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Mar 14, 2023

An AI Learned to Play Atari 6,000 Times Faster

Posted by in categories: information science, robotics/AI

We don’t learn by brute force repetition. AI shouldn’t either.


Despite impressive progress, today’s AI models are very inefficient learners, taking huge amounts of time and data to solve problems humans pick up almost instantaneously. A new approach could drastically speed things up by getting AI to read instruction manuals before attempting a challenge.

One of the most promising approaches to creating AI that can solve a diverse range of problems is reinforcement learning, which involves setting a goal and rewarding the AI for taking actions that work towards that goal. This is the approach behind most of the major breakthroughs in game-playing AI, such as DeepMind’s AlphaGo.

As powerful as the technique is, it essentially relies on trial and error to find an effective strategy. This means these algorithms can spend the equivalent of several years blundering through video and board games until they hit on a winning formula.

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