DeepMind’s differentiable neural computer helps you navigate the subway with its memory

In his best selling 2011 book Thinking Fast and Slow, Nobel Prize winning economist Daniel Kahneman hypothesized that thinking could be broken down into two distinct processes —aptly named fast and slow thought. The former is all about your gut, the initial automatic responses you have to things while the later is calculated, reflective, and time consuming. A new algorithm from DeepMind is beginning to show us that so-called “slow” thinking may soon be within the reach of machine learning.In a new paper published in Nature, the Google subsidiary DeepMind explained a new approach to machine learning that uses something called a differentiable neural computer. Of course the new computer isn’t a physical piece of hardware, it’s more of a technique for organizing information and then applying that prior knowledge to unique problems. Neural Networks operate using what essentially…


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