these articles that we have written throughout 2026: the chronicles of us diving head first into AI model training, the data needed to feed them, and emergent applications of training at the frontier.
One of my favorite articles I wrote this year was centered around the bio data market and why biological training data has such unique considerations compared to text data. Since I published this one back in June, the demand for high-quality, therapeutic-relevant bio data has become even more obvious, and I don’t see this demand slowing down. The impact that AI is and is going to have in bio is becoming increasingly apparent every day, and we can’t get there without the right datasets.
Our goal here is to make these topics accessible and interesting to all, no matter if you’re a frontier ML researcher doing this work daily or brand new to the space and just trying to get a sense of it all. We very much hope you enjoy!
Nan Li retweeted
That's a wrap! Today, we're (@_DimensionCap) releasing the third volume of our Research Magazine.
Before anything else, I want to shout out my tremendous research colleagues Bauer (@bauer_lesavage) and Frank (@ChemVagabond), who were both core contributors to this volume.
We're also releasing a digital version:
dimensioncap.com/research-ma…
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Compared to previous magazines, our third work is more heavily focused on machine learning. That's by design.
Dimension invests in all companies, small and large, spanning the continuum from compute to the life sciences. At our core, we love technical teams working on the hardest, most important problems.
That means data center infrastructure, new networking protocols, new silicon, inference optimization, physical AI, lean/tech-enabled biotechs, data generation, and more.
As such, we challenged ourselves to go deeper into the compute stack than ever before, and how it connects to various branches of science. This magazine is a small sliver of the proverbial 'research exhaust' that our team generates over the course of a few quarters.
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One piece I want to highlight is Without Form and Void, which was my attempt at unifying my background in fluid mechanics, my admiration of clever inductive biases in ML, and a major industry chokepoint seldom talked about in CS circles, which is bioprocess scaling.
It's also the first piece I've tried writing with this much history (back to Galileo).
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We hope you like Vol. 3 and we can't wait to show you all what's in store in Vol. 4!
Excellent read covering the underlying theme of surface receptor mapping that has been behind recent Pharma success stories.
Outside of the tremendous pace of progress in AI, scaled molecular interrogation and experimental precision continue to play a massive role in scientific progress in biotech. Written by the one and only @ChemVagabond!
Nan Li retweeted
At the start of this year, @joshim5 told me 2026 would be the "year of deployment" for @chaidiscovery
That wasn't just an aspiration — Chai has now signed its 6th pharma deal in the past 9 months:
Lilly
Pfizer
Novartis
argenx
BMS
and now with GSK:
endpoints.news/chai-discover…
Nan Li retweeted
Folding models, protein diffusion, single-cell LLMs, and agent swarms: AI for science runs on a different model every hour and needs a different number of GPUs every day.
Listen to leaders in computational biology from @GSK, @AnthropicAI, and @achira_ai on the main stage at Runtime.
Excited to announce our partnership with @rgrchen, @amlakhan and the team at @onyxbio!
We believe that precision immunology is one of the most interesting directions of new medicines and that multi-modal, longitudinal datasets from real patients are needed to power this field.
Onyx is building a unified data platform for immunology - combining clinical records, multi-omics, sample banking, and patient reported outcomes. This platform helps researchers to understand how immune diseases progress, why patients respond differently to treatment, and uncover new ideas for medicines. At the limit, these data will power the buildout of a entirely virtual immune model to simulate human immunology with high precision.
We have known Roger for over a decade and are excited to reunite! Nearly a thousand patients are already enrolled onto the platform and looking forward to much more to come!
onyx.bio/
Excited to announce @_DimensionCap's partnership with @WKightlinger and the team at Ridge Bio to develop next-generation conjugate medicines!
Ridge has built a computational enzyme design model to create custom conjugation and linker systems. Payload stability and programmatic release are two important levers in conjugate drugs, and Ridge has shown compelling data in both of these areas.
Ridge's portfolio of enzymes and linkers are both compatible with existing ADCs and unlocks entirely new programs directed towards novel targets. Excited for the journey ahead and much more to come.
ridgebio.com/
What a year for the team at Chai! Congrats on the string of top Pharma partnerships
Frontier drug discovery programs require frontier capabilities. Today, we’re excited to share that BMS will be using Chai’s models to support the discovery of new therapeutics. Since rolling out Chai-3 to partners at the start of this year, we’ve partnered with @EliLillyandCo, @Novartis, @Pfizer, @argenxglobal, and now @BMSnews. Many of the world’s leading biopharma companies are now using our models to go after diseases.
Scientific discovery is the domain where access to frontier AI matters the most. At @ChaiDiscovery, we’ve seen first hand how our latest model generations can make the difference between discovering a molecule and not. We’re excited to work with @BMSnews to break new ground in medicine and science.
Nan Li retweeted
Frontier drug discovery programs require frontier capabilities. Today, we’re excited to share that BMS will be using Chai’s models to support the discovery of new therapeutics. Since rolling out Chai-3 to partners at the start of this year, we’ve partnered with @EliLillyandCo, @Novartis, @Pfizer, @argenxglobal, and now @BMSnews. Many of the world’s leading biopharma companies are now using our models to go after diseases.
Scientific discovery is the domain where access to frontier AI matters the most. At @ChaiDiscovery, we’ve seen first hand how our latest model generations can make the difference between discovering a molecule and not. We’re excited to work with @BMSnews to break new ground in medicine and science.
Nan Li retweeted
we believe biology is AI's true frontier edge case
today we're it's launching the capital map: the top VCs in AI x Bio
The TechBio 50
Congrats on the AX Cloud launch @514hq! Run agent simulations for any product at scale. Managed infra, observability and traces.
Agents are your new users. Learn from them.
AX Cloud is now in research preview: managed infra, agents and data for experimenting with coding agents as users.
Run unbiased simulations of coding agents at scale. This allows you to understand how agents discover and use products. Yours, your partners' and your competition's. Use this to optimize your product, craft go-to-market materials or develop your technical partnerships.
Get started for free on managed infrastructure, then upgrade when you're ready to parallelize at massive scale. Every run starts from a fresh sandbox. No bias. No context pollution. No cheating.
Run your first experiment in minutes: docs.514.ax/getting-started
Nan Li retweeted
Agents are your new users. Learn from them.
AX Cloud is now in research preview: managed infra, agents and data for experimenting with coding agents as users.
Run unbiased simulations of coding agents at scale. This allows you to understand how agents discover and use products. Yours, your partners' and your competition's. Use this to optimize your product, craft go-to-market materials or develop your technical partnerships.
Get started for free on managed infrastructure, then upgrade when you're ready to parallelize at massive scale. Every run starts from a fresh sandbox. No bias. No context pollution. No cheating.
Run your first experiment in minutes: docs.514.ax/getting-started
Amazing opportunity to work with the best in the biz! And learn film photography on the side
We continue to expand our investment team across deep/frontier tech investing @CompoundVC .
I am biased but think it's an n of 1 opportunity to help build and grow a firm with the right amount of capital to be top 5% in the world, a unique investing mandate across early-stage venture + public equities, a high amount of autonomy, and an obsession with the craft of investing and life.
DM me if you're curious.
Nan Li retweeted
I've joined @_DimensionCap as an operating partner.
I'll be building cool stuff with people I love and trust.
Here's a bit more about what I'll be doing and why I chose to join this incredible team for this season of my career.
linkedin.com/pulse/climbing-…
Welcome to the team @RecursionChris!! It is an honor to partner once again and I know you will be an amazing resource for Dimension and the founders we work with.
Exclusive: Founding Recursion CEO @RecursionChris is now an operating partner at @_DimensionCap, a life sci + computation VC firm fresh off an $800M third fund
@endpts spoke w/Chris + @zavaindar about the move:
endpoints.news/exclusive-for…
Nan Li retweeted
joining @_DimensionCap was just an elaborate ploy to infiltrate @Getthecheckpod and become their intern
@anikamirzaa @priya_kamdar @mayamshahh
.@nikhilvnamburi went from tracking down the investment fund behind his college scholarship to a 5 person investment team that manages $1.65B @_DimensionCap
They just announced an $800M Fund III. They’ve backed @AnthropicAI, @modal, and @chaidiscovery
We sat down to talk about:
> Why only 1-2 investors matter at every fund (except Dimension)
> If the Coefficient Bio @AnthropicAI acquisition returned fund II
> Why hyper-concentration freaks out normal VCs but excites him
If you watch till the end he flips the interview on us (first time a guest has ever done that!)
00:00 Dimension raises $800M Fund III
06:29 The unexpected way Nikhil found venture as an engineer
08:48 Who are the LPs behind huge venture funds
11:04 Why Dimension only has 5 investors
13:14 Coefficient returned the fund?
14:49 They predicted bio would be big
16:34 Does Nikhil believe in AGI
17:20 Does Nikhil believe in looksmaxxing
20:10 Hot take on if SF VCs are smart
21:53 How to break into VC
22:52 Why only 1-2 investors matter at each fund
23:35 Churn and burn in the junior VC role
34:50 His viral quant thesis
42:11 Nikhil interviews us...
46:45 Biggest recession indicator
53:24 Nikhil is the podcast’s most eligible guy friend?!
