I was responding to you. I should be quoting these, but I haven't. Except I've fallen into some kind of toxic loop here.
Chess will never be solved, here's why
Sort:
Wow
Ian_Rastall wrote:
I was responding to you. I should be quoting these, but I haven't. Except I've fallen into some kind of toxic loop here.
Well, I agree that shangtsung111 is toxic, even when speaking in Turkish, but there was no reason to jump on his bandwagon. He seems to have left you behind.
Jan 15, 2023
0
#5465
llama36 wrote:
shangtsung111 wrote:
if its astronomical true.but it may not be
There is a simple proof it will be enormous... namely in the EGTBs we already have.
But you don't necessarily reach the EGTBs.
The starting position could be a forced mate in 10 that never gets below 30 men.
shangtsung111 wrote:
hi ,i agree with what MARattigan wrote.may be a few more moves than 10.
even made an analogy statement :"solution may be a one page book or a book as thick as a mountain
meaning it maybe shorter than we expect ,or not."to a nice person who asked opinion.but an ulo (unudentified living objecct)irritated me
with nonsense hollow talks and accusations for hours.thats why i wasnt in the mood to answer yyou before.
if youre still wondering,yes i live in turkey,izmir.i havvent been to van either.and i wish i could borrow your calm against such abusive people
Try again. I said your comment was absurd (which it was). You took this personally, and replied twice to call my reply absurd, and it went from there with you doing the escalating. You finishing by insulting me in Turkish...a rather craven maneuver.
Jan 15, 2023
0
#5467
btickler wrote:
MEGACHE3SE wrote:
2 things.
first, Go is much more complex than chess. it took 20 years after deep blue to get the same level for AlphaGo.
second, a massive number of permutations doesnt necessarily mean that something cant be solved. checkers had 10 ^20 and was still solved. of course, chess is much much more complex, but the big number alone should dissuade us.
Your premise assumes that the efforts put into beating the world champs for Chess and Go were the same. This is not the case. Solving Chess was much better PR for IBM than solving Go would have been, so a lot more resources were brought to bear.
In terms of actually solving, IIRC Go has more positions...but evaluating Go positions should take less CPU horsepower than evaluating Chess positions.
evaluating go positions takes WAY more CPU than chess positions.
i recommend you look at the smithsonian article or the one by scientific american.
in terms of raw computing power,
MEGACHE3SE wrote:
evaluating go positions takes WAY more CPU than chess positions.
i recommend you look at the smithsonian article or the one by scientific american.
in terms of raw computing power,
I'll read the articles if you link them, but I did not find any in-depth articles about solving Go or Chess from either publication in my 5 minutes of digging that support your statement, so...I'll stick with the articles I have already read in the past on the subject.
Optimissed wrote:
My wife is waiting for me and I'll have to go in a minute. I've been enjoying talking to you. Regarding the people you were arguing with, nobody can help where they come from and Americans sometimes have less than usual tolerance for different cultures. They can't help it so don't take it to heart! Goodnight.
Americans don't really need you to be a spokesman for them, and if your premise were true, it begs the question of where did this "American" bias originate? Are there any other cultures known for running roughshod over every other culture in their way and appropriating them (and stealing their historic treasures for good measure)?
The only person whose biases you can speak for are your own, and there's plenty of fodder there to keep you busy for a good long time.
@7328
"start analyzing on Stockfish on your PC from the opening position,
and post back here when you get to 100 ply"
++ That takes 15,000 years on a desktop, or 5 years on 3 cloud engines of 10^9 nodes/s.
@7341
"you don't necessarily reach the EGTBs"
++ It is inevitable to reach the 7-men endgame table base at sufficient depth.
In ICCF WC Finals the average is 42 moves i.e. 84 ply.
Jan 15, 2023
0
#5472
btickler wrote:
MEGACHE3SE wrote:
evaluating go positions takes WAY more CPU than chess positions.
i recommend you look at the smithsonian article or the one by scientific american.
in terms of raw computing power,
I'll read the articles if you link them, but I did not find any in-depth articles about solving Go or Chess from either publication in my 5 minutes of digging that support your statement, so...I'll stick with the articles I have already read in the past on the subject.
https://www.scientificamerican.com/article/how-the-computer-beat-the-go-master/
https://www.nature.com/articles/nature16961
https://www.businessinsider.com/why-google-ai-game-go-is-harder-than-chess-2016-3
true
MEGACHE3SE wrote:
Those articles reinforce my point. A single Chess position should take more CPU power to evaluate than a single Go position. Chess engines still use deep searches and brute force calculation alongside machine learning, AlphaGo uses purely machine learning (though they did "cheat" and use human play to seed the process, unlike AlphaZero's machine learning...which ultimately will make AlphaGo's learned valuations imperfect in the end), with heuristics to decide on win probabilities, and the heuristics used are baked-in every time AlphaGo plays and learns...i.e. almost all the processing power would be already front-loaded and done before a new position is evaluated. The only evaluation that takes place for AlphaGo in a new position is "what does this position look like related to already evaluated positions, and what does the value network say is the best win probablility?"
The whole point of machine learning is that the previous AI work is subsumed into the valuation so that the next position *doesn't* require brute force calculation. All that AlphaGo calculates is "what worked best the last time a position like this came up?". It's like training a dog to do tricks, but the AI can remember a gazillion steps for its tricks and performs those steps perfectly every single time.
Machine learning for Chess works to a point, but as Stockfish has proven out, a combination of brute force calculation and machine learning probability valuations is stronger that machine learning alone. Which is inherently obvious if you ponder it for a minute or two.
If Chess has 400 possibilities after 2 moves, and Go has 130,000 possibilities after 2 moves, then if each single Go position took more CPU power than each single Chess position, AlphaGo would be running more than 325 times slower than AlphaZero on a given position using the same DeepMind hardware. I'm pretty sure that is not the case...but feel free to prove me wrong on that.
Ergo, the CPU usage for each individual Chess position > the CPU usage for each individual Go position.
Jan 16, 2023
0
#5475
btickler wrote:
MEGACHE3SE wrote:
Those articles reinforce my point. A single Chess position should take more CPU power to evaluate than a single Go position. Chess engines still use deep searches and brute force calculation alongside machine learning, AlphaGo uses purely machine learning (though they did "cheat" and use human play to seed the process, unlike AlphaZero's machine learning...which ultimately will make AlphaGo's learned valuations imperfect in the end), with heuristics to decide on win probabilities, and the heuristics used are baked-in every time AlphaGo plays and learns...i.e. almost all the processing power would be already front-loaded and done before a new position is evaluated. The only evaluation that takes place for AlphaGo in a new position is "what does this position look like related to already evaluated positions, and what does the value network say is the best win probablility?"
The whole point of machine learning is that the previous AI work is subsumed into the valuation so that the next position *doesn't* require brute force calculation. All that AlphaGo calculates is "what worked best the last time a position like this came up?". It's like training a dog to do tricks, but the AI can remember a gazillion steps for its tricks and performs those steps perfectly every single time.
Machine learning for Chess works to a point, but as Stockfish has proven out, a combination of brute force calculation and machine learning probability valuations is stronger that machine learning alone. Which is inherently obvious if you ponder it for a minute or two.
If Chess has 400 possibilities after 2 moves, and Go has 130,000 possibilities after 2 moves, then if each single Go position took more CPU power than each single Chess position, AlphaGo would be running more than 325 times slower than AlphaZero on a given position using the same DeepMind hardware. I'm pretty sure that is not the case...but feel free to prove me wrong on that.
Ergo, the CPU usage for each individual Chess position > the CPU usage for each individual Go position.
bro i think ur just straight misreading the articles at this point.
you.... do realize that the equivalent heuristic is that alphago evaluates a position 300 times weaker?
MEGACHE3SE wrote:
bro i think ur just straight misreading the articles at this point.
you.... do realize that the equivalent heuristic is that alphago evaluates a position 300 times weaker?
"Bro" can you even explain what you just said using your own words? Define "a position 300 times weaker". What does that mean to you? Or are you going to keep regurgitating? Do you even know how to program, or are you just reading these articles with no understanding? If someone told you to write a Chess or Go engine from scratch, how would you attack the problems?
Jan 16, 2023
0
#5477
@btickler you are making the false assumption that those engines are evaluating positions at the same strength.
im going to repeat myself here
"If Chess has 400 possibilities after 2 moves, and Go has 130,000 possibilities after 2 moves, then if each single Go position took more CPU power than each single Chess position, AlphaGo would be running more than 325 times slower than AlphaZero on a given position using the same DeepMind hardware. I'm pretty sure that is not the case...but feel free to prove me wrong on that."
this makes the assumption that the evaluations are of the same strength. they arent.
it is stated very explicitly "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."
"difficulty of evaluating board positions and moves"
compared to human - wise, alphago is the same level as deep blue.
deep blue had 11 Gflops. Alphago uses at least 84000. (1200 CPU*70 gflops each, assuming the cpu's are like those found in a regular computer.).
takes more than a thousand times the amount of power, let alone with better AI, for a Go program to perform as well as a chess program
MEGACHE3SE wrote:
@btickler you are making the false assumption that those engines are evaluating positions at the same strength.
im going to repeat myself here
"If Chess has 400 possibilities after 2 moves, and Go has 130,000 possibilities after 2 moves, then if each single Go position took more CPU power than each single Chess position, AlphaGo would be running more than 325 times slower than AlphaZero on a given position using the same DeepMind hardware. I'm pretty sure that is not the case...but feel free to prove me wrong on that."
this makes the assumption that the evaluations are of the same strength. they arent.
it is stated very explicitly "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."
"difficulty of evaluating board positions and moves"
compared to human - wise, alphago is the same level as deep blue.
deep blue had 11 Gflops. Alphago uses at least 84000. (1200 CPU*70 gflops each, assuming the cpu's are like those found in a regular computer.).
takes more than a thousand times the amount of power, let alone with better AI, for a Go program to perform as well as a chess program
No Sherlock, we're comparing AlphaGo to AlphaZero here, same hardware and two root branches of the same AI software. Why would you even bring up Deep Blue?
There's no assumption of "strength" required. I stated that Chess positions should take more CPU to evaluate than Go positions, one for one. Period. End stop. You have supported my position with every post you have made. The fact that you can't grok this is pretty funny.
Jan 16, 2023
0
#5479
" I stated that Chess positions should take more CPU to evaluate than Go positions, one for one." - which is objectively incorrect.
MEGACHE3SE wrote:
" I stated that Chess positions should take more CPU to evaluate than Go positions, one for one." - which is objectively incorrect.
Well, I've made a logical case. I don't see you putting anything forth other than blather and quotes you don't understand yourself but that have given you some vague notion that you must be right.
I think the important thing is to have noticed the tone that I was using throughout, and to have honored that by matching it. That's the problem. I came back to say that in most cases you actually can't get past thirty moves, because when I go through the process over in Fritz that's what I discover. I guess it's all right to still come in here and say it, but man does it suck to have to enter back in to this thought process.
I don't know why you came back and then decided to confront the poster defending you rather then the poster that disagreed with you...but I guess you bridled at the "uninformed" characterization.