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TECHNOLOGY
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NVIDIA Announces Physical AI Agent Skills at CVPR2026
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Building autonomous vehicles, robots, and vision AI takes more data than any team can collect on their own.
— NVIDIA (@nvidia) 4 juin 2026
At #CVPR2026, NVIDIA announced physical AI agent skills to help speed development: composable workflows that automate data generation, simulation, policy training and… pic.twitter.com/ZuHaTO683SBuilding autonomous vehicles, robots, and vision AI takes more data than any team can collect on their own. At #CVPR2026, NVIDIA announced physical AI agent skills to help speed development: composable workflows that automate data generation, simulation, policy training and
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NVIDIA Nemotron 3 Ultra: open 550B hybrid Mamba-Attention MoE
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1/ NVIDIA shipped Nemotron 3 Ultra today, a fully open 550B model with 55B active params, with the weights, training data, and complete recipe all released openly. That alone is rare at this scale. The headline however actually is speed. Ultra is a hybrid Mamba-Attention MoE, an
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AI consciousness: The pressing philosophical question of our age, debated on Hackernews
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Intense discussion at the moment on Hackernews, reacting to Ted Chiang's article. "Can AI be conscious" is a pressing question, and could become the prime philosophical question of our age.
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Modernization: now an integral part of AI strategy
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Companies running AI at scale have made a strategic shift: They have stopped treating modernization as an IT project. They have started to view it as an integral part of the AI strategy. Examples: →
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Machine learning identifies 14-protein signature predicting lung cancer risk and therapy response.
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A very impressive study for how we could prevent lung cancer more than 5 years before it is diagnosed. Using machine learning, discovery of a 14-plasma protein signature of risk that predicts responsiveness to an antibody therapy to interleukin, IL-1β
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NanoClaw AI traces shared with Hugging Face for analysis and model improvement.
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Shared my first trace from @NanoClaw_AI to @huggingface yesterday. Very cool! By default, all agents should store their traces on HF (in private) so that you can keep a history of them, analyze them,… & share them and post-train better models, harnesses and more. Excited
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AEP-001 GoalOS Proof-of-Evolution Constitution Standard
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New standard for the agent era: AEP-001 — GoalOS Proof-of-Evolution Constitution Commit → Execute → Prove → Evolve. No proof, no evolution.
No eval, no propagation.
No rollback, no release. This is Proof-Carrying Intelligence. https://
montrealai.github.io/proof-gradient
/standards/AEP-001/
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Fastest P-Video-Replace model for character replacement, 70% off until Sunday
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P-Video-Replace from @PrunaAI is up on Replicate!
— Replicate (@replicate) 4 juin 2026
This is the fastest model for character replacement in existing video.
And until Sunday, we're giving our community 70% off, making this model only $0.009/s of output video.https://t.co/0vZhSlksom https://t.co/tWLiRDuBSiP-Video-Replace from @PrunaAI is up on Replicate! This is the fastest model for character replacement in existing video. And until Sunday, we're giving our community 70% off, making this model only $0.009/s of output video. http://
replicate.com/prunaai/p-vide
o-replace
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Pipeline order is a hyperparameter for optimizing LLM execution strategies
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5/5 Takeaway: pipeline order is a hyperparameter. If you're already paying for parallel rollouts, reuse them – they're relevant context, not just candidate answers. Full write-up: [
https://
ai21.com/blog/first-sca
le-then-enrich-how-the-right-execution-strategy-helped-us-reach-state-of-the-art-on-swe-rebench/?utm_source=org-twitter
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