Yann LeCun

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Developing visual recognition in machines is helpful in performing visual tasks, of course, but this ability has the potential to unfold Artificial Intelligence in much broader and significant ways, providing AI with a context from which to more accurately “comprehend” the world. (I’m not even sure if the quotation marks in the previous sentence are necessary.)

In an interview conducted by Tom Simonite of Technology Review, Director of AI Research at Facebook’s AI research director Yann LeCun explains that exposing machines to video will hopefully enable them to learn through observation as small children do. “That’s what would allow them to acquire common sense, in the end,” he says.

An excerpt:


Babies learn a lot about the world without explicit instruction, though.

Yann LeCun:

One of the things we really want to do is get machines to acquire the very large number of facts that represent the constraints of the real world just by observing it through video or other channels. That’s what would allow them to acquire common sense, in the end. These are things that animals and babies learn in the first few months of life—you learn a ridiculously large amount about the world just by observation. There are a lot of ways that machines are currently fooled easily because they have very narrow knowledge of the world.


What progress is being made on getting software to learn by observation?

Yann LeCun:

We are very interested in the idea that a learning system should be able to predict the future. You show it a few frames of video and it tries to predict what’s going to happen next. If we can train a system to do this we think we’ll have developed techniques at the root of an unsupervised learning system. That is where, in my opinion, a lot of interesting things are likely to happen. The applications for this are not necessarily in vision—it’s a big part of our effort in making progress in AI.•

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Mere consumerism can’t explain the whole of innovation, as I’ve mentioned. Cool gadgets you can slide into your pocket are good things, but they’re not everything. 

Silicon Valley’s investment in smartphones and social media is tapering, as Artificial Intelligence, from driverless cars to robot workers, has, urged on by Deep Learning, come into fashion, writes John Markoff of the New York Times. Is it all a bubble? Probably somewhat, but a lot of actual foundation can be laid during such a time of exuberance. 

In Markoff’s book Machine of Loving Grace, he held that we could make a conscious choice between A.I. and Intelligence Augmentation, but when different companies and countries are competing with so much on the line, such questions often answer themselves. 

An excerpt:

In the most recent shift, the A.I. idea emerged first in Canada in the work of cognitive scientists and computer scientists like Geoffrey Hinton, Yoshua Bengio and Yann LeCun during the previous decade. The three helped pioneer a new approach to deep learning, a machine learning method that is highly effective for pattern recognition challenges like vision and speech. Modeled on a general understanding of how the human brain works, it has helped technologists make rapid progress in a wide range of A.I. fields.

How far the A.I. boom will go is hotly debated. For some technologists, today’s technical advances are laying the groundwork for truly brilliant machines that will soon have human-level intelligence.

Yet Silicon Valley has faced false starts with A.I. before. During the 1980s, an earlier generation of entrepreneurs also believed that artificial intelligence was the wave of the future, leading to a flurry of start-ups. Their products offered little business value at the time, and so the commercial enthusiasm ended in disappointment, leading to a period now referred to as the “A.I. Winter.”

The current resurgence will not fall short this time, said several investors, who believe that the economic potential in terms of new efficiency and new applications is strong.

“There is no chance of a new winter,” said Shivon Zilis, an investor at Bloomberg Beta who specializes in machine intelligence start-ups.•

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