Google’s AI Just Reinvented Reinforcement Learning — With Reinforcement Learning | Front Page
What if AI didn’t just follow our instructions, but learned how to improve itself? That’s exactly what Google DeepMind just pulled off. In this video, we explore how DeepMind built a new AI system that uses reinforcement learning to invent better reinforcement learning algorithms. Yes, really. AI improving AI — not as a concept, but in practice.
For years, human researchers have been writing the rules of reinforcement learning. But now, an agent has learned to write its own and outperform the best human-designed algorithms in the process. This breakthrough marks a shift from what DeepMind’s David Silver calls “the era of human data” to the “era of experience,” where AI learns not from us, but from the world around it — through trial, error, and iteration.
This is bigger than just one paper. It’s a glimpse into the future of machine learning, where human-made algorithms might become the starting point, not the standard. We’re entering an age of self-improving systems, capable of evolving far beyond what we can build by hand.
If you’re interested in the future of AI, how reinforcement learning is changing, or what happens when machines start designing their own intelligence, this is a conversation you won’t want to miss.
Subscribe to AIM TV for more deep dives into the ideas and breakthroughs shaping the future of AI and work.
India’s Biggest AI Summit: https://cypher.analyticsindiamag.com/
Read more: https://analyticsindiamag.com/
Watch more: https://www.youtube.com/playlist?list=PL9Kc1zSa46OxR8h0ZgAfEENta0vaxfWrs
#googledeepmind #reinforcementlearning #aitrainingai #metarl #aiimprovingai #futureofai #recursiveselfimprovement #aimtv #airesearch #selflearning #deepmind #aievolution #thinkaithinkaim
What if AI didn’t just follow our instructions, but learned how to improve itself? That’s exactly what Google DeepMind just pulled off. In this video, we explore how DeepMind built a new AI system that uses reinforcement learning to invent better reinforcement learning algorithms. Yes, really. AI improving AI — not as a concept, but in practice.
For years, human researchers have been writing the rules of reinforcement learning. But now, an agent has learned to write its own and outperform the best human-designed algorithms in the process. This breakthrough marks a shift from what DeepMind’s David Silver calls “the era of human data” to the “era of experience,” where AI learns not from us, but from the world around it — through trial, error, and iteration.
This is bigger than just one paper. It’s a glimpse into the future of machine learning, where human-made algorithms might become the starting point, not the standard. We’re entering an age of self-improving systems, capable of evolving far beyond what we can build by hand.
If you’re interested in the future of AI, how reinforcement learning is changing, or what happens when machines start designing their own intelligence, this is a conversation you won’t want to miss.
Subscribe to AIM TV for more deep dives into the ideas and breakthroughs shaping the future of AI and work.
India’s Biggest AI Summit: https://cypher.analyticsindiamag.com/
Read more: https://analyticsindiamag.com/
Watch more: https://www.youtube.com/playlist?list=PL9Kc1zSa46OxR8h0ZgAfEENta0vaxfWrs
#googledeepmind #reinforcementlearning #aitrainingai #metarl #aiimprovingai #futureofai #recursiveselfimprovement #aimtv #airesearch #selflearning #deepmind #aievolution #thinkaithinkaim
