DeepMind CEO Demis Hassabis在访谈中回顾了从少年编程到创立DeepMind的历程,阐述了为何以游戏为起点、为何坚信强化学习,并深入解释了AlphaFold如何解决蛋白质折叠这一50年难题。他认为,构建通用人工智能的关键在于结合算法、算力与多学科协作,而最终目标是用智能解决科学与现实世界的根本挑战。
""I think if you look back at the 1950 paper... I don't think he meant it to be a rigorous formal test. I think it was more like a thought experiment." —— 我认为,如果你回顾图灵1950年的论文……我并不认为他本意是将其作为一个严谨的正式测试。它更像是一个思想实验。"
""Games have been significant in my life for three reasons: first to train myself, then designing games and writing AI for games, and third using games as a testing ground for developing AI algorithms." —— 游戏在我的人生中有三个重要意义:首先是训练我自己,然后是设计游戏并为游戏编写AI,第三是用游戏作为开发AI算法的试验场。"
""AlphaFold is the most complex and also probably most meaningful system we've built so far." —— AlphaFold是我们迄今为止构建的最复杂、也可能最有意义的系统。"
""I would be very hesitant to bet against how far the universal Turing machine and classical computation paradigm can go." —— 我非常不愿意押注通用图灵机和经典计算范式的极限在哪里。"
""Maybe we are the mechanism by which the universe is going to try and understand itself." —— 也许我们是宇宙试图理解自身的机制。"