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Google DeepMind’s Game-Playing AI Tackles a Chatbot Blind Spot
Google's new advance combines a large language model with a self-learning AI. The technique could address some shortcomings with AI—although there’s a catch.
Several years before ChatGPT began jibber-jabbering away, Google developed a very different kind of artificial intelligence program called AlphaGo that learned to play the board game Go with superhuman skill through tireless practice. Google DeepMind calls the approach used for both AlphaProof and AlphaGeometry “neuro-symbolic” because they combine the pure machine learning of an artificial neural network, the technology that underpins most progress in AI of late, with the language of conventional programming. “What we’ve seen here is that you can combine the approach that was so successful, and things like AlphaGo, with large language models and produce something that is extremely capable,” says David Silver, the Google DeepMind researcher who led work on AlphaZero.
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