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Why this is ridiculous
为什么这个结论是荒诞的
These two ways of benchmarking the brain represent opposite ends of a spectrum. One, the pencil-and-paper Dhrystone benchmark, asks humans to manually simulate individual operations on a computer chip, and finds humans perform about 0.01 MIPS. The other, the supercomputer neuron simulation project, asks computers to simulate individual neurons firing in a human brain, and finds humans perform about the equivalent of 50,000,000,000 MIPS. A slightly better approach might be to combine the two estimates. This actually makes a strange sort of sense. If we assume our computer programs are about as inefficient at simulating human brain activity as human brains are at simulating computer chip activity, then maybe a more fair brain power rating would be the geometric mean of the two numbers. The combined figure suggests human brains clock in at about 30,000 MIPS-right about on par with the computer on which I'm typing these words. It also suggests that the year when Earth's digital complexity overtook its human neurological complexity was 2004.
这两种不同的人脑基准测试得出了两个完全相反的结论。第一个纸笔基准测试要求人类模拟计算机芯片上执行的单个指令，得出的结果为人脑的得分仅为0.01 MIPS左右。第二个超级计算机神经元模拟项目让计算机模拟人类大脑中单个突触的行为，得出的结果为人脑得分高达500亿MIPS。稍微好一些的做法是把两个结果合并在一起，但还是感觉怪怪的。如果我们认为计算机程序模拟人脑和人脑模拟计算机芯片的行为都一样不利索，那么稍微公平一点，人脑基准结果也许是这两个数字的几何平均值。这样得到的结果是人脑的执行效率约为3万MIPS，差不多和我现在正在打字用的计算机性能是一个水平。这同时也说明全球计算机的总计算能力在2004年就已经超过所有人类的总计算能力了。
Ants
蚂蚁
In his paper “Moore's Law at 40,” Gordon Moore makes an interesting observation. He points out that, according to biologist E. O. Wilson, there are 1015 to 1016 ants in the world. By comparison, in 2014 there were about 1020 transistors in the world, or tens of thousands of transistors per ant. An ant's brain might contain a quarter of a million neurons, and thousands of synapses per neuron, which suggests that the world's ant brains have a combined complexity similar to that of the world's human brains. So we shouldn't worry too much about when computers will catch up with us in complexity. After all, we've caught up to ants, and they don't seem too concerned. Sure, we seem like we've taken over the planet, but if I had to bet on which one of us would still be around in a million years-primates, computers, or ants-I know who I'd pick.
戈登•摩尔在《摩尔定律迈入40周年》一文中提出了一个很有意思的发现。他指出，根据生物学家E．O．威尔逊的说法，全世界有1015～1016只蚂蚁。相比之下，2014年全世界一共有约1020个晶体管，也就是说平摊下来每只蚂蚁能分到几万个晶体管。蚂蚁的大脑可能有25万个神经元，每个神经元上又有几千个突触，这意味着全世界所有蚂蚁大脑的总复杂度已经和所有人类大脑的总复杂度相当。所以我们没必要太在意什么时候计算机会在复杂度上击败我们。毕竟，我们追上了蚂蚁，但蚂蚁一点也没着急嘛。当然了，虽然我们看上去现在主宰了地球，但如果一定要我从灵长类动物、计算机和蚂蚁之中选出一个能在几百万年后依然存在的东西的话，我当然知道该选哪个。
1 Except Red Delicious apples, whose misleading name is a travesty.
1． 除了蛇果，这玩意儿的名字真是坑人。
2 Our house had a lot of vases when I was a kid.
2． 我小时候家里有许多花瓶。
3 Yet.
3． 到目前为止。
4 This figure comes from a list in Hans Moravec's book Robot: Mere Machine to Transcendent Mind.
4． 这个数字来自汉斯•莫拉维克撰写的《机器人：由机器迈向超越人类心智之路》中的一个列表。
5 Although even this might not capture everything that's going on. Biology is tricky.
5．即使是这样也没法完全精确地模拟每一个细节，生物学从来都不是这么简单的。
6 Using 82,944 processors with about 750 million transistors each, K spent 40 minutes simulating one second of brain activity in a brain with 1 percent of the number of connections as a human's.
6．每台“京”超级计算机配备了82944个处理器以及7.5亿个晶体管，连接数量相当于人类大脑的1％，它需要花40分钟才能模拟出人类大脑仅用时一秒的活动。
7 If it's past the year 2036 right now while you're reading this, hello from the distant past! I hope things are better in the future. P.S. Please figure out a way to come get us.
7．如果你读到这篇文章的时候已经过了2036年，那我在这里给你打一个来自遥远过去的招呼！我希望未来科技会更加进步。对了，你们快找个方法回来接我们啊！
8 “TPA.”
TPA：每只蚂蚁能分到的晶体管数目。
