Chess will never be solved, here's why

@7381

"you do realize that such evaluations can be wrong?"
++ All evaluations are wrong to some extent:
the only right evaluation is draw / win / loss from the 7-men endgame table base.
That is also how Checkers has been weakly solved:
calculate until the exact evaluation draw / win / loss of the endgame table base.

Whether they are wrong (and they are *all* presumed to be wrong until each game is solved) or right is immaterial here.  Under state of the art conditions for Go and Chess playing software and using the best available methodologies available for each currently, an evaluation of a discrete Chess position should take more CPU power to complete than a discrete Go position when using a NNUE hybrid of machine learning and brute force calculation for chess versus straight machine learning for Go.

lmao what '"whether they are wrong or right is immaterial here"

you do realize that that is the most important part???

Not remotely.  All "evaluations" derived for as-yet unsolved games are assumed to be wrong.  I'm just winning the point you tried to argue so you will think harder next time.  This discussion is meaningless for any other purpose.  It adds nothing to the topic, and I have no interest in your conclusions.  This is just a newspaper to the snout.

and yet a go position ends up taking more computing power.

your logic must be flawed somewhere.

@7386

"Stockfish can not even solve simple 8 man TB positions."
++ If given enough time it can.
Besides you first have to prove your 8-men position is relevant, i.e. can result from optimal play from both sides. Your example cannot result from the initial position by optimal play from both sides and thus is not relevant to weakly solving Chess.

Show your work.  Your articles say no such thing.  If you think that they do, then you do not understand them.  You keep ducking the question...do you have any software or hardware background?  Roblox does not count.

ok what does "The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves"  mean?

are you seriously trying to argue that strength of evaluations doesnt matter?  

It means that overall, due to Go's much larger move tree, it's the most challenging "mainstream" game to solve.  But we're not discussing that...and that imprecision is why you lost this argument.

did you miss the "difficulty of evaluating board positions and moves"?

I can evaluate a billion positions of chess a second with just a pocket calculator, and I will evaluate 3 tic tac toe positions a second with the same pocket calculator, ergo tic tac toe would require the more power to solve

Your logic is failing here.  

Read the quote:

"The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves"

The word "and" here denotes a combination.  There are games with more difficult to evaluate singular board positions (like Chess...).  There are games with larger search spaces.  There is no (popular/well known) game that has both to such a degree.  An NBA team is #1 ranked.  Do you assume that that this must ergo mean that they have the #1 offense *and* the #1 defense (as you are doing with this line of reasoning for Go)?  Because they might be ranked #3 in one and #7 in the other, and still be ranked #1 overall.  It's not a tough concept.

whats funny is that i literally predicted that you would say that.

where u fail is that the "difficulty in evaluating board positions/moves" is mathematically equivalent to the overall difficulty.

how hard is it to see that the sheer amount of moves is what makes evaluating positions hard, among other things

its also funny how you still refuse to concede your original claim, that Go as a whole is less complex than chess.

Lol.  You added "among other things" by choice, which confirms the point I just got done making.  Why do I need to keep arguing when you tacitly admit you are incorrect all by yourself? 

Good night.  I'll eviscerate any new stuff that emerges later.

Link it.  No such claim was made.

btw, deep mind cost 400 million, while deep blue cost 100 million, although inflation might put deep blue over

So where's the claim that Chess is more complex than Go in that post?  I see a claim that your "20 years later" argument is misleading (true).  I see a claim that Chess was a more prestigious game for IBM's PR purposes (true).  I see the claim that we have discussed at length (which was also true).

I don't see any other claims.

P.S. Inflation does not put Deep Blue over, but you are still comparing apples and oranges.  Google's hardware is reusable, and the AI software they built for machine learning can be applied to any number of games.  The tests they ran with AlphaZero vs. Stockfish were behind closed doors with the DeepMind team controlling both engines and their configurations.  The results were not official or verified.  They spent some weeks on it, made a misleading press release, and moved on.  IBM, on the other hand, made specialized processor boards and hardware specifically for playing chess, hired GMs, paid for an official competition with a prize fund, etc.