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Nebius
@nebiusai
The ultimate cloud for AI innovators. For GenAI open-source model endpoints, check out @nebiustf.
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Most robot telemetry is thrown away because full-fidelity storage costs too much. @norma_core_dev fixes this with a data layer: NormFS syncs to Nebius S3-compatible storage, serverless GPUs on Nebius train the VLA model, and the policy returns to the fleet. One provider, one bill.
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We're one day away from our ScienceClaw Hackathon - see you all tomorrow afternoon Oct 30, 2026 at the @MIT @medialab for an exciting weekend. Thank you to our sponsors @nvidia , @claudeai, @formlabs, @nebiusai, @EdisonSci, @Stifel Venture Banking, @Google, @romixbio, @askalphaxiv, the @MITEngineering, and @LilaSciences for supporting the event and providing resources for our teams. A dream team of leaders in agentic AI, AI for science, and scaling discovery! And thank you to our amazing organizing team Habib Haddad, Calvin Chin, @e14fund, Andrea Porras, @fwang108_, @JaimeBerkovich, @SubhadeepPal, Bruno Howard, Awu Chen, Keira Boone, @leemmarom, and @maxwellbauer, and to our judges @evijit, Desiree Plata, Yilun Du, Riken Shah, Ian Ferguson, and @NikitaFedik for contributing their time and expertise. We are also grateful to the broader community joining us from Hardmode, Sundai, Harvard University, the University of Michigan, MIT, and @ReactorfieldAI, bringing together expertise and perspectives across institutions and disciplines. Looking forward to seeing what we build together!
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We're live! Three rooms. 45 minutes. Can they escape the Haunted Datacenter? 👻 Watch @devopsjacquie, @tavily_rick, and @arsh_goyal take on the challenge with @tavilyai and @nebiustf.
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Explore all the latest innovations and features across the Nebius AI Cloud. In this webinar, our product teams will walk through Q3 updates across our Cloud Platform, Managed Inference with @nebiustf, and Agentic Infrastructure with @tavilyai. Sign up:
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#NVIDIAGTC# Berlin is a wrap... and we didn't just show up. 🤖 We hit the ground running with workshops on LLM inference, physical AI, and post-training; a hackathon with 250 developers; three sessions at the show; and a full agenda at Nebius House. Here is what a week of building looks like. Danke, Berlin. 🇩🇪
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Jensen reporting for booth duty. Making the rounds at GTC Berlin, meeting the people and partners bringing AI to life across Europe. 🧵
Five days left on this one. 🏆 The @nebiusai Physical AI Awards, in partnership with @NVIDIARobotics, are open globally and close 25 October. I’m on the judging panel this year. Five categories, which double as a decent map of how the stack is being carved up right now: → Physical AI Models → Perception and Spatial Intelligence → Simulation and Synthetic Data → Systems and Deployment → Software, Tooling and Orchestration One winner in each takes $150,000 in Nebius AI Cloud credits, executive mentorship, introductions to investors and industry leaders, promotion across Nebius and NVIDIA channels, and invitation to a VIP executive dinner during CES in Las Vegas. Last year: 250+ applicants from 60+ countries, 16 winners, $1.5M in credits between them. Applications are free and open globally. If you’re building in physical AI, compute is usually the binding constraint, and six days of paperwork against $150k of it is decent arithmetic. Closes 25 October! ⏳ See you from the other side of the table! :) 🔗 Find more details here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
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"I'm going to give you a tagline: No tagline needed!" - @JensenHuang, CEO, @nvidia #NVIDIAGTC# Berlin
We’ve secured a $3.5 billion financing facility from Citi to support our global growth. The facility provides capital at attractive rates, diversifies our capital structure, and gives us greater flexibility over when and how we raise long-term financing. Full release:
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There's still time to stop by our booth at #NVIDIAGTC# Berlin. Check out our live demo with @DhruvDiddi, where we show our robots playing the piano. Booth #3013#. See you there!
Too many companies are taking a Ferrari to the grocery store. I made the case for open models on Nebius Live at GTC Berlin.
We’re behind the scenes of Nebius LIVE! Don’t miss out. We’re still streaming on X. 📺 On now: Ryan Lewis, Head of UK & Northern Europe, @cohere and Ewa Zborowska, Research Director, AI, Europe @IDC with @dee_bosa. Tune in.
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It’s day two of #NVIDIAGTC# Berlin and we’re kicking things off at Nebius House with our Healthcare & Life Sciences Startup breakfast in partnership with @nvidia. So many innovative ideas and projects are transforming the state of human health. It’s invigorating. 🩺
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🚨New: Our Head of Research @stevehou breaks down the implications of @nebiusai’s new dynamic pricing for spot/preemptible GPU compute.
The AI Builder Program is expanding across Europe with $10M in total support across compute grants, capital, and community programs. Are you building open models, developer tools, or applications on top of them? The program helps builders go from experimentation to scale-up through: - Compute grants for selected projects in areas such as open models, coding agents, post-training, and evals - VC connections to help turn open source projects into companies - Hackathons and demo days with communities including @AITinkerers, @techeurope_ , and @esra_robotics to build, connect, and share your work We’re kicking off the European expansion this week at #NVIDIAGTC# Berlin with @NVIDIAAI, @Accel, and a network of European VCs. Building AI in Europe? Details below. 👇
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Nebius has achieved NVIDIA Exemplar Cloud on NVIDIA HGX B300 for training, following our H200 and GB300 NVL72 Exemplar achievements. Learn what the validation means for training on Nebius:
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an agent can write code in seconds. But installing dependencies, running tests and waiting for results can take MUCH longer When you’re training agents, all that waiting is important. Faster text generation only speeds up one part of the process. My colleagues Di and @Mhr1036 at @nebiusai worked on the rest: how tasks get routed, how tools run, and how completed work becomes a batch the model can learn from. One idea I love: use groups of completed attempts as they become ready, so unrelated slow tasks don’t hold everything up Across the changes, they reduced the time to collect a training batch from roughly 10 minutes to just over 3 in a controlled Terminal Bench based test, with model weights held fixed. That’s 66.9% less time gathering the next batch For me, this is an interesting part of building better AI: the engineering around the model determines how much of its speed becomes useful progress. Full breakdown below
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We're a Diamond Sponsor at #NVIDIAGTC# Berlin, October 20 to 22. 💎 Join us at Booth 3013 to see demos, meet our experts, and talk shop. Stay tuned for details about our sessions! Learn more:
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