Games
6 milestones in AI history
Samuel's Checkers Program
Arthur Samuel created a checkers-playing program at IBM that could learn from experience, improving its play over time. He coined the term 'machine learning' to describe programs that learn without being explicitly programmed.
TD-Gammon: Reinforcement Learning Plays Backgammon
Gerald Tesauro created TD-Gammon, a neural network that learned to play backgammon at expert level through self-play using temporal difference reinforcement learning. It discovered novel strategies that surprised human experts.
Deep Blue Defeats Kasparov
IBM's Deep Blue defeated world chess champion Garry Kasparov in a six-game match (3.5-2.5). It was the first time a reigning world champion lost a match to a computer under standard tournament conditions. Deep Blue evaluated 200 million positions per second using brute-force search and hand-crafted evaluation.
DeepMind's DQN Masters Atari Games
DeepMind demonstrated a deep reinforcement learning agent (Deep Q-Network) that learned to play Atari 2600 games directly from pixel inputs, achieving superhuman performance on many games with no task-specific engineering. Google acquired DeepMind for ~$500 million shortly after.
AlphaGo Defeats Lee Sedol
DeepMind's AlphaGo defeated Lee Sedol, one of the greatest Go players ever, 4-1 in a five-game match in Seoul. Go has more possible positions than atoms in the universe — brute force was impossible. AlphaGo used deep reinforcement learning and Monte Carlo tree search. In Game 2, AlphaGo played Move 37 — a move so creative that experts called it 'beautiful' and 'not a human move.'
AlphaStar Masters StarCraft II
DeepMind's AlphaStar reached Grandmaster level in StarCraft II, a real-time strategy game requiring long-term planning, deception, and split-second tactics with incomplete information — far more complex than Go or chess.