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Comment by nopinsight | Hacker News Reader

The article is an interesting discussion by a Go insider in Korea.

Regarding the impact on pro-level teaching:

“The demand for pro-level teaching games and private lessons has plummeted. Professional players used to command a high price for teaching games and lessons, and this has been a critical source of income for many pros.”

I think the community would also be interested in articles which discuss the impact of AI on professionals in other fields, obviously chess, but also more distant ones such as e-sports and language translation.

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On language, I would guess that the demand for non-certified translation might plummet between many major languages and English since automatic translation of documents is now quite close to human level when there is sufficient training data.

Down the line, might this reduce the demand for advanced foreign language skills and thus change the career paths of language majors as well?

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This is interesting and doesn't make a lot of sense. You can't learn good form just by playing a good opponent.

I think you can. Especially when you can browse the tree which is similar to asking your teacher "what if" questions.

Many players I know learned how to play pretty well on 9x9 by playing a computer program.

I'd argue you can even learn much faster playing a program, because for high level players many sequences were based purely on memorization (including point values) but now seeing different results quickly you can understand it better.

And the level where your play is based on high level abstractions like influence and group strength is not that hard to reach and it wouldn't take much to reason them out just from the games.

I think the proper statement is that it's possible, but not efficient. Learning go from a go-program seems much like learning assembly from gcc.

People I know that went studying go to Asia had output from their teachers likely worse than you get from the program given the language barrier and general approach. It was about playing games with strong players (playing different styles, which I admit may teach a bit more than Alpha) and having teacher to point you which of your moves were bad and what to do instead (and that's it, only seeing some sequences and hearing "good", "bad"). Because knowing how and when you lost the game is huge. And doing shitloads of go problems of course.

That said, it still may be worth having a teacher/trainer I guess. To motivate you, give you that dopamine in person and all that jazz.

I would say it's more like learning to code yourself rather than at the university than learning assembly from gcc.

The article addresses this. Unfortunately the "teachers" were being paid mostly just to be strong opponents for the "students". So AI ruins their market.

From the article: "the Go school recruits a professional player, who would agree to play a fixed number of games, like five games, one per week, at a certain price.... Of course there is still room for lower level classes and teaching, but pros are often better at playing teaching games than explaining easy concepts."

I don't think this is a good comparison because there's so much about language that's subjective or dependent on context. if you could translate something with perfect denotation, you still need a human touch for connotation. the nuances of word choice and sentence structure that give something a flavor of emotionality, or cool logic, or confidence, or aloofness, etc. to say nothing of localization, how to handle meter, all the various tradeoffs a translator has to make because translation is inherently lossy. games don't have any of these problems, you either win or you don't

I think ai will prove "good enough" for most applications in the near future, but this won't eliminate human translation (or journalism, or copywriting, or whatever you might want to apply similar technology/techniques to). but it may well eliminate the bottom 80%

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