Postdoc @Stanford | Evals, Agents & AI for Science
Palo Alto, CA
Joined June 2020
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Chen-Yang Su, PhD retweeted
⚡Iterating at lightning speed! Gemini 4 Carbon is SOTA across key benchmarks and combines frontier capabilities with deep safety & security research.
Chen-Yang Su, PhD retweeted
I did say we'd be releasing our models periodically...introducing Gemini 4 Carbon, our next frontier model.
Following Argon's release just two weeks ago, Carbon shows the pace at which we’re pushing the frontier, it ranks #1 on the recently updated v5.0 of @ArtificialAnlys Intelligence Index at 59. It also leads across key cybersecurity evaluations scoring 88.2% on SEC-bench Pro for finding vulnerabilities, 54.8% on ExploitGym for exploitation, and 71.0% on CWE-bench for patching.
We’re seeing significant improvements in long-horizon tasks even compared to Argon, and we’ve strengthened frontier safeguards.
As we did with Argon, we’re going to roll it out gradually + responsibly. Some trusted cyber defenders will get access starting this week. We'll be expanding it to more partners through our Fairwind Program, ahead of wider availability soon, so hang tight!
Chen-Yang Su, PhD retweeted
Walter Isaacson asks Peter Thiel what humans can uniquely do in the AI era.
Thiel: "We're very relational… these relational dimensions will become more important."
When knowledge is worth $0, the only career skills that matter:
- networking / social calibration
- persuasion (sales)
- curiosity (harnessing AI)
- taste (curation)
- storytelling
- grit
- golfing with clients (or equivalent)
We'll get so sick of a fake world that we'll go back to doing business like it's the 1800s. A handshake at the local saloon.
Chen-Yang Su, PhD retweeted
Over the past few months, Anthropic scientists have engaged in deep research partnerships with six organizations developing new medicines. We've also begun drug discovery efforts of our own.
In doing so, we’ve learned much more about how Claude can support the many stages of drug development.
In this blog post, we share some early results from these efforts, and describe how this work fits in with our wider ambitions in the life sciences.
anthropic.com/research/early…
Chen-Yang Su, PhD retweeted
The real 1-person billion-dollar company.
A solo smart, high-agency CEO + AI can have an outsized impact on the world.
Over the past few months, Anthropic scientists have engaged in deep research partnerships with six organizations developing new medicines. We've also begun drug discovery efforts of our own.
In doing so, we’ve learned much more about how Claude can support the many stages of drug development.
In this blog post, we share some early results from these efforts, and describe how this work fits in with our wider ambitions in the life sciences.
anthropic.com/research/early…
Chen-Yang Su, PhD retweeted
Axiom says its AI agents formalized a 15,000-page mathematical proof in just 24 days, largest proofs in mathematics.
Built by over 100 mathematicians across decades, the proof classifies the fundamental building blocks of finite symmetry.
With human guidance, the agents translated it into Lean, making every logical step computer-checkable and repairing errors along the way.
AI tackling an entire interconnected body of mathematics, with results others can verify. A major milestone.
We are witnessing history unfold. Again. Every day now.
Chen-Yang Su, PhD retweeted
2023: GPT-4 almost solved grade-school math
2024: IMO silver
2025: IMO gold
2026 May: Erdős unit-distance conjecture
2026 Sep: Navier–Stokes Millennium Prize Problem solved
2026 Oct: 722 AI-written math manuscripts
Today: OpenAI proves ETH is false
Tomorrow: P = NP?
Chen-Yang Su, PhD retweeted
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory).
AI starting to help us improve our understanding of the universe! openai.com/index/building-sc…
Chen-Yang Su, PhD retweeted
My quick takeaways on the Anthropic S-1:
1. This is a historical moment
2. $6.6M in revenue per employee!! Hard to even comprehend how good that is but Anthropic is AI native as it gets so makes sense.
3. I always thought OpenAI would drop their S-1 first
4. Customers spend about 9x more after a year. Net Revenue Retention is approximately 900% as of Sep 30, 2026. Good SaaS companies brag about 120%.
5. Cowork is growing faster than Claude Code did. Goes to show you the demand for consumer products. Duo will probably rip.
6. 3 years ago this company did $41M in revenue. In the first six months of 2026, it did $16.3 billion. I don't think anyone has a mental model for that curve yet, I sure don’t.
7. Nearly half of revenue comes through cloud marketplaces. About 48% comes from customers buying through them. Big companies buy where their budget already lives, and the lesson for founders selling to enterprises is to get listed where your buyers already spend.
8. Their run rate formula is published: the last 28 days of usage times 13, plus subscriptions times 12, which i guess is the new ARR math for founders?
9. It looks like They're merging Cowork into Claude dot au which tells you the chat box era is ending and the "go do the work for me" era is here.
10. Thousands of Anthropic employees are about to become liquid at once, so expect the biggest wave of new AI startups and angel checks San Francisco has ever seen. Reminds me when Facebook went public but this is way bigger.
Let’s go!
11. Buried in the filing, Anthropic says the gap between what Claude can do and how widely it's used is one of its biggest growth opportunities, so the company itself is telling you the models are ahead of the market and someone has to close that gap for dentists, landlords, and plumbers.
12. Whatever happens, exciting times to be building in AI.
Anthropic has filed an S-1 registration statement with the SEC related to its proposed IPO.
Read more: anthropic.com/news/s1-sec
Legal disclaimer: A registration statement relating to these securities has been filed with the SEC but has not yet become effective. These securities may not be sold, nor may offers to buy be accepted, prior to the time the registration statement becomes effective. This post does not constitute an offer to sell or the solicitation of an offer to buy these securities, nor shall there be any sale of these securities in any state or jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of any such state or jurisdiction.
Chen-Yang Su, PhD retweeted
GPT-6.1 Terra: delivering fast and capable computer use at a lower price.
GPT-6.1 Terra understands what’s on screen, takes action across apps, writes naturally, and is a more capable model for your whole workday with the efficiency to take on more of it.
🤖 Made with AI
Chen-Yang Su, PhD retweeted
I’ve left Anthropic after more than a year of working on Claude Code and seeing it scale larger than I ever imagined.
I have really loved working at Ant and believe deeply in the mission, and most of all, the idea of a race to the top.
The idea that if we work hard and responsibly, we can raise the bar and inspire others to great outcomes. And if we all push each other to be better, things can be radically good. I will carry the spirit of this with me forever.
My colleagues at Anthropic are the most talented, thoughtful, competent, and earnest people I have ever met. I am glad they are at the wheel and trust them deeply.
To the community on X, thank you for everything. You’ve made this the most fun (and sometimes stressful) job I’ve ever had.
For me, it is time for a bit of a break before diving into something new.
If you want more excellent Claude Code content, you should follow @addyosmani , @lydiahallie, @_catwu, @ClaudeDevs and of course @bcherny who started it all.
Chen-Yang Su, PhD retweeted
Introducing Kimi K3.1 Pro: our most capable 3T-class open-weight model.
🔹 1M-token context, 2.8T total / 104B active params (MoE), Multimodal.
🔹 Full-project coding: games in Unreal, Unity & Godot.
🔹 Excels at parametric 3D modeling in Blender & CAD.
🔹 More reliable at finance work: Accurate modeling with hallucination down by 65%.
🔹 Matching the strongest proprietary models across coding, agentic and knowledge benchmarks.
Kimi K3.1 Pro and K3.1 Pro Highspeed (2–3× faster) are now live on Kimi.ai, Kimi Work, Kimi Code, and the Kimi API.
Open weights by Nov 4, 2026.
🔗 API: platform.kimi.ai
🔗 Tech blog: kimi.ai/blog/kimi-k3-1-pro
Chen-Yang Su, PhD retweeted
Today, we're sharing a major milestone in our mission to democratize frontier AI development:
Pretraining at scale without a pretraining team.
We set out to answer an ambitious question: Can we significantly reduce the time, human expertise, and compute needed to pretrain a competitive foundation model from scratch?
The result is Mirendil-Base, our first pretrained coding model, built by one researcher in just 3.5 months with less than $10M in compute, including all research, experimentation, and the final training run.
Our approach is already showing promising results as we scale to even larger models.
This is an important step toward a future where a single researcher, empowered by AI, can accomplish what once required an entire research organization. As these capabilities improve, we believe frontier AI development can become accessible to far more people and teams.
More to come soon, including independent evaluations, post-training benchmarks, and API access.
Chen-Yang Su, PhD retweeted
this is amazing
1000s of AI agents compress months of biological analysis into just 32 minutes
OpenAI, PerturbAI and Scripps Research deployed 1000s of GPT‑Rosalind agents to analyze data from millions of mouse brain cells in 32 minutes, work researchers estimate would take humans months to a year.
They uncovered promising leads related to brain disease, including a potential link between cholesterol regulation and neurodegeneration.
“We build cell atlases so that other scientists can make discoveries we haven’t imagined yet. AI could help more researchers explore these resources and turn unexpected observations into new questions to test.”
These are testable hypotheses awaiting experiments, but the speed is extraordinary.
Chen-Yang Su, PhD retweeted
New from @arcinstitute: using the latent space representation of genomes from single-cell life to find new candidate functional RNAs.
I think this is cool because: (1) it uses deep learning and model interpretability to productive ends on a totally different kind of "knowledge"; (2) it shows how agents may be able to accelerate discovery in vast combinatoric spaces; and (3) it's an example of the synergy we'll hopefully see in the coming years between computational techniques and wet lab biology.
Delighted to share a landmark preprint from our lab, using genome language models and AI agents for biological discovery and genome mining!
The stretches of DNA between protein-coding genes are often called the genome’s “dark matter,” but they are far from empty. They encode RNA molecules that sense metabolites, regulate genes, and control some of molecular biology's most important tools (such as programmable genome editors e.g. CRISPR/bridge)
Much of this biology is unexplored. One reason is that RNAs can retain similar structures and functions even as their DNA sequences change dramatically, making their relationships difficult to recognize with conventional computational tools
Chen-Yang Su, PhD retweeted
It's pretty bad out there (cyberattacks).
People complain about AI writing slop code. But our software and internet infra run on 50 years of human-written slop.
Even dumb AI models today are becoming powerful hacking tools.
The race is on: defenders need to find and patch the bugs using AI before attackers find them.
Chen-Yang Su, PhD retweeted
that is not even his most impressive feat, this is:
youtube.com/shorts/j2AwScMSr…
Chen-Yang Su, PhD retweeted
Hackers reportedly used Claude and Grok to automate attacks targeting over 400 banks and other financial targets in Latin America. Via the information
In one of the first documented cases of its kind, AI agents appear to have stolen data and accessed bank accounts with little human input.
This makes attacks much easier to scale, potentially overwhelming defenders. I guess this is just the beginning
