Introducing the first sub-1 nanometer node chip — the smallest, most powerful chip technology in the world
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Mike Murphy
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73 results for AI Hardware
How to run AI workloads on mixed GPUs quickly and affordably
NewsKim MartineauBringing quantum-centric supercomputing to Illinois
Q & AKim Martineau- Topic
IBM demonstrates extreme scale for content-aware storage with a 100-billion vector database
NewsPeter HessBuilding PyTorch-native support for the IBM Spyre Accelerator
Technical noteRaghu Ganti, Mudhakar Srivatsa, Elpida Tzortzatos, Viji Srinivasan, Vaidyanathan Srinivasan, and Tabari AlexanderLifting the cover on the IBM Spyre Accelerator
Technical noteJeffrey BurnsIt takes a village to make open infrastructure for AI a reality
NewsPeter HessExpanding AI model training and inference for the open-source community
NewsPeter HessBuilding the IBM Spyre Accelerator
ReleasePeter HessIBM researchers win prestigious European grants
NewsMike Murphy and Peter HessHow the IBM Research AI Hardware Center is building tomorrow’s processors
Deep DivePeter HessReimagining storage for the generative AI era
ResearchTalia Gershon, Mike Murphy, Haris Pozidis, Swaminathan Sundararaman, and Khanh NgoHow IBM Research helped prepare the IBM z17 for tomorrow’s workloads
NewsPeter HessWhy a decades old architecture decision is impeding the power of AI computing
ExplainerPeter HessHow analog in-memory computing could power the AI models of tomorrow
ResearchPeter Hess
