Generative AI
Generative AI is revolutionizing how the world computes, but there are still roadblocks for scaling to solve real business problems. At IBM Research, we’re working on trustworthy models, software, and infrastructure to allow any business to harness the power of generative AI.
Our work
BeeAI now has multiple agents, and a standardized way for them to talk
ResearchKim MartineauAI and quantum computing: How IBM showed up at SXSW 2025
NewsMike MurphyIBM’s Mikhail Yurochkin wants to make AI’s “cool” factor tangible
ResearchKim MartineauIBM Granite now has eyes
ResearchKim MartineauIBM’s new benchmark changes monthly to avoid teaching to the test
ResearchKim MartineauA benchmark for evaluating conversational RAG
ResearchKim Martineau- See more of our work on Generative AI
Publications
Can LLMs Replace Manual Annotation of Software Engineering Artifacts?
- Toufique Ahmed
- Premkumar Devanbu
- et al.
- 2025
- MSR 2025
Contextual Value Alignment
- Kush Varshney
- Miao Liu
- et al.
- 2025
- ICASSP 2025
Generative AI Model Data Pre-Training on Kubernetes: A Use Case Study
- Alexey Roytman
- Anish Asthana
- 2025
- KubeCon EU 2025
A Practical Guide To Benchmarking AI and GPU Workloads in Kubernetes
- Chen Wang
- Yuan Chen
- 2025
- KubeCon EU 2025
Effective cluster management for large scale AI and GPUs: Challenges and opportunities
- Claudia Misale
- David Grove
- 2025
- Cloud Native + Kubernetes AI Day 2025
Compliance at the Speed of Innovation: Leveraging AI-Driven Automation for Real-Time Regulatory Read
- Larry Carvalho
- Anca Sailer
- et al.
- 2025
- KubeCon EU 2025