Transcript · english → Chinese
english → Chinese transcript
在研究过去时，他的以色列根源 对他未来观点的形成至关重要。
他现在正利用所有这些知识， 为我们描绘他对未来的愿景。
尤其是随着脑机接口、 生物识别感测器等等的兴起，
很可能在比如说50年内， 人类将真正成为网络的一部分。
所有的身体、所有的大脑 都会连接到一个网络上，
如果你与网络断开连接，你将无法生 存。
因为你自己的身体部位、你自己的免 疫系统， 或许都依赖于持续连接到这个群体， 这个网络。
我们现在正在获得的新力量， 特别是生物技术和人工智能的力量，
真的会把我们变成神。
我这么说不是一种文学上的比喻，而 是字面上的意思，
也就是人类正在获得神一般的能力， 特别是创造和设计生命的能力。
不是每个人都能升级自己，
也不是每个人都能接触或控制新的 大数据算法。
全球80亿人口中，绝大多数仍会是普 通的智人，
他们很可能会失去其经济价值、政治 权力，
以及对自己生活的控制权。
我们很可能会看到一个极度不平等 的社会，
在这个社会中，极少数精英 要么是升级后的人类，要么是拥有主 宰算法的人，
比如谷歌算法或脸书算法，
End of transcript · 239 words · machine translated
Original transcript (english)
Studying the past, his Israeli roots are of crucial importance to the formation of his view of the future. He's now using all of that knowledge to give us his vision for the future. With especially the rise of brain-computer interfaces and biometric sensors and so forth, it is very likely that within, say, 50 years, people will literally be part of a network. All the bodies, all the brains would be connected together to a network,
and you won't be able to survive if you're disconnected from the net. Because your own body parts, your own immune system, perhaps depends on being constantly connected to the colony, to the network. The new powers that we are gaining now, especially the powers of biotechnology and artificial intelligence, are really going to transform us into gods. And I don't mean this as a kind of literary metaphor, I mean it in a literal sense,
that humans are acquiring divine abilities, especially the ability to create and to design life. Not everybody will be able to upgrade themselves, and not everybody will have access or have control over the new big data algorithms. Of 8 billion people in the world, the vast majority will stay just ordinary homo sapiens, and they are likely to lose their economic value, their political power,
their control over their lives. And we are likely to see an extremely unequal society, in which a very small elite, either of upgraded humans or of those humans who own the master algorithms, like the Google algorithm or the Facebook algorithm,
