Sumith Kulal

Fixed vision encoders like DINO have driven impressive progress in more learnable representations for generative modeling - but there is no universal variant across modalities, and they do not scale with the generative model. We introduce our self-supervised framework, Self-Flow, that builds learnability directly into flow models, working in a unified and scalable way across image, video and audio. Particularly excited about the gains on video-action prediction: Beyond the overall success rate improving substantially, more complex tasks - like "Open and Place" - see some of the clearest gains. So many interesting research questions to explore to make 🤖 go brrr Super glad to be working with my amazing colleagues @hila_chefer, Dominik, @dustin_podell, Vikash, @Vinh_Suhi, Antonio and @robrombach - as well as the whole @bfl_ml team! arxiv: arxiv.org/abs/2603.06507 project page: bfl.ai/research/self-…

@iamsashasax @AnthropicAI Congrats Sasha!!!

In a couple weeks I'm joining @AnthropicAI to work on pretraining after nearly 3 years at FAIR, developing post-training flywheels for physical intelligence (like SAM 3D) I'm stoked to build new capabilities for a model I personally love, with such thoughtful people

New research from @bfl_ml 🥳 Meet Self-Flow: our self-supervised framework for image, audio, video & world models 🤖 bfl.ai/research/self-… Do generative models really need DINO to learn strong representations? We propose teaching them directly via a joint framework instead 🧵

hot off the press — representation learning done right 🚀

@weihua916 @Anthropic woohoo, congrats Weihua!

Excited to share that I’ve joined @Anthropic on the Knowledge team. Looking forward to working on model capabilities for knowledge work — things like deep research and multi-hop web search. Grateful for everything I learned at Perplexity and excited for what’s ahead.

future is wild, really excited for coding and agentic workflows with blazing fast speed ⚡️ kudos to @StefanoErmon @adityagrover_ @volokuleshov and the whole @_inception_ai team for pushing hard on the new paradigm!

@StefanoErmon congrats team, very impressive!

Mercury 2 is live 🚀🚀 The world’s first reasoning diffusion LLM, delivering 5x faster performance than leading speed-optimized LLMs. Watching the team turn years of research into a real product never gets old, and I’m incredibly proud of what we’ve built. We’re just getting started on what diffusion can do for language.

🚨 FLUX.2 from @bfl_ml is here on fal - day 0 release! 🎨 Generate and edit images with incredible quality 🎯 HEX codes and JSON prompts for better control 🎬 Pro and Flex: High-fidelity images and text rendering ⚡ Dev: LoRA training for customization blog.fal.ai/flux-2-is-now-…

FLUX.2, from @bfl_ml, is now available in ElevenLabs Image & Video. Real-world lighting and spatial accuracy. 4MP fidelity. Multi-reference control.

FLUX.2 is here - our most capable image generation & editing model to date. Multi-reference. 4MP. Production-ready. Open weights. Into the new.

@bfl_ml hackathon kicking off at @SHACK15sf. The hats go hard, shoutout to @fal for the collab. The builds will go harder. 🌲🌲

@mshlguo 🔥🔥🔥

Today we're announcing SAM 3D, a foundation model for visually grounded 3D reconstruction. Super excited to share what my team has been working on! Try it here: aidemos.meta.com/segment-anythi… Blog: ai.meta.com/blog/sam-3d/ Paper: ai.meta.com/research/publi… Code: github.com/facebookresear…

upgrade incoming.

@vivianmshen @ycombinator 🔥🔥🔥

Feels good to come home :) I thought I was going to take a long break after leaving Acely this summer, but I’m excited to join @ycombinator as a Visiting Partner in the W26 batch. I loved my time in YC and I’m excited to pay it forward. Serendipitously reconnecting with @sdianahu @garrytan @harjtaggar and @snowmaker made it clear that there’s exciting work to be done with the most ambitious founders. Let’s make something people want!

we're hosting another round of AI Talks this friday at the krea office in sf! we'll have an amazing list of speakers from top research labs: @runwayml, @bfl_ml, @Snap and krea. join here: partiful.com/e/M0kSKIR3KuBs…?

@LiamFedus @ekindogus @periodiclabs Congrats on the launch, very exciting!

Today, @ekindogus and I are excited to introduce @periodiclabs. Our goal is to create an AI scientist. Science works by conjecturing how the world might be, running experiments, and learning from the results. Intelligence is necessary, but not sufficient. New knowledge is created when ideas are found to be consistent with reality. And so, at Periodic, we are building AI scientists and the autonomous laboratories for them to operate. Until now, scientific AI advances have come from models trained on the internet. But despite its vastness — it’s still finite (estimates are ~10T text tokens where one English word may be 1-2 tokens). And in recent years the best frontier AI models have fully exhausted it. Researchers seek better use of this data, but as any scientist knows: though re-reading a textbook may give new insights, they eventually need to try their idea to see if it holds. Autonomous labs are central to our strategy. They provide huge amounts of high-quality data (each experiment can produce GBs of data!) that exists nowhere else. They generate valuable negative results which are seldom published. But most importantly, they give our AI scientists the tools to act. We’re starting in the physical sciences. Technological progress is limited by our ability to design the physical world. We’re starting here because experiments have high signal-to-noise and are (relatively) fast, physical simulations effectively model many systems, but more broadly, physics is a verifiable environment. AI has progressed fastest in domains with data and verifiable results - for example, in math and code. Here, nature is the RL environment. One of our goals is to discover superconductors that work at higher temperatures than today's materials. Significant advances could help us create next-generation transportation and build power grids with minimal losses. But this is just one example — if we can automate materials design, we have the potential to accelerate Moore’s Law, space travel, and nuclear fusion. We’re also working to deploy our solutions with industry. As an example, we're helping a semiconductor manufacturer that is facing issues with heat dissipation on their chips. We’re training custom agents for their engineers and researchers to make sense of their experimental data in order to iterate faster. Our founding team co-created ChatGPT, DeepMind’s GNoME, OpenAI’s Operator (now Agent), the neural attention mechanism, MatterGen; have scaled autonomous physics labs; and have contributed to some of the most important materials discoveries of the last decade. We’ve come together to scale up and reimagine how science is done. We’re fortunate to be backed by investors who share our vision, including @a16z who led our $300M round, as well as @Felicis, DST Global, NVentures (NVIDIA’s venture capital arm), @Accel and individuals including @JeffBezos , @eladgil , @ericschmidt, and @JeffDean. Their support will help us grow our team, scale our labs, and develop the first generation of AI scientists.

@ibab legendary run Igor 🫡

Today was my last day at xAI, the company that I helped start with Elon Musk in 2023. I still remember the day I first met Elon, we talked for hours about AI and what the future might hold. We both felt that a new AI company with a different kind of mission was needed. Building AI that advances humanity has been my lifelong dream. My parents left the Russian Federation after the collapse of the USSR in search of a better life for their kids. Life wasn’t always easy as immigrants. Despite the hardships, my parents believed that human values were priceless: values like courage, compassion, curiosity for understanding the world. As a child, I admired scientists like Richard Feynman and Max Planck, who relentlessly pushed the frontiers of physics in order to understand the universe. As a particle physics PhD student at CERN I was excited to contribute to that mission. But the search for new physics was getting harder and harder, requiring bigger and bigger colliders, while new discoveries kept getting fewer. So I began to wonder if superintelligence, not larger colliders, could be the key to unlocking the mysteries of the universe. Could AI develop a consistent theory of quantum gravity? Could AI prove the Riemann hypothesis? In early 2023 I became convinced that we were getting close to a recipe for superintelligence. I saw the writing on the wall: very soon AI could reason beyond the level of humans. How could we ensure that this technology is used for good? Elon had warned of the dangers of powerful AI for years. Elon and I realized that we had a shared vision of AI used to benefit humanity, thus we recruited more like minded engineers and set off to build xAI. The early days of xAI were not easy. Naysayers told us that we arrived too late to the game, so starting a top AI company from scratch would be impossible. But we believed we could do the impossible. Starting a company from zero required lots of hands-on work. In the beginning I built many of the foundational tools used at the company to launch and manage training jobs. I later oversaw much of the engineering at the company, including Infrastructure, Product and Applied AI projects. xAI’s people are deeply dedicated. Through blood sweat and tears, our team’s blistering velocity built the Memphis supercluster, and shipped frontier models faster than any company in history. I learned 2 priceless lessons from Elon: #1 be fearless in rolling up your sleeves to personally dig into technical problems, #2 have a maniacal sense of urgency. xAI executes at ludicrous speed. Industry veterans told us that building the Memphis supercluster in 120 days would be impossible. But we believed we could do the impossible. Our goal was to get our training setup running at scale on the Memphis cluster ASAP. Towards the end of our 120 day deadline, we were riddled with mysterious issues with communicating over RDMA between the machines. Elon decided to fly to the datacenter, and we followed. Our infra team landed in Memphis in the middle of the night and got straight to work. After pouring through tens of thousands of lines of lspci output we finally identified a wrong BIOS setting, the root of the problem. Elon was there with us until late into the night. When the training run finally worked, Elon posted our triumph at “4:20am” causing us to laugh out loud. I will never forget the rush of adrenaline that night, and the emotional bonds that we were all in this together. We went to bed feeling like we were living through the most exhilarating time of our lives. I have enormous love for the whole family at xAI. Our team is truly special - you’re the most dedicated people I’ve ever worked with. Catching up to the frontier this quickly hasn’t been easy. It was made possible by everyone’s diehard grit and team spirit. Thank you to every single person who joined me on this adventure. I want to honor your contributions, your time, your sacrifices, which are never easy. I will always remember working together far into the nights and burning the midnight oil. I will never forget the sacrifices and contributions you’ve made. As I drive away today, I feel like a proud parent, driving away after sending their kid away to college. My heart is brimming with tears of joy, rooting for the company as it grows and matures. As I'm heading towards my next chapter, I’m inspired by how my parents immigrated to seek a better world for their children. Recently I had dinner with Max Tegmark, founder of the Future of Life Institute. He showed me a photo of his young sons, and asked me “how can we build AI safely to ensure that our children can flourish?” I was deeply moved by his question. Earlier in my career, I was a technical lead for DeepMind's Alphastar StarCraft agent, and I got to see how powerful reinforcement learning is when scaled up. As frontier models become more agentic over longer horizons and a wider range of tasks, they will take on more and more powerful capabilities, which will make it critical to study and advance AI safety. I want to continue on my mission to bring about AI that’s safe and beneficial to humanity. I’m announcing the launch of Babuschkin Ventures, which supports AI safety research and backs startups in AI and agentic systems that advance humanity and unlock the mysteries of our universe. Please reach out at ventures@babuschk.in if you want to chat. The singularity is near, but humanity’s future is bright!

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Super thrilled to welcome @hila_chefer to @bfl_ml 🚀 Come join us. We are actively hiring across several functions!