this post was submitted on 07 Sep 2026
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Huh, which logic? I'm genuinely confused. I'm just saying that it's weird that the article is phrasing it like humans are inferior to the Go engine when it's literally humans who created the Go engine. Just because humans lose to a machine doesn't make humans inferior, which the article insinuates.
The implication that something that creates something else is superior to the thing it creates is a fallacy. There is no inherent relationship between them whatsoever - it is only measurable via direct measurement of performance. The claim that "humans created the Go engine makes them superior" is exactly the same amount of logically incorrect as the "it's a machine so it's superior" claim.
If your claim that creating something means superiority held true, Lebron James' dad must be better than him at basketball. And I know that's a ridiculous claim. But it's logically equivalent to your own.
Do you really think your parents created the entirety of what constitutes "you"?
It's not logically equivalent at all, a child learns on its own without parents, or through all kinds of other influences. In addition, if your parents actually knew how to make a human, they would be able to exactly replicate a previous human they created. But this is absolutely impossible, even with genetic clones, as no human actually has any idea how to get another human to be exactly the same as another.
In contrast, someone (or a collection of humans) understands completely how the best Go engine works. They can perfectly replicate the current Go engine by writing the same code again. The Go engine is a product solely by the human mind and, if the code were lost, can be remade by applying the same principles.
"Creating a human" is nothing any human has ever done. Humans have been created by million of years of evolution. In this context, if you want logical equivalency, "nature/universal laws" (or if you're so inclined, "god") would be the equivalent representation of what humans are to a Go engine.
We actually don't understand the inner workings of most neural networks, this is a well-known problem. We can evolve them to solve a problem but we won't necessarily know how they are solving it.