Co-founder & CEO of Discovery Loop. Former Chief Scientist, Google. Helped build many Google products, TPUs, Gemini, TensorFlow, MapReduce, Bigtable, ...
Joined September 2017
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In April, '17, @jsomers of @NewYorker reached out & said he wanted to do a small profile of me & my longtime colleague Sanjay Ghemawat, watch us work for a few hours, maybe dinner, etc.
It came out today. I think it captures our working style really well. newyorker.com/magazine/2018/…
Jeff Dean retweeted
I launched the first image and video generation models at Google, and kept asking why all AI designs look the same.
AI has brought us the WORST era of design.
It made content creation effortless, but it also made 90% of it look painfully generic.
My co-founder and I spent 2 years building in stealth to change that.
Meet Vyb, the first AI design model that understands your taste like a designer would.
RT + comment your website URL and we’ll make your first design.
Jeff Dean retweeted
Cancer patients with the same diagnosis often have very different tumor biology.
Molecular testing can reveal underlying differences, but that's slow and expensive.
Introducing Holon-S1, our platform to predict genes and biomarkers from routine pathology slides.
• beats two other models at predicting spatial gene activity in a controlled comparison
• has identified potentially novel biomarkers in breast cancer and colon cancer
• evaluated across 16 organ types and more than 15 scanners, using slides from both formalin-fixed, paraffin-embedded and fresh-frozen tissue.
We believe Holon-S1 has the potential to help researchers find new biomarkers in slides they already have, discover treatment targets, and bring more personalized cancer care within reach!
Have a glimpse at this! Nice work, @AndrewDai and Elorian folks!
Jeff Dean retweeted
My AI security research lab AISLE discovered 500+ zero-days with CVEs across 100+ codebases in a year => ~1% of 2026's open-source CVEs globally from a single team! On hardened codebases like curl, we've repeatedly matched or outperformed frontier AI labs in zero-day discovery
I've been a personal supporter (through our family foundation) of @Khipu_AI & @DeepIndaba, which are fantastic events for AI researchers in Africa and South America. I've encouraged Google to support these in the past. Discovery Loop (@DiscoLoopAI) is thrilled to support!
For the last 10 years we've been raising funds to bring AI to Africa (@DeepIndaba) and South America (@Khipu_AI). The efforts have been very successful, but this year we are finding it hard to raise money. If you work for an AI company, please share the following with the right team to support us. Thank you!
About KHIPU 2027
What it is: KHIPU AI (khipu.ai) is a non-profit organization dedicated to advancing AI talent, research, and community across Latin America. Alongside year-round regional initiatives, we host a biennial in-person gathering rotating across the continent, previously in Uruguay (2019, 2023) and Chile (2025).
Next Edition: April 5–9, 2027, in São Paulo, Brazil, hosted at the Universidade de São Paulo (USP), one of Latin America's leading research universities.
Watch our 2-minute video: youtube.com/watch?v=Db19zoqu… (hear directly from past speakers, including Nando, and Latin American students on how KHIPU grew from a single gathering into a regional AI movement).
Who Attends & Why Support - Engaging with the region's top talent and lab leaders: We bring together around 500 participants, including leading faculty and lab directors from across Latin America alongside a curated cohort of ~300 graduate students and industry researchers selected from over 1,000 applicants. As the local AI ecosystem grows rapidly, KHIPU offers a rare opportunity to engage directly with these emerging researchers and regional leaders in one place, helping shape research priorities and the safety mindset across Latin America while connecting with talent and perspectives outside Silicon Valley.
100% free attendance & student grants: Attendance is completely free for all selected students, professors, and researchers. Sponsorship funding goes directly toward travel and accommodation grants for students and faculty across Latin America who otherwise could not afford to attend.
Community & Track Record: Past editions have featured speakers such as @Yoshua_Bengio , @JeffDean , @jpineau1 , and @NandoDF (2025 lineup: khipu.ai/khipu2025/speakers-…), and have been supported by the Hopper-Dean Foundation, @GoogleDeepMind , @Apple , @Microsoft , @Meta, @cohere , and @MistralAI . For 2027, @OriolVinyalsML and @sarahookr are already confirmed.
2027 Sponsorship Prospectus: Attached (also available at khipu.ai/prospectus-2027)
Contact: @FortunatoMeire ([email protected]) & KHIPU Sponsorship Committee ([email protected])
Jeff Dean retweeted
Introducing DeepRSI, a new industry standard for measuring recursive self-improvement.
On preexisting benchmarks, tasks are contributor-based and short-horizon (~12 hrs). In DeepRSI, we push agents to work 48 hours on ML tasks actually derived from ongoing proprietary research.
Jeff Dean retweeted
Wrapping up my first month at @DiscoLoopAI (am on leave from @PrincetonCS and @PrincetonPLI ). Excited to work on using AI to accelerate scientific discovery and solve important problems. My first startup experience, and with an incredible set of colleagues!
Announcing Discovery Loop!
I am very excited to announce that, along with my longtime friends and collaborators @Sanjay_Ghemawat, @OriolVinyalsML and @quocleix, we are founding Discovery Loop (@DiscoLoopAI), a Public Benefit Corporation whose mission is to automate machine learning, science, and engineering to accelerate discoveries and progress. The four of us have worked together for 14 to 30 years, and have helped build some of the world’s most used products, infrastructure and AI models, and we’re excited to turn our attention to this ambitious endeavor.
♾
Learn more at: discoveryloop.com
Jeff Dean retweeted
We’re sharing new results showing that frontier AI models are able to outperform human experts on financial predictions for the first time. We built an environment for the challenging task of Earnings Predictions, finding that the most recent frontier models (Opus 5.5, Fable 5.1, Astra) with Samaya’s harness, meaningfully outperform expert consensus predictions on commonly reported earnings metrics such as company revenue, gross margin and more.
We built this environment to have a “point-in-time” gate in the harness to ensure no information leakage, and created financial retrieval and data tools that would respect this gate and give the models access to the same information available to experts. We also adjusted for bias in expert consensus to create a hard, bias-corrected baseline, where outperformance has real signal. Only the most recent frontier AI models are able to beat this hard baseline, pointing to an important inflection point in AI capabilities in finance.
Like with FrontierFinance, we see substantial headroom for further RL training in this environment — the models show large variations in error across different rollouts. We’re continuing research on using earnings prediction and other predictive tasks to post-train models to learn from their mistakes. Get in touch if you’d like to collaborate or try out an alpha version. Link to the full research below.
Jeff Dean retweeted
Proud to share that @phinity_ai is coming out of stealth today, announcing our seed fundraise and that we’ve reached 8-figures in annualized run rate.
Chip design has been stuck in the 20th century for far too long. Now, for the first time in decades, a unique set of emerging factors is making it possible to fundamentally reinvent how chips are designed.
At Phinity, we’re building toward fully autonomous chip design, with the goal of enabling custom silicon for thousands of emerging AI applications. Our team combines hardware experts, AI researchers, and infrastructure/EDA engineers to define a new way to design chips.
We’re extremely grateful to @uncorkcap for leading our $5.2M seed, to @MoxxieVentures and angels including @JeffDean for joining the round, and to @pearvc for leading our pre-seed and backing us from the start.
We’ve worked so, so hard to make this happen, and I’m proud to share our work publicly for the first time!
You can read more about the announcement below. phinity.ai/blog/introducing-…
We’re hiring for ops and engineering roles. If you want to help build the future of chip design with us or are interested in learning more/partnering, please reach out to me or @sonyashijin .
Jeff Dean retweeted
Excited to finally share that @phinity_ai is now out of stealth! We're announcing our seed fundraise and that we’ve reached 8-figures in annualized run rate.
We’re already working with some of the largest foundation model labs. Our mission is to build fully autonomous chip design so AI can help us search beyond the limits of human engineering and discover computational systems we would never find on our own.
We’re fortunate to have the support of @uncorkcap, which led our $5.2M seed round, with participation from @Moxxie including @JeffDean, following our pre-seed led by @pearvc!
It’s been an amazing few months, and I couldn’t be more grateful for the opportunity to build the future of chip design with such a talented team.
You can read more about what we’re building and why in our full announcement. phinity.ai/blog/introducing-…
We’re hiring across all disciplines - if you’re interested in working with us, please reach out to me or @aadi_nash.
Very sorry to hear this news. 😥
I never had the chance to meet Margaret Hamilton, but her contributions to the flight software that got us to the moon are legendary. I love this image of her standing next to the printouts of the Apollo code.
We’ve lost an icon. Margaret Hamilton, a computer science pioneer best known for her work at MIT leading development of the flight software for the Apollo missions to the moon, has died at 90. Read about her legacy via MIT News: news.mit.edu/2026/margaret-h…
ALT Margaret Hamilton is reclined inside a NASA spacecraft module, surrounded by control panels and switches.
Jeff Dean retweeted
We are excited to announce a new faculty position in AI for Biology at UC Berkeley, jointly between @Berkeley_EECS and @CCBBerkeley.
Please repost & share this opportunity with outstanding early-career researchers in your networks.
Apply by Nov 9, 2026: aprecruit.berkeley.edu/JPF05…
The safety data for Waymo gets better and better.
Comparison w/ human drivers on rate of crashes with serious injury:
Latest data: 270M miles, 20X better
Mar 2026: 170M miles, 13X better
Before that (forget exactly when): 10X better
270M+ miles. 841 fewer injury-causing crashes.
Our latest safety data shows the Waymo Driver continues to make roads safer for everyone.
Compared to human drivers across 5 territories, it reduced:
📉 Injury crashes by 82%
📉 Serious injury crashes by 95%
Full data: waymo.com/safety/impact
This was recorded a few months ago when I was still at Google and it was a really fun conversation!
How does this only have 21,000 views in 8 days?
Chat with @JeffDean (then Google) and Bill Jia about large scale AI models.
youtu.be/BVQSWeK2Nrw?si=MvMX…
Did you know you can learn interesting things from computations in real rat neurons? I love what @AlexKsendzovsky and team are doing at @BioComputingCo are doing.
Jeff Dean retweeted
Luiz André Barroso’s work influenced me a lot in how I think about systems, and even about my career.
I decided to write about his work with @JeffDean on some topics that interest me a lot: tail latency and the systems behind the modern internet. andreybleme.com/2026-09-22/l…
Thanks for the great discussion, @dawnsongtweets!
I had the great honor and pleasure of sitting down with @JeffDean for his first public talk since leaving Google, where he spent an extraordinary 27 years.
Few people have shaped modern computing and AI as profoundly - from MapReduce and Bigtable to TensorFlow, Mixture-of-Experts, TPUs, and Gemini.
Our conversation covered some of the biggest questions shaping the future of AI:
• How do you recognize a foundational idea before everyone else does?
• How do you choose a research problem worth spending 5 years on?
• What can coding teach us about building better reasoning models?
• What might recursive self-improvement (RSI) actually look like?
• What happens when the scientific discovery loop itself becomes increasingly automated? (and how is Jeff’s new startup going to contribute in this space?)
• As AI becomes increasingly autonomous, how do we keep it safe and secure?
• What should the next generation of researchers be working on?
Here are some key insights and highlights for anyone building the future of AI. 🧵1/8
