Machine Learning
Supervised, unsupervised, and reinforcement learning algorithms.
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Transfer Learning
Key moments that shaped the field
Alan Turing proposes the Turing Test and the term Artificial Intelligence is coined at the Dartmouth Conference (1956).
Expert systems and natural language processing emerge; the first AI winter follows due to limited compute and funding.
Machine learning proliferates, neural networks gain traction, and industry adoption accelerates.
Deep learning breakthroughs enabled by big data and GPU compute usher in modern AI.
Explore current fields and applications
Supervised, unsupervised, and reinforcement learning algorithms.
Neural networks learning complex representations.
Understanding and generating human language.
Understanding images and video at scale.
Emerging technologies and societal impact
Machines that can generalize across tasks approaching human-level capability.
Quantum computing paired with AI for previously intractable problems.
Direct human–AI interfaces enabling new forms of cognition.
Self-driving vehicles, drones, and robotics operating independently.
Standards and policy ensuring safe and beneficial AI.
Human–AI collaboration at scale in manufacturing.
Personalized medicine and AI-powered diagnostics.
Adaptive learning and intelligent tutoring systems.
AI for renewable energy and environmental monitoring.