Brains, real and metaphorical


A few highlights from Lee Gomes’s long, lucid interview with Facebook’s artificial-intelligence chief Yann LeCun in IEEE Spectrum:

Gomes: We read about Deep Learning in the news a lot these days. What’s your least favorite definition of the term that you see in these stories?

LeCun: My least favorite description is, “It works just like the brain.” I don’t like people saying this because, while Deep Learning gets an inspiration from biology, it’s very, very far from what the brain actually does. And describing it like the brain gives a bit of the aura of magic to it, which is dangerous. It leads to hype; people claim things that are not true. AI has gone through a number of AI winters because people claimed things they couldn’t deliver.

Gomes: You seem to take pains to distance your work from neuroscience and biology. For example, you talk about “convolutional nets,” and not “convolutional neural nets.” And you talk about “units” in your algorithms, and not “neurons.”

LeCun: That’s true. Some aspects of our models are inspired by neuroscience, but many components are not at all inspired by neuroscience, and instead come from theory, intuition, or empirical exploration. Our models do not aspire to be models of the brain, and we don’t make claims of neural relevance.

Gomes: You’ve already expressed your disagreement with many of the ideas associated with the Singularity movement. I’m interested in your thoughts about its sociology. How do you account for its popularity in Silicon Valley?

LeCun: It’s difficult to say. I’m kind of puzzled by that phenomenon. As Neil Gershenfeld has noted, the first part of a sigmoid looks a lot like an exponential. It’s another way of saying that what currently looks like exponential progress is very likely to hit some limit—physical, economical, societal—then go through an inflection point, and then saturate. I’m an optimist, but I’m also a realist.

There are people that you’d expect to hype the Singularity, like Ray Kurzweil. He’s a futurist. He likes to have this positivist view of the future. He sells a lot of books this way. But he has not contributed anything to the science of AI, as far as I can tell. He’s sold products based on technology, some of which were somewhat innovative, but nothing conceptually new. And certainly he has never written papers that taught the world anything on how to make progress in AI.

Gomes: You yourself have a very clear notion of where computers are going to go, and I don’t think you believe we will be downloading our consciousness into them in 30 years.

LeCun: Not anytime soon.

3 thoughts on “Brains, real and metaphorical

  1. Alan Booker

    Nick, what a great read. LeCun certainly embodies so much of what might give confidence in the research that is being done today.
    His balanced articulation about the differences between theory, intuition, and empirical exploration also inspires.

    Unsupervised learning, as opposed to artificial learning systems, does necessitate what he calls the “basic principles of biological learning.” Even after those elusive basic elements might have been defined I suspect, as far as AI is concerned, that which truly defines our humanity, use your own definition, will be an impassible stumbling block.

    The term cargo cult science which I really like, brings unfolding vistas of mad tweekers and rabid scientists to mind.

    Regards, Alan

  2. Ketan

    I love the commentary on “not” calling it just like brain learning. In a similar way, kids’ curiosity needs to be carefully observed lest something unintended happen. Mr. Carr, I’d love to speak with you at greater length regarding the exploration of data’s usefulness in our government systems. I’m currently working on my Master’s capstone project for Sustainable Management in Public Administration at Presidio Graduate School in San Francisco. The focus of my project is the utilization of open data and cloud utility to improve the provision of public service through information ubiquity. Your writing in Big Switch and Is Google Making Us Stupid? paints a vivid picture of where information in society is going and I think your input would be invaluable to my work. Please let me know, thanks!

  3. Walter Hehl

    Your comment on NOT using “like the brain” is very appropriate and important: But for journalists (and probably us, too) nature in general and specifically the brain is the giant benchmark and “sells”. In technology, the design points for functions can be very different from nature – due to different basics – and result in very different solutions, or can be similar. And there are features in technology making AI in some aspects even superior. I understand that you in the AI business have to be cautious. But I would insist that the brain on the other hand is a computer.

    But aren’t you too harsh to Ray Kurzweil? Ray has been a pioneer in pragmatic character recognition many years ago (1974 with a product reading printed material loud for blind people!) . Isn’t pattern recognition a building block of AI?

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