llm-d 1.0 hardens open-source AI inference for day 2 production operations
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Peter Hess
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422 results for AI
IBM and Kaggle launch leaderboard for Java framework migration
Technical noteBridget McGinn, Raju Pavuluri, Advait Pavuluri, Rahul Krishna, Srikanth Tamilselvam, Ashita Saxena, George Safta, and Michele MerlerPyTorch opens the AI ecosystem to a new class of accelerators
NewsPeter Hess- Focus Area
Toward fast AI interpretability and control
NewsKim Martineaullm-d 1.0 hardens open-source AI inference for day 2 production operations
ReleasePeter HessA new IBM Research specialization teaches how AI models run on modern accelerators
Technical noteKaoutar El MaghraouiMaking AI-driven chip design affordable with open agent factories and distributed inference at scale
NewsPeter HessHow distributed inference keeps large AI models moving
ExplainerPeter HessDemonstrating a theoretical separation between quantum computers and large language models
ResearchSrinivasan Arunachalam, Arkopal Dutt, Hari Krovi, Rik Sengupta, and Ryan MandelbaumA rough guide for going back to the Moon
ReleaseKim Martineau- Accelerated Discovery
- AI
- AI Models
- Algorithms
How llm-d makes the most of the hardware you already have
NewsPeter HessGranite 4.2 brings native reasoning to enterprise agents
ReleaseMike Murphy and Kim MartineauIntroducing DocLang, a markup language for AI
NewsKim MartineauFrom vision to reality: a unified neural solver for the power grid
ReleasePeter HessBringing a common language to AI evaluation
NewsKim Martineau
