What’s Next in AI
is fluid intelligence
Today’s AI is narrow. Applying trained models to new challenges requires an immense amount of new data training, and time. We need AI that combines different forms of knowledge, unpacks causal relationships, and learns new things on its own.
Our work
What are foundation models?
ExplainerHow to use AI to discover new drugs and materials with limited data
NewsThe IBM Research innovations powering IBM z16
NewsWhat is human-centered AI?
ExplainerOpen-sourcing analog AI simulation
ResearchIBM scientists give artificial neural networks a new look for neuromorphic computing
Research- See more of our work on AI
Tools + code
IBM Analog Hardware Acceleration Kit
An open source Python toolkit for exploring and using the capabilities of in-memory computing devices in the context of artificial intelligence.
View project →Project Debater for Academic Use
The technologies underlying Project Debater available as cloud services. Includes core natural language understanding capabilities, argument mining, and narrative generation.
View project →AI FactSheets 360
Toolkit to create factsheets outlining the details about how an AI service operates, how it was trained and tested, its performance metrics, fairness and robustness checks, intended uses, maintenance, and other critical details.
View project →GT4SD
An open-source library to accelerate hypothesis generation in the scientific discovery process.
View project →
MIT-IBM Watson AI Lab
We’re partnering with the sharpest minds at MIT to advance AI research in areas like healthcare, security, and finance.
Publication collections
Teams
- Adversarial Robustness and Privacy
- AI for Asset Management
- AI for Business Automation
- AI for Code
- AI for Supply Chain
- AI Hardware
- AI Testing
- Automated AI
- Causality
- Computer Vision
- Conversational AI
- Explainable AI
- Fairness, Accountability, Transparency
- Human-Centered AI
- Knowledge and Reasoning
- Machine Learning
- Natural Language Processing
- Neuro-symbolic AI
- Speech
- Trusted AI
- Trustworthy Generation
- Uncertainty Quantification
