Google Fellow(VP) at Google, Professor at UT Austin, Machine Learning Researcher, Ex-VP/Distinguished Scientist at Amazon.
Joined March 2020
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This would also be a good time to congratulate @Devvrit_Khatri and @nileshgupta2797 who also recently obtained their PhDs. I am so glad to have served as their PhD advisor - all credit to them for becoming strong, independent and influential researchers. Congratulations!
Congrats @dvsaisurya on your successful defense! Its been a pleasure of my life to collaborate with you!
@inderjit_ml @cho_jui_hsieh @Devvrit_Khatri
Heartiest Congratulations to @dvsaisurya on the high quality work he did for his PhD, spanning optimizers, architecture and sample efficiency. It has been my pleasure to be his PhD advisor, and I am absolutely thrilled that he landed with the good folks in @coreauto.
Congrats @dvsaisurya on your successful defense! Its been a pleasure of my life to collaborate with you!
@inderjit_ml @cho_jui_hsieh @Devvrit_Khatri
Inderjit Dhillon 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!
Inderjit Dhillon retweeted
We pushed 10M of Google's EmbeddingGemma 2 vectors from ~30GB of RAM down to ~0.4GB
float32, 768 dims: ~30GB
1-bit TurboQuant: ~1GB (99% nDCG@10 kept)
+ MRL to 256 dims: ~0.4GB (94.5% kept with rescoring)
77x less RAM for a ~5% drop in quality! TurboQuant + MRL is magic 🪄
Matryoshka structure in the latest EmbeddingGemma model for on-device
Inderjit Dhillon retweeted
Lots of discussion out there about our next model(!), so I wanted to give an early look as soon as possible. Introducing Gemini 4 Argon!
It shows frontier performance in complex workflows, cyber defense and software engineering. Teams are using it extensively at Google, from coding to quantum computing, great feedback.
Here’s a look at the benchmarks:
Inderjit Dhillon retweeted
Take public transit, earn Waymo Cash! Introducing transit rewards 🚆💸
Available to our San Francisco Bay Area riders in the coming weeks.
Read more: waymo.com/blog/2026/09/trans…
Inderjit Dhillon retweeted
Introducing Gemini 3.8, our best reasoning & coding model yet.
By leveraging long-running agentic loops, we’re building on the momentum of 3.7 Flash from just three weeks ago to release two new 3.8 variants:
Meet Gemini 3.8 Flash and Gemini 3.8 Flash Cyber 🧵
Incredible!
Matrix multiplication is the basic computational operation that powers modern computing (including AI). Yet, the theoretical fastest speed at which computers can multiply matrices (omega ω) is still unknown and has been a longstanding challenge for complexity theory and computer science.
Today, we announce a new record for omega (ω<2.371177). This is the result of a great team effort between @GoogleDeepMind, our academic collaborators, and our Gemini-powered coding agent AlphaEvolve! 🧮
arxiv.org/abs/2608.16884v1
Inderjit Dhillon retweeted
3.7 Flash brings a big jump in agentic performance and coding accuracy. To demonstrate, we set up a 3-agent team to autonomously train a robotics control model from scratch.
We hope you like 3.7 Flash, and you can read more here: blog.google/innovation-and-a…
Inderjit Dhillon retweeted
Latest crazy story from the frontiers of math and AI -- a neurosurgery resident, with no training in advanced math, uses ChatGPT 5.6 to solve a major open problem in numerical linear algebra. alextownsend.net/essays/SIAM…
Inderjit Dhillon retweeted
absolute honor to work and learn from you, @JeffDean @inderjit_ml, @adityakusupati @Devvrit_Khatri @snehaark , Anirudh, Rakesh, Izhak and many other collaborators. Miss those days🥲
Good times indeed!
Timely patent document email today about some past work with @jainprateek_ @inderjit_ml and @JeffDean and some awesome people about a few year old work on training neural networks 🥺
Inderjit Dhillon retweeted
New numbers are up on ProgramBench: Gemini 3.5 Flash and 3.6 Flash.
ProgramBench gives an agent a compiled binary + its docs and asks it to rebuild the entire program from scratch. No source, no decompiler, no internet.
3.6 Flash is Gemini's best showing yet. 🧵
Inderjit Dhillon retweeted
We have started our most ambitious pre-training run yet, for Gemini 4, and are excited by the progress : )
Congratulations on your legendary tenure at Google and on your new endeavor @JeffDean. Thank you for being an amazing researcher and an even better human being. Interacting with you, even though it has been on a limited basis, has been a highlight of my (ongoing) time at Google.
Tomorrow will be my last day at Google after 27 years, and watching it grow from 25 people to 190,000+ has been an amazing journey. Below is a note I shared with many people internally at Google today. An excerpt is:
It has been an absolute pleasure to work with you and to help build some of the most widely used and impactful products of all time. As a kid, I dreamed of helping build software that would be used by many people, and Google now has thirteen products used by more than a billion people (amazing!). Our work has had a tremendous impact in the world, and I have been lucky enough to collaborate and form friendships with many colleagues that I deeply admire, respect, and enjoy. It still brings me joy every time I see people out in the world using our products to find information, handle email, translate documents, watch videos, learn new things, navigate and understand the physical world, browse the web, use their phone, run large-scale computations on our infrastructure, ride in an autonomous vehicle, or perform complex tasks with the help of our AI systems. I hope you all share this sense of joy, because it is a shared accomplishment! Thank you to all of my colleagues at Google over many years!
Now I'm excited to go start @DiscoLoopAI with my longtime friends and colleagues @Sanjay_Ghemawat, @OriolVinyalsML, and @quocleix.
(Updated post: slightly redacted to not have some personal info)
Inderjit Dhillon retweeted
The goal Pelé called the most beautiful of his life was never filmed. Aug 2, 1959, vs Juventus, on Rua Javari. With @Google, we rebuilt it frame by frame. This time, the whole world can see it - goo.gle/pele
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O gol que Pelé considerava o mais bonito nunca foi filmado. 2/8/1959, contra o Juventus, na Rua Javari. Em parceria com o Google, reconstruímos o lance quadro a quadro. Desta vez, o mundo inteiro pode ver em goo.gle/pele.
Inderjit Dhillon retweeted
Introducing Nano Banana 2 Lite 🍌 and Gemini Omni Flash 🔮, our new generative media models in the Gemini API and AI Studio!
Nano Banana 2 Lite is extremely fast (<4s image) & cheap ($0.034 / 1K image).
Omni Flash is SOTA at video editing at $0.10 / sec, same as Veo 3.1 Fast!
