A more fluid way to model time-series data
Research
Kim Martineau
Blog
356 results for AI
How IBM built an AI model to discover railroad defects before they’re critical
NewsPeter HessA more fluid way to model time-series data
ResearchKim Martineau- Focus Area
In AI, alignment is the goal. Steerability is how you get there
Q & AKim MartineauScaling to meet the future of India’s AI needs
NewsMike MurphyAI agent reliability with BeeAI
Technical noteSandi BesenIBM further strengthens Granite for enterprise deployment with HackerOne
NewsMike MurphyHere comes a foundation model for the Sun
ReleaseKim Martineau and Mike MurphyUnderstanding AI through the algorithms they compute
Technical noteTakuya ItoTowards a generative future for computing
ReleaseMike MurphyHow the IBM Research AI Hardware Center is building tomorrow’s processors
Deep DivePeter HessAll decisions have trade-offs. IBM’s Wei Sun is an expert at weighing them
Q & AKim MartineauIBM Storage Scale delivers real-world performance: an in-depth analysis
Technical noteBrian Belgodere, Chris Miller, John Lewars, Matthew Klos, Yukio Hayashi Leon, Mara Miranda Bautista, and Olaf WeiserDebugging LLMs to improve their credibility
ResearchKim MartineauFrom simulated steps to real-world care: AI learns how we walk for neurology
ResearchPeter Hess
