IBM and Kaggle launch leaderboard for Java framework migration
Technical note
Bridget McGinn, Raju Pavuluri, Advait Pavuluri, Rahul Krishna, Srikanth Tamilselvam, Ashita Saxena, George Safta, and Michele Merler
AI for Code
Most enterprises rely on large volumes of aging code that are a challenge to debug, maintain, and update. At IBM Research, we’re using AI to help modernize software stacks, designing automated programming and refactoring systems to help businesses keep up with the speed of modern life.
Our work
llm-d 1.0 hardens open-source AI inference for day 2 production operations
ReleasePeter HessHow distributed inference keeps large AI models moving
ExplainerPeter HessHow llm-d makes the most of the hardware you already have
NewsPeter HessIBM open sources CodeAlchemy, a massive synthetic dataset of high-quality code
ReleaseKim MartineauIBM’s software engineering agent tops the Multi-SWE-bench leaderboard for Java
NewsPeter Hess- See more of our work on AI for Code
