AlphaZero, developed by DeepMind, represents a significant advancement in artificial intelligence, particularly in the realm of chess, outperforming the long-standing champion Stockfish. Unlike Stockfish, which calculates a vast number of potential moves, AlphaZero employs a pattern recognition approach to achieve optimal outcomes with fewer calculations. The discussion highlights the implications of Gödel's Incompleteness Theorem on the potential for algorithms to fully understand mathematics, while also emphasizing the remarkable capabilities of neural networks in solving complex problems. The conversation suggests that while AlphaZero is groundbreaking, it raises questions about the limits of AI in mathematical reasoning.
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greg1313 said:...which leads me to the question "Can we construct an algorithm that, given the rules of math, teaches itself math and consequently arrives at solutions for problems currently unattainable for humans". Maybe not in this era but I certainly don't know that.
Jameson said:I work with machine learning on a daily basis in my day job, so I've really become interested in these types of projects. Neural networks have become absolutely amazing with regards to the types of problems they can solve. Stockfish has been the gold standard of chess for years now and AlphaZero actually calculated less potential moves than Stockfish on average. Instead it will search for patterns that lead to optimal outcomes.
jonah said:Beer soaked doubt follows.
https://medium.com/@josecamachocoll...-a-scientific-breakthrough-in-ai-bf66ae1c84f2