The current fashion favours general AI approaches forgoing knowledge
details. Given enough calculation power applied to well chosen AI
techiques, many knowledge details are redundant because they are
generated automatically: AlphaGo does play (at least some) ko fights
with ko threats, tesujis, test moves, (at least some) life and death or
semeai problems etc. At the same time, AI calculation power is still not
large enough to generate all human knowledge details. Aji with long-term
impact and maintaining the life status "independently alive" instead of
unnecessarily transforming it to "(ko|independently alive)" (aka
"unsettled") are prime examples. Programs also play for the win
regardless of whether moves are suboptimal for the score difference -
human players tend to avoid such (programs would also profit from
avoiding such to prevent losing when making a later mistake due to a
knowledge gap related to insufficient error handling). There is another
great threat related to knowledge details, which is not immediately
apparent and will be even much less apparent when programs will exceed
top human playing strength: A program can run into a situation where an
infrequent knowledge detail becomes relevant. And a program can run into
ordinary software or hardware bugs, something that must be detected and
correct on the AI level.
My conclusion is: human expert knowledge on details of go theory matters.
There have been 9p players committing self-atari when filling a dame, so
you might argue that programs may infrequently make similar blunders.
When I issued a million dollar prize, I'd prefer human expert knowledge
implemented at least as an additional layer of error handling.
(Other fun includes internet connection trouble, server bugs of
distributed computers, hardware bugs of the local interface computers or
interrupted power supply.)
--
robert jasiek
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