Philosophy

It forces you to confront the fact that we know almost nothing about the true nature of reality. Whatever image you have of what's real or possible is obliterated in an instant. You're faced with a world that isn't just strange, but so utterly incomprehensible that it transcends imagination.

We never have direct access to the world in itself; we only have access to the model our brain is constructing. It works as a sort of 'best guess.' The brain isn't trying to find the absolute truth or create a perfect replica of the outside world's structure.

For a long time there was a kind of cultural chauvinism: the idea that if you just played Mozart to people in the Amazon or to hunter-gatherer groups in the South Pacific, they'd instantly recognize its greatness, maybe even see God. But of course, they don't experience it that way at all.

Neuroscientist & author of "This Is Your Brain on Music

In real life, emotions rarely arrive in neat, isolated packages. They're layered, overlapping, constantly shifting. Pure happiness, for instance, is rare; most of the time it's tinged with something else. And music, more than words, captures that mixture.

Neuroscientist & author of "This Is Your Brain on Music

Trust is a confident relationship with the unknown. Trust isn't, at its essence, an asset or an attribute or a currency. It's a belief. It's what we believe about someone or something.

Author & Leading Expert on the Sharing Economy & Collaborative Consumption

What we envision is humans using informal reasoning and intuition as a powerful guide, with formal systems then verifying those ideas. In this way, the formal system grounds high-level intuition.

When you tell people these things, they get a little fatalistic about it. They tend to think, 'Well, I guess there's not much I can do about that.' I would call that a bias. It is wrong just as often as it's likely to be right. We really need to interrogate and deconstruct that assumption. It's rarely true, and it can lead people to internalise some of these effects in a way that can be pretty damaging and totally unnecessary.

I think that we must move to a model where we value nature differently and work by integrating with nature. We just have to start innovating at a faster scale, and doing it in a way where we can then communicate those innovation wins to the next generation in a way that gets them excited and gives them hope.

We have a significant ability to change our cognitive trajectory. But first, we need to believe it's possible. And second, we need to engage in the things that allow it to happen.

Think about a rabbit sitting in a field. If that rabbit saw a hawk circling above and decided to wait for the back-propagation step before responding, it would be dead. The better you model the world, and the faster you can act on that model, the more likely your genes are to survive.

The things that are trivially easy for humans turn out to be extraordinarily difficult for machines, and vice versa. I cannot do the square root of a large number in my head, but my pocket calculator can do that instantly. But my pocket calculator still cannot make me a cup of coffee.

I think intelligence is best understood as an entity that has the ability to improve a metric through repeated exposure over time. By that definition, machine learning algorithms are learning systems — they get better with more data and more exposures.