The Future of Machine Intelligence

Chapter 2. Yoshua Bengio: Machines That Dream

Yoshua Bengio is a professor with the department of computer science and operations research at the University of Montreal, where he is head of the Machine Learning Laboratory (MILA) and serves as the Canada Research Chair in statistical learning algorithms. The goal of his research is to understand the principles of learning that yield intelligence.

Key Takeaways

• Natural language processing has come a long way since its inception. Through techniques such as vector representation and custom deep neural nets, the field has taken meaningful steps towards real language understanding.

• The language model endorsed by deep learning breaks with the Chomskyan school and harkens back to Connectionism, a field made popular in the 1980s.

• In the relationship between neuroscience and machine learning, inspiration flows both ways, as advances in each respective field shine new light on the other.

• Unsupervised learning remains one of the key mysteries to be unraveled in the search for true AI. A measure of our progress towards this goal can be found in the unlikeliest of places—inside the machine’s dreams.

Let’s start with your background.

I have been researching neural networks since the 80s. I got my Ph.D. in 1991 from McGill University, followed by a postdoc at MIT with Michael Jordan. Afterward, I worked with Yann LeCun, Patrice Simard, Léon Bottou, Vladimir Vapnik, and others at Bell Labs and returned to Montreal, where I’ve spent ...