It is still the case, though, that AI dominates humans at Go; humans didn't get so creative about the game that they put AI back on its toes (though some did discover exploitable AI "strategy bugs").
Keel in mind that if you had a variation of Go where there was a "hole" in the middle of the board, both Lee Sedol and a competent amateur would be able to play competent "Doughnut Go" without any prior experience. But AlphaGo and its successors would certainly make a ton of dumb unforced errors unless it practiced at least a few hundred games. (I am basing this observation on similar experiments with a similar Breakout AI, not sure if these experiments have been done with Go.)
Mammals, including humans, have advanced brains because we evolved to solve weird and unexpected problems with moderate reliability, not to optimize well-known benchmarks with high reliability. (This is also why plants are green instead of black.) By contrast, AlphaGo is a machine designed to solve a highly specific problem. The whole point of machines is that they dominate humans at specific tasks, otherwise we would just use a human. But we don't describe bulldozers as "superhuman" unless we're being intentionally obscure; the same should apply to AI. Otherwise we risk assuming the AI is capable of things it probably can't do without retraining.
I am still so impressed that Lee Sedol beat Alpha Go 1 game out of 5 way back when AI made its breakout. I was sad he felt so sheepish afterward for losing. In hindsight, I think it was an amazing accomplishment even if today an AI could beat Shin Jin-Seo (#1 player) 100 out of 100 times!
When I was playing seriously there were strong players who played a ton over a board and had deep intuition about what made plays good and what made plays bad. In the late 1990s/ early 2000s there started to be a lot more in the way of computer simulation and analysis and some very strong computer players.
One (general) example was that older players liked the idea of making longer plays using more tiles to "win" a race to the S and blank tiles (the best tiles in the bag). Computer simulations generally show that turnover (as this is called) isn't optimal and you're better off holding strong combinations of letters rather than playing them off hoping to draw something better.
Now younger players are better than ever because all of their training came with the help of computer analysis and simulation.
Of course in Scrabble a huge part of it comes down to just memorizing the words in the dictionary.
It's a partial-information game, but the search space can't be as big as Go, and an AI has an advantage over human players in that the entire valid string family can be encoded into a trie or some other efficient data structure, it's never going to forget a word or think it can play one that isn't valid.
My intuition is that AI should be able to crush the best human players at this point in time, but I'm open to being corrected on that if there's some aspect of the game which I'm not modeling correctly.
https://arxiv.org/search/?query=scrabble&searchtype=all&sour...
The reason is that you need to apply some rules, like when to trade vs. making a play, balancing consonants and vowels for future plays, what parts of the board are too dangerous to make certain plays in, etc. It’s because of the distribution of unplayed tiles, the high-scoring spots on the board, and the 50-point bonus for using all of your tiles.
Because of that, generally, you’ll do better by building towards a 50-point bonus play every 3 or 4 turns than by maxing your score on each turn.
I’d be curious about letting a human player play with the assistance of the best bot available and seeing how much better that would make them. I guess part of the issue though is that in a 13 play game maybe 3 plays are meaningfully difficult. So it’d take awhile to see if the human is improving on the bot or not.
Having written what I believe is the best bot out there, since that article (BestBot on https://woogles.io), it beats many top players around 55% of the time roughly, but still has so many fundamental issues that we have not solved yet. I believe if we matched it against the top player or two in the world that it would be roughly even. I would not put money on it beating Nigel Richards over a 100-game series. We have a while to go until we build a truly superhuman bot; this is not the case for Chess/Go.
As to what you're possibly missing here - it's that Scrabble is more than just about finding the top-scoring word. There's a lot of board shape considerations, inferences, volatility, etc that current engines, including mine, don't yet take into account.
I’ve been following Mack Meller’s YT channel and he’s getting beaten pretty handily in his series.
I’d put the over/under on people playing today who would beat BestBot in a 100-game series at say 3.5. What side would you take?
I said that Scrabble was like Go in that there is/was a pretty clear difference in the type/style of play before and after the introduction of strong computer programs.
And I think that’s true? Although the computer tools have been around so long now that there aren’t any of the old school left.
Yes and no. The biggest takeaway from AI is that learning all the joseki doesn't actually matter that much, which has freed up players (except for the pros) to spend more of their time focusing on the more fun and interesting parts of the game.
There are a lot of videos showing what josekis and strategies the AI recommends, but as a human you're likely not going to be any better off following them. This is for the same reason why AI analysis of fights is largely useless. That is, the reason why you lost the big fight (and the game) isn't that you didn't find that one obscure 9P move that could have saved you, but rather than you let yourself get cut 50 moves earlier. But the AI will never show you the move where you got cut as being the reason why you lost the game, it will only show you the one random move that you'd never in a million years actually be able to find.
This video from Shygost sums up the most important strategy stuff that you actually need to know in order to get strong: https://www.youtube.com/watch?v=ig8cWuDSHTg