Mimicking the universe to solve its greatest mysteries. From accelerating drug discovery to revolutionizing AI, the leap from bits to qubits is the next great frontier in tech. @IBM #WorldQuantumDay!
COMPUTING
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NVIDIA Ising Brings AI to Quantum Computing Error Correction
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Quantum computing just got an AI upgrade. @nvidia unveils NVIDIA Ising – open AI models for quantum systems delivering: up to 2.5x faster error correction up to 3x greater accuracy AI is becoming the operating system for quantum machines. More: https://
nvidianews.nvidia.com/news/nvidia-la
unches-ising-the-worlds-first-open-ai-models-to-accelerate-the-path-to-useful-quantum-computers
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NVIDIA Ising: AI Control Plane for Quantum Systems
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One of the most important signals today on World Quantum Day: @nvidia launched NVIDIA Ising, open AI models that bring calibration and error correction into the AI era. As Jensen Huang put it: "AI becomes the control plane for quantum systems." The convergence is accelerating.
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NVIDIA Launches Ising Open AI Models to Accelerate Quantum Computing
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NVIDIA Launches Ising, the World’s First Open AI Models to Accelerate the Path to Useful Quantum Computers
— Harold Sinnott 📱 (@HaroldSinnott) 15 avril 2026
👉Learn More: https://t.co/Qq51qySawH@nvidia @nvidianewsroom @NVIDIAHPCDev #WorldQuantumDay #AI pic.twitter.com/w9R268ZOi5NVIDIA Launches Ising, the World’s First Open AI Models to Accelerate the Path to Useful Quantum Computers Learn More: https://
nvidianews.nvidia.com/news/nvidia-la
unches-ising-the-worlds-first-open-ai-models-to-accelerate-the-path-to-useful-quantum-computers
… @nvidia @nvidianewsroom @NVIDIAHPCDev #WorldQuantumDay #AI -
MoE models recommended over dense models for unified memory
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Dense models like Qwen 3.5 27B & Gemma 4 31B on unified memory are a bad idea Simple rule: Lower memory bandwidth works best w/ fewer active parameters per token MoE like Gemma 4 26B-A4B would work much faster on Unified Memory
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Compute constraints double bind hurts current and future AI growth
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Compute constraints are a double bind: On the inference side you need to either (a) raise prices, (b) ration use, and/or (c) serve worse models. This hurts current growth On the training side, you can't train the next gen of models to stay competitive. This hurts future growth
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Quantum AI Significance: Users, Mechanisms and Applications Explained
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Why Quantum AI matters, who's using it, how it works + more. #WorldQuantumDay
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Dead Spiders Transformed Into Necrobotic Grippers by Engineers
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Dead Spiders Reanimated as Necrobotic Grippers by Rice University Engineers
— Ronald van Loon (@Ronald_vanLoon) 15 avril 2026
by @IntEngineering#Innovation #TechForGood #EmergingTech #Technology #Tech pic.twitter.com/nOIsc4TvO9Dead Spiders Reanimated as Necrobotic Grippers by Rice University Engineers
by @IntEngineering #Innovation #TechForGood #EmergingTech #Technology #Tech -
Training AI Models on Production Signals and Operational Patterns
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These models are trained on production signals, process behavior, operational patterns, and engineering context.
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Google Launches Gemini Robotics ER 1.6 Preview Model
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Developers can try it in @GoogleAIStudio
: https://
aistudio.google.com/prompts/new_ch
at?model=gemini-robotics-er-1.6-preview
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