Vilobh Meshram

I’ve always believed the No.1 application of AI should be to improve human health. That work started with AlphaFold, and now at @IsomorphicLabs with the mission to reimagine drug discovery and one day solve all disease! We are turbocharging that goal with $2.1B in new funding.

Join us at 1pm PT for a conversation with our co-founders Dario Amodei and Daniela Amodei, moderated by Chief Product Officer Ami Vora. x.com/i/broadcasts/1…

In Claude Managed Agents, we’ve added multiagent orchestration, an outcomes loop for rubric-driven self-improvement, dreaming for self-learning, & webhooks.

I'm at the Claude w/ Code event in San Francisco, and I'll be live blogging the keynote here simonwillison.net/2026/May/6/cod…

I've always been passionate about games and they've played a big part in @GoogleDeepMind’s history, as the perfect proving ground for AI. Thrilled to announce this research partnership with @FenrisCreations - @EveOnline is one of the most extraordinary games ever built and has an amazing community. Very excited to work with @HilmarVeigar and the team!

So much rests on which of these trend lines is more representative.

Claude Mythos is a looped Transformer? Why does a loop improve performance? Our ICML 2026 paper formally answers this. arxiv.org/abs/2509.25239

Learn LLM internals

GPT-5.5 & Opus 4.7 on ARC-AGI-3 - GPT-5.5: 0.43% - Opus 4.7: 0.18% We found 3 failure modes: - True local effect, false world model - Wrong level of abstraction from training data - Solved the level, didn’t reinforce the reward See our full analysis 🧵

Thanks @Konstantine and @sequoia for such a fun and wide-ranging chat! Loved the final question - von Neumann FTW 😀

Think your vibe coding and creativity could be on the #GoogleIO main stage? Show us. As we countdown to the start of the show, the best ideas built with @GeminiApp or @GoogleAIStudio will be featured – think protein simulators, physics engines, or math-based art. 🔢

Really enjoyed this conversation - thanks again @garrytan for hosting!

Fireside chat at Sequoia Ascent 2026 from a ~week ago. Some highlights: The first theme I tried to push on is that LLMs are about a lot more than just speeding up what existed before (e.g. coding). Three examples of new horizons: 1. menugen: an app that can be fully engulfed by LLMs, with no classical code needed: input an image, output an image and an LLM can natively do the thing. 2. install .md skills instead of install .sh scripts. Why create a complex Software 1.0 bash script for e.g. installing a piece of software if you can write the installation out in words and say "just show this to your LLM". The LLM is an advanced interpreter of English and can intelligently target installation to your setup, debug everything inline, etc. 3. LLM knowledge bases as an example of something that was *impossible* with classical code because it's computation over unstructured data (knowledge) from arbitrary sources and in arbitrary formats, including simply text articles etc. I pushed on these because in every new paradigm change, the obvious things are always in the realm of speeding up or somehow improving what existed, but here we have examples of functionality that either suddenly perhaps shouldn't even exist (1,2), or was fundamentally not possible before (3). The second (ongoing) theme is trying to explain the pattern of jaggedness in LLMs. How it can be true that a single artifact will simultaneously 1) coherently refactor a 100,000-line code base *and* 2) tell you to walk to the car wash to wash your car. I previously wrote about the source of this as having to do with verifiability of a domain, here I expand on this as having to also do with economics because revenue/TAM dictates what the frontier labs choose to package into training data distributions during RL. You're either in the data distribution (on the rails of the RL circuits) and flying or you're off-roading in the jungle with a machete, in relative terms. Still not 100% satisfied with this, but it's an ongoing struggle to build an accurate model of LLM capabilities if you wish to practically take advantage of their power while avoiding their pitfalls, which brings me to... Last theme is the agent-native economy. The decomposition of products and services into sensors, actuators and logic (split up across all of 1.0/2.0/3.0 computing paradigms), how we can make information maximally legible to LLMs, some words on the quickly emerging agentic engineering and its skill set, related hiring practices, etc., possibly even hints/dreams of fully neural computing handling the vast majority of computation with some help from (classical) CPU coprocessors.

Q1 earnings are in: 2026 is off to a terrific start. Our AI investments and full stack approach are lighting up every part of the business: Search queries are at an all-time high with AI continuing to drive usage. Google Cloud revenue grew 63%, Gemini models have incredible momentum, and it was our strongest quarter ever for consumer AI subs, driven by @GeminiApp. Thanks to our partners + employees around the world. Much more to share on our earnings call in 20 minutes… and at Google I/O in 20 days!

Sir @demishassabis has a mind for synthesis. His favorite book is about a grand theory of everything. His preferred philosophers are seen by some as opposites. His life's work ranges from board games to Nobel-winning science. We're grateful to have hosted Demis and his @GoogleDeepMind team at @sequoia AI Ascent last week for a fireside chat. He kindly gave us permission to share this, and you can watch the full video here: 00:00 Intro 00:38 The Common Thread 01:29 Games as AI Training 02:59 Startup Advice 1.0 04:39 Founding DeepMind 07:25 DeepMind and AGI 08:52 AI for Science 10:37 Biology Breakthroughs and Isomorphic 12:42 New Sciences 20:29 Philosophy

@karpathy and I are back! At @sequoia AI Ascent 2026. And a lot has changed. Last year, he coined “vibe coding”. This year, he’s never felt more behind as a programmer. The big shift: vibe coding raised the floor. Agentic engineering raises the ceiling. We talk about what it means to build seriously in the agent era. Not just moving faster. Building new things, with new tools, while preserving the parts that still require human taste, judgment, and understanding.

You can now ask Gemini to create Docs, Sheets, Slides, PDFs, and more directly in your chat. No more copying, pasting, or reformatting, just prompt and download. Available globally for all @GeminiApp users.

Hello. How are you? Thank you. I love you. Please. Some of the most frequently translated phrases of the past 20 years! Google Translate began twenty years ago with a mission to help people understand one another, regardless of the language they speak. What started as a small experiment has become a global tool that helps over 1 billion users every month. In that time Translate has evolved from simple pattern matching to true understanding. In 2006, it relied on statistical machine learning to look for patterns in small word clusters. By 2016, we pioneered a shift to neural networks to move beyond literal word-for-word translations, and today we’re using our powerful Gemini models to make Translate even more helpful. We are moving from text to fluid, real-time conversations. With our latest models, you can even use your headphones as a personal interpreter that preserves your original tone and cadence - it’s an amazing experience! One of the interesting things about AI is that as we make progress, we begin to take it for granted. If you met a person who could translate across a hundred languages faster than any human can, you would be so impressed. Today, one product does that for nearly 250 languages, and we kind of just shrug. Being able to say thank you in 250 languages is not something I take for granted. So to the 1 billion who use Google Translate - merci, dhanyavaad, arigatō, gracias, and thank you! Let’s see what the next 20 years will bring.

Thanks for inviting me @garrytan, was awesome to chat and loved the inspirational space! Great to see so many startups building with @googlegemma models!

Truly an honor and blessing to host @demishassabis at YC today 🙏