Board Games

2914 readers

2 users here now

Let's Play a Game! A place to discuss all things board game, regardless of genre. Everything from Scrabble and Catan to Ark Nova, 1830 and beyond is fair game! That means we have blackjack. Bring your own hookers, sorry.

Rules:

Play nicely with others here.
Discussion should be at least somewhat related to board games and all that entails.
Self-promotion is allowed within reason. Don't go overboard!

Other comms that might be of interest:

Other boardgame comms:

!juegosdemesa@feddit.cl (Spanish)

founded 3 years ago

MODERATORS

Profilename1@sopuli.xyz

AwesomeLowlander@sh.itjust.works

AwesomeLowlander@sopuli.xyz

Blaze@sopuli.xyz

Dupelet@piefed.social

297

Go grandmaster becomes first human to win series against advanced AI engine in 3-hour match (www.pcgamer.com)

submitted 3 weeks ago by cm0002@lemy.lol to c/boardgames@sopuli.xyz

31 comments fedilink hide all child comments

you are viewing a single comment's thread
view the rest of the comments

[–] baines@lemmy.cafe 6 points 3 weeks ago (1 children)

yea nah

it being a deterministic game means there is a right answer or correct play at each point

now we obviously realized our foundational principles are wrong at times, otherwise this new computer method would not have been shocking but that was a human failing and not something you could exploit against a bot

the kind of leap you are envisioning is something that would only really work in a chaotic system

the idea being there that human can leap to a right conclusion not completely supported by facts

you could arguably just call that gambling

[–] tquid@sh.itjust.works 3 points 3 weeks ago* (last edited 3 weeks ago) (1 children)

I wouldn't call it a "leap" but a few years ago some researchers did find a weird byway in the then-current go-playing "AI"s (neural-network setups, as someone else pointed out). They had to cheat a bit by examining the NN's "thinking" more directly, and found a cyclic strategy that allowed a human to beat the machine.

https://www.far.ai/blog/even-superhuman-go-ais-have-surprising-failure-modes

It's interesting for more "AI"-type stuff generally. The point is not so much "us with our special brains will always find ways to defeat AI" but more "there are odd blind spots that you would not predict by just looking at the output/games, and these can be exploited with appropriate technology."

Edit: remove redundantly redundant redundancy

[–] baines@lemmy.cafe 4 points 3 weeks ago

that is cool and not uncommon in algos in general

bad cost function, poor fit / overfit, local inflection etc