What’s Next in AI is Fluid Intelligence

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.

In short, AI must have fluid intelligence—
and that's exactly what AI research teams are building.

Read our full vision and strategy

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.

In short, AI must have fluid intelligence—
and that's exactly what AI research teams are building.

Read our full vision and strategy

Workstreams

Neurosymbolic AI

We're integrating neural and symbolic techniques to build AI that can perform complex tasks by understanding and reasoning more like we do.

AI Hardware

Our digital and analog accelerators are driving massive improvements in computational power while remaining energy-efficient.

Secure, Trusted AI

Trust and security should be baked into
the core of any AI we put out into the world. We're building tools to help you ensure that it is.

AI Engineering

We're building tools to help AI creators reduce the time they spend training, maintaining,
 and updating their models.

See all teams

Publication collections

Dec 2020

Conference on Neural Information Processing Systems (NeurIPS)

Aug 2020

ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)

Jul 2020

Association for Computational Linguistics (ACL)

Feb 2020

Association for the Advancement of Artificial Intelligence (AAAI)

Dec 2019

Conference on Neural Information Processing Systems (NeurIPS)

All AI publications

Featured

mit-ibm watson ai lab

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.

Explore the lab

mit-ibm watson ai lab logo

Recent news

Blog

Project Debater explained: How debating AI actually works

12 new Project Debater AI technologies available as cloud APIs


17-March-2021

Project Debater explained: How debating AI actually works

Blog

Getting AI to Reason: Using Neuro-Symbolic AI for Knowledge-Based Question Answering

IBM researchers check AI bias with counterfactual text


5-Feb-2021

Getting AI to Reason: Using Neuro-Symbolic AI for Knowledge-Based Question Answering

IBM breakthroughs could help bring AI training from cloud to edge

Learn more

7-Dec-2020

Blog

Using machine learning to solve a dense hydrogen conundrum

IBM’s AI learns to navigate around a virtual home using common sense


3-Feb-2021

intern using quantum experience

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Experiments

The APIs include natural language understanding capabilities that deal with wikification, semantic relatedness between Wikipedia concepts, short text clustering, and common theme extraction for texts.

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The Open Source python toolkit for exploring and using the capabilities of in-memory computing devices in the context of artificial intelligence.

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Compare VSRL with traditional reinforcement learning to see how they perform under different environmental conditions and with different amounts of training.

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Try CLAI, an open-source framework for AI-powered command line plugins. CLAI helps you navigate the command line more efficiently, removing roadblocks and finding missing dependencies.

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Featured publications

Date Content Title Journal / Venue
March 2021 Paper

An autonomous debating system

Nature
Jan 2020 Paper

Mapping the Space of Chemical Reactions Using Attention-Based Neural Networks

Nature Machine Intelligence (2021)
Oct 2020 Paper

Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines

AAAI (2021)
May 2020 Paper

Generate Your Counterfactuals: Towards Controlled Counterfactual Generation for Text

AAAI (2021)

AI research teams

AI Hardware
Algorithmic Acceleration
Auto AI (tools)
Computer Vision
Explainability
Fairness
Knowledge and Reasoning
Machine Learning
Natural Language
Process Automation
Robustness
Speech
Transparency and Accountability
Value Alignment