The ‘era of experience’ will unleash self-learning AI agents across the web—here’s how to prepare
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Summary
Scientists David Silver and Richard Sutton claim AI is at the “threshold” of an “era of experience” where AI systems will be less reliant on human-provided data for improvement.
Self-improvement will come from the AI agents accessing data from, and interacting with, the real world, says the paper.
Although it looks forward and conceptual, the paper claims real-world implications for enterprises building with and for future AI systems and agents.
Famous essay by Sutton in 2019 stated that long-term progress in AI comes from leveraging large-scale computation and general-purpose search/learning methods over incorporating complex human-derived domain knowledge.
Silver is a senior scientist at DeepMind and was behind AlphaGo, AlphaZero, and AlphaStar, all breakthroughs in deep reinforcement learning.
The “era of experience” adapts these concepts and states that progress relying on human-provided data is slowing, requiring a new approach.
AI agents will have their own “stream of experience” to enable long-term goals and adapting to new behavioural patterns, and act autonomously.