2 ms·

What do you think about the hardware centric approaches like http://news.stanford.edu/news/2014/april/neurogrid-boahen-engineering-042814.html http://news.stanf

• p1esk 12y ago
  Those are interesting projects, and sooner or later we will need specialized hardware to speed up AI algorithms. However, today AI development is not constrained by computing power, at least not directly. If you run IBM Watson algorithms 100 times faster, it won't be much smarter. In ML, we need better algorithms. In AI, we need better theories. Brain simulations, such as Human Brain Project, is where we need more computing power. That is the field where 100 times faster can lead to major breakthroughs.