When Machines Have Ideas

Ben Vigoda, Gamalon’s CEO, spoke recently at MIT Technology Review EmTech along with Pedro Domingos from University of Washington, Noah Goodman from Stanford, Ruslan Salakhutdinov from Apple/CMU, Ilya Sutskever from OpenAI, Maya Gupta from Google, and Eric Horvitz from Microsoft.

He describes how deep learning and other state-of-the art machine learning is like training a dog to provide a desired response to a stimulus – ‘ring the bell, give some food’ , ‘ring the bell, give some food’, and so forth, except that with today’s machine learning you typically need to repeat this kind of labeled input/output pair 10,000 times.

By contrast, to teach a human we would just say, ‘This is a dinner bell, when I ring it I am going to serve you some food’ – you would insert that idea directly into their mind in between where the stimulus comes in and the response goes out – by talking to them. The person can still learn from stimulus-response experiences, but you can also teach them by communicating ideas to them. This is how Gamalon’s Idea Learning works.