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My friend Jaan Tallinn likes to point out that just as with rocketry, it's not enough to make our technology powerful.
我的朋友扬·塔林常说，这就像是火箭学一样，只让我们的科技拥有强大的力量是不够的。
We also have to figure out, if we're going to be really ambitious, how to steer it and where we want to go with it.
如果我们有足够的雄心壮志，就应当想出如何控制它们的方法，希望它朝着怎样的方向前进。
So let's talk about all three for artificial intelligence: the power, the steering and the destination.
那么对于人工智能，我们先来谈谈这三点：力量，操控和目的地。
Let's start with the power. I define intelligence very inclusively
我们先来说力量。我对于人工智能的定义非常全面，
simply as our ability to accomplish complex goals, because I want to include both biological and artificial intelligence.
就是我们能够完成复杂目标的能力，因为我想把生物学和人工智能都包含进去。
And I want to avoid the silly carbon-chauvinism idea that you can only be smart if you're made of meat.
我还想要避免愚蠢的碳沙文主义的观点，即你认为如果你很聪明，你就一定有着肉身。
It's really amazing how the power of AI has grown recently. Just think about it.
人工智能的力量在近期的发展十分惊人。试想一下。
Not long ago, robots couldn't walk. Now, they can do backflips.
甚至在不久以前，机器人还不能走路呢。现在，它们居然开始后空翻了。
Not long ago, we didn't have self-driving cars. Now, we have self-flying rockets.
不久以前，我们还没有全自动驾驶汽车。现在，我们都有自动飞行的火箭了。
Not long ago, AI couldn't do face recognition.
不久以前，人工智能甚至不能完成脸部识别。
Now, AI can generate fake faces and simulate your face saying stuff that you never said.
现在，人工智能都开始生成仿真面貌了，并模拟你的脸部表情，说出你从未说过的话。
Not long ago, AI couldn't beat us at the game of Go.
不久以前，人工智能还不能在围棋中战胜人类。
Then, Google DeepMind's AlphaZero AI took 3,000 years of human Go games and Go wisdom,
然后，谷歌的DeepMind推出的AlphaZero就掌握了人类三千多年的围棋比赛和智慧，
ignored it all and became the world's best player by just playing against itself.
通过和自己对战的方式轻松秒杀我们，成了全球最厉害的围棋手。
And the most impressive feat here wasn't that it crushed human gamers,
这里最让人印象深刻的部分，不是它击垮了人类棋手，
but that it crushed human AI researchers who had spent decades handcrafting game-playing software.
而是它击垮了人类人工智能的研究者，这些研究者花了数十年手工打造了下棋软件。
And AlphaZero crushed human AI researchers not just in Go but even at chess, which we have been working on since 1950.
此外，AlphaZero也在国际象棋比赛中轻松战胜了人类的人工智能研究者们，我们从1950年就开始致力于国际象棋研究。
