让我来给你们讲个故事。
Let me tell you a story. It goes back 200 million years. It's a story of the neocortex, which means "new rind." So in these early mammals, because only mammals have a neocortex, rodent-like creatures. It was the size of a postage stamp and just as thin, and was a thin covering around their walnut-sized brain, but it was capable of a new type of thinking. Rather than the fixed behaviors that non-mammalian animals have, it could invent new behaviors. So a mouse is escaping a predator, its path is blocked, it'll try to invent a new solution. That may work, it may not, but if it does, it will remember that and have a new behavior, and that can actually spread virally through the rest of the community. Another mouse watching this could say, "Hey, that was pretty clever, going around that rock," and it could adopt a new behavior as well.
要追溯到两亿年前。 是个关于新大脑皮层的故事, 讲的就是大脑的表层。 对于早期的哺乳类动物, 由于只有他们有新大脑皮层, 就像啮齿类的生物。 皮质尺寸像邮票一样而且很薄, 这个薄的皮质包裹着他们 像核桃大小的头脑。 但它可以产生新的思维方式。 不像那些非哺乳类动物, 只有固定的行为, 它可以创造新的行为。 例如一只老鼠在逃避捕食者, 它的路被堵住了, 就想想出一个新的解决方案。 那方案可能成功也可能失败, 但如果成功了,它就会记住, 于是就有了一种新的行为, 同时那个方案会迅速传遍 到其余的团体。 比如另一只老鼠看到这会说, “噢,绕过那块岩石,真是高明,” 于是它也会采取那种行为。 非哺乳类动物
Non-mammalian animals couldn't do any of those things. They had fixed behaviors. Now they could learn a new behavior but not in the course of one lifetime. In the course of maybe a thousand lifetimes, it could evolve a new fixed behavior. That was perfectly okay 200 million years ago. The environment changed very slowly. It could take 10,000 years for there to be a significant environmental change, and during that period of time it would evolve a new behavior.
不能做这些事情。 因为他们有固定的行为方式。 现在他们能学习新的行为 但不是在一个生命的过程中。 也许在几千个生命周期内, 它可以衍生出一个新的固定的行为。 那对两亿年前来讲是好极了。 那时的环境变化很慢。 那时可能要过一万年才会 发生一次巨大的环境变化, 在那期间, 可能进化一种新的行为。 那样发展似乎还不错,
Now that went along fine, but then something happened. Sixty-five million years ago, there was a sudden, violent change to the environment. We call it the Cretaceous extinction event. That's when the dinosaurs went extinct, that's when 75 percent of the animal and plant species went extinct, and that's when mammals overtook their ecological niche, and to anthropomorphize, biological evolution said, "Hmm, this neocortex is pretty good stuff," and it began to grow it. And mammals got bigger, their brains got bigger at an even faster pace, and the neocortex got bigger even faster than that and developed these distinctive ridges and folds basically to increase its surface area. If you took the human neocortex and stretched it out, it's about the size of a table napkin, and it's still a thin structure. It's about the thickness of a table napkin. But it has so many convolutions and ridges it's now 80 percent of our brain, and that's where we do our thinking, and it's the great sublimator. We still have that old brain that provides our basic drives and motivations, but I may have a drive for conquest, and that'll be sublimated by the neocortex into writing a poem or inventing an app or giving a TED Talk, and it's really the neocortex that's where the action is.
但有些事情发生了。 六千五百万年前, 发生了一个突然的,剧烈的环境变化。 我们称之为白垩纪灭绝事件。 那是恐龙走向灭绝的时候, 是百分之七十五的动植物 走向灭绝的时候, 也是哺乳类动物 取代生态位, 而达到人格化,生物进化学说道, “嗯,这个新大脑皮层是个好东西,” 于是开始发展。 哺乳类动物逐渐变大, 他们的大脑变大的速度更快, 新大脑皮层同时变大的速度也更快, 发展出明显的隆起和褶皱 来增加它的表面积。 如果你有一个人的新大脑皮层 然后把它伸展开, 大概有一方餐巾那么大, 它也是一个很薄的构造。 就像餐巾那么薄。 但它有很多的隆起和褶皱。 现在它占据我们的大脑有百分之八十 那也是我们用来思考的地方, 所以那是个很棒的升华。 我们仍旧还是有那个 提供基本动力和动机的大脑, 但也许我会有一个要去征服的想法, 那就要新大脑皮层 借由写首诗或发明一个程序 或来一个TED演讲而达到升华, 它的确是在新的大脑皮层 有了行动。 五十年前,我写了一篇论文,
Fifty years ago, I wrote a paper describing how I thought the brain worked, and I described it as a series of modules. Each module could do things with a pattern. It could learn a pattern. It could remember a pattern. It could implement a pattern. And these modules were organized in hierarchies, and we created that hierarchy with our own thinking. And there was actually very little to go on 50 years ago. It led me to meet President Johnson. I've been thinking about this for 50 years, and a year and a half ago I came out with the book "How To Create A Mind," which has the same thesis, but now there's a plethora of evidence. The amount of data we're getting about the brain from neuroscience is doubling every year. Spatial resolution of brainscanning of all types is doubling every year. We can now see inside a living brain and see individual interneural connections connecting in real time, firing in real time. We can see your brain create your thoughts. We can see your thoughts create your brain, which is really key to how it works.
描述我对大脑如何运作的想法, 我描述说大脑就像一系列模块。 每个模块可以用一种方式做事情。 每个模块可以学习和记住一种方式。 也可以执行一种方式。 然后这些模块被分派到统治集团中, 我们用我们自己的想法创造了统治集团。 后来我的这个想法就没怎么继续了。 那还是50年前。 它让我去见了约翰逊总统。 我已经思考了五十年, 一年半前我出了本书, ”如何创造思想,“ 这本书和那篇论文有着相同的主题, 但现在有了更多的证据支撑。 我们从神经科学得到 关于大脑的数据每年都成倍增加。 各类脑扫描的空间分辨率也是。 每年双倍增加。 我们现在可以看到一个活大脑的内部 看到个别神经元间的连接, 实时连接,实时放电 我们可以看到你大脑创造思维。 我们可以看到你的思维也在创造你的大脑, 这对了解大脑如何运作很重要。
So let me describe briefly how it works. I've actually counted these modules. We have about 300 million of them, and we create them in these hierarchies. I'll give you a simple example. I've got a bunch of modules that can recognize the crossbar to a capital A, and that's all they care about. A beautiful song can play, a pretty girl could walk by, they don't care, but they see a crossbar to a capital A, they get very excited and they say "crossbar," and they put out a high probability on their output axon. That goes to the next level, and these layers are organized in conceptual levels. Each is more abstract than the next one, so the next one might say "capital A." That goes up to a higher level that might say "Apple." Information flows down also. If the apple recognizer has seen A-P-P-L, it'll think to itself, "Hmm, I think an E is probably likely," and it'll send a signal down to all the E recognizers saying, "Be on the lookout for an E, I think one might be coming." The E recognizers will lower their threshold and they see some sloppy thing, could be an E. Ordinarily you wouldn't think so, but we're expecting an E, it's good enough, and yeah, I've seen an E, and then apple says, "Yeah, I've seen an Apple."
让我简单描述一下大脑如何工作的。 我算过这些单位的数量。 我们大约有三亿, 我们在大脑层里创造他们。 给你们简单举例。 我有一堆模块, 它们可以认知A的一横, 那是它们关心的全部。 一首动人的歌在播放, 一个美丽的姑娘经过, 它们都不在意,但当它们看见A的一横, 它们就会很兴奋的说“横,” 然后他们 从输出轴突输出一个高度的可能性, 那就到了下一个等级, 这些层次被分布在概念性等级中。 每一个都比下一个更抽象, 所以下一个可能说“字母A。” 去到更高一个等级可能说“apple” 信息也这样流动。 如果那个认出apple的看到 a-p-p-l, 它就会想,“嗯,我觉得接下来是e,” 然后它就会把信号传送个所有认知e的 说,“看住e, 我觉得它就要来了。” e的认知这就会降低警觉 它们可能粗心的看到一些东西觉得就是E。 通常你不会这样想, 但我们在期待一个E, 那就够了, 于是我看到了E,然后认知的apple说, “太好了,我看到了apple。”
Go up another five levels, and you're now at a pretty high level of this hierarchy, and stretch down into the different senses, and you may have a module that sees a certain fabric, hears a certain voice quality, smells a certain perfume, and will say, "My wife has entered the room."
再往上五个等级, 现在你就在一个很高的水平, 的这种大脑层, 于是延伸到不同的感官, 你可能有一个模块看到了一个特殊东西, 听到一个声音,闻到到某个特殊的香水, 它就会说,“我老婆进来房间了。”
Go up another 10 levels, and now you're at a very high level. You're probably in the frontal cortex, and you'll have modules that say, "That was ironic. That's funny. She's pretty."
往上十个等级,现在你在 一个非常高的等级。 你可能在大脑额叶, 然后你有模块说,“那很讽刺。 那很有趣。她很美。”
You might think that those are more sophisticated, but actually what's more complicated is the hierarchy beneath them. There was a 16-year-old girl, she had brain surgery, and she was conscious because the surgeons wanted to talk to her. You can do that because there's no pain receptors in the brain. And whenever they stimulated particular, very small points on her neocortex, shown here in red, she would laugh. So at first they thought they were triggering some kind of laugh reflex, but no, they quickly realized they had found the points in her neocortex that detect humor, and she just found everything hilarious whenever they stimulated these points. "You guys are so funny just standing around," was the typical comment, and they weren't funny, not while doing surgery.
你可能觉得那些模块很复杂, 实际上更复杂的是 在他们之下的大脑层集团。 有一个十六岁的女孩,她做了一个大脑手术, 她依然是清醒的,因为外科医生 要和她谈话。 手术可以做是因为大脑里没有疼痛的感觉器官。 在大脑里, 当他们刺激到某个部分, 在她大脑皮层的很小的点, 这里显示红色的,她就会笑。 所以一开始他们以为他们触碰到 某个笑神经, 但不是,他们很快意识到他们发现 那些在新大脑皮层的小点能探测到幽默, 然后她发现一切都很可笑, 每当刺激到那些点的时候。 “你们站在这里真是太好笑了,” 这是她典型的言论, 但 实际上他们在做手术时并不有趣。
So how are we doing today? Well, computers are actually beginning to master human language with techniques that are similar to the neocortex. I actually described the algorithm, which is similar to something called a hierarchical hidden Markov model, something I've worked on since the '90s. "Jeopardy" is a very broad natural language game, and Watson got a higher score than the best two players combined. It got this query correct: "A long, tiresome speech delivered by a frothy pie topping," and it quickly responded, "What is a meringue harangue?" And Jennings and the other guy didn't get that. It's a pretty sophisticated example of computers actually understanding human language, and it actually got its knowledge by reading Wikipedia and several other encyclopedias.
所以我们现在怎么样? 事实上电脑逐渐开始 通过科技掌握人类语言, 这和新大脑皮层类似。 我实际上描述了运算法则, 这和 脑层隐藏的马尔可夫模型类似, 这是一些我从90年代就开始研究的事。 "Jeopardy"是一个很广泛的语言游戏, Watson得了一个 比两人加在一起还高的分数。 它纠正了这个问题: "一段很长很无聊的演讲 就像馅饼上的装饰。“ 于是有了很快的回复,”什么是长篇大论?“ 没人理解这个问题。 那是个很复杂的例子 关于电脑理解人类语言, 它实际得到了自己的知识通过 维基百科和一些其他百科。
Five to 10 years from now, search engines will actually be based on not just looking for combinations of words and links but actually understanding, reading for understanding the billions of pages on the web and in books. So you'll be walking along, and Google will pop up and say, "You know, Mary, you expressed concern to me a month ago that your glutathione supplement wasn't getting past the blood-brain barrier. Well, new research just came out 13 seconds ago that shows a whole new approach to that and a new way to take glutathione. Let me summarize it for you."
从现在起五到十年, 搜索引擎会不仅仅基于 对文字、链接组合的寻找, 而是真正的理解, 通过阅读来理解 网络和书中成千上万页。 那么当你郁郁独行,古狗会跳出来 说,”你知道吗,Mary, 你一个月前 你向我述说的你补充的谷胱甘肽 没有通过血脑屏障。 十三秒前刚出了个新研究, 显示有一个全新方法的来解决这个问题。 一个服用谷胱甘肽的新方法, 让我来为你总结一下。“
Twenty years from now, we'll have nanobots, because another exponential trend is the shrinking of technology. They'll go into our brain through the capillaries and basically connect our neocortex to a synthetic neocortex in the cloud providing an extension of our neocortex. Now today, I mean, you have a computer in your phone, but if you need 10,000 computers for a few seconds to do a complex search, you can access that for a second or two in the cloud. In the 2030s, if you need some extra neocortex, you'll be able to connect to that in the cloud directly from your brain. So I'm walking along and I say, "Oh, there's Chris Anderson. He's coming my way. I'd better think of something clever to say. I've got three seconds. My 300 million modules in my neocortex isn't going to cut it. I need a billion more." I'll be able to access that in the cloud. And our thinking, then, will be a hybrid of biological and non-biological thinking, but the non-biological portion is subject to my law of accelerating returns. It will grow exponentially. And remember what happens the last time we expanded our neocortex? That was two million years ago when we became humanoids and developed these large foreheads. Other primates have a slanted brow. They don't have the frontal cortex. But the frontal cortex is not really qualitatively different. It's a quantitative expansion of neocortex, but that additional quantity of thinking was the enabling factor for us to take a qualitative leap and invent language and art and science and technology and TED conferences. No other species has done that.
从现在起二十年, 我们会有纳米机器人, 因为另一个指数趋势 显示科技的收缩。 他们会通过 毛细血管进入我们的大脑 然后把我们的大脑皮层连接 到枢纽里的合成大脑皮层。 而提供一个大脑皮层的延伸 现在,我的意思是, 你手机里有一个电脑, 但如果你需要一万台电脑用几秒钟 来做一个复杂的研究, 你可以进入那个枢纽一两秒。 在2030年,如果你需要一些额外的大脑皮层, 你可以在枢纽里 直接与你大脑连接。 所以当我走过我会说, “哦,这是Chris Anderson。” 他在向我走来。 我最好想一个聪明的方式来说。 我有三秒钟来想。 我大脑皮层里的三亿个模块 还不够 我需要另外一亿个。“ 于是我可以在枢纽里实现。 那时我们的思考,会像一个 生物和非生物思考的混合, 但非生物的部分 取决于我加速回收的原则。 它会成指数增长。 还记得 上次我们伸展我们大脑皮层发生了什么吗? 那是两亿年前 当我们成为变类人 进化这些大前额时。 其他灵长目动物有倾斜的额。 他们没有前大脑皮层。 但那不是真正的不同。 不同在于大脑皮层的伸展, 但那额外的思考 是我们能够飞跃的启动因子, 并因此发明了语言、艺术、科学 艺术,科学和科技 还有TED会议。 没有其他物种可以做到这样。 在接下来的几十年,
And so, over the next few decades, we're going to do it again. We're going to again expand our neocortex, only this time we won't be limited by a fixed architecture of enclosure. It'll be expanded without limit. That additional quantity will again be the enabling factor for another qualitative leap in culture and technology.
我们要再一次。 我们会再次伸展我们的新大脑皮层, 只有这样我们不会 被固定的框架结构所限制。 它会无限伸展。 那个额外的量 会再次成为一个启动因子 使我们在文化科技中有一个质的飞跃。 非常感谢!
Thank you very much.
(鼓掌)
(Applause)