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. Researchers at the company have now published research that combines the abilities of a large language model with those of AlphaZero, a successor to AlphaGo also capable of playing chess, to solve very tricky mathematical proofs.
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.
Artificial Intelligence Machine Learning Google Deepmind Mathematics
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