Geoffrey Everest Hinton CC FRS FRSC是一位英裔加拿大认知心理学家和计算机科学家，最著名的工作是人工神经网络。自2013年以来，他一直在谷歌和多伦多大学工作。2017年，他共同创立并成为多伦多病媒研究所的首席科学顾问。
In a sensibly organised society, if you improve productivity, there is room for everybody to benefit.
All you need is lots and lots of data and lots of information about what the right answer is, and you'll be able to train a big neural net to do what you want.
I got fed up with academia and decided I would rather be a carpenter.
The brain has about ten thousand parameters for every second of experience. We do not really have much experience about how systems like that work or how to make them be so good at finding structure in data.
My father was an entomologist who believed in continental drift. In the early '50s, that was regarded as nonsense. It was in the mid-'50s that it came back. Someone had thought of it 30 or 40 years earlier named Alfred Wegener, and he never got to see it come back.
Deep learning is already working in Google search and in image search; it allows you to image-search a term like 'hug.' It's used to getting you Smart Replies to your Gmail. It's in speech and vision. It will soon be used in machine translation, I believe.