How much did AlphaGo Zero cost? (2018)
101–110 of 179 posts
Re: How much did AlphaGo Zero cost? (2018)
#102Re: How much did AlphaGo Zero cost? (2018)
#103Earlier quoted context omitted.
Do we have algorithms that allow bipedal robots to walk at human level ? Or run at, let's say, 10th grade standard student level?
Bipedal walking and running on uneven terrain has been demonstrated years ago - Boston Dynamics has a lot of nice videos; e.g. here's a four year old video on walking https://www.youtube.com/watch?v=rVlhMGQgDkY , here's two year old videos on running https://www.youtube.com/watch?v=vjSohj-Iclc and https://www.youtube.com/watch?v=LikxFZZO2sk - perhaps it's debatable if it's "full human level" but it seems sufficient t…
Re: How much did AlphaGo Zero cost? (2018)
#104Earlier quoted context omitted.
Do we have algorithms that allow bipedal robots to walk at human level ? Or run at, let's say, 10th grade standard student level?
Yes. Here's Boston Dynamic's robot doing Parkour and gymnastics: https://www.youtube.com/watch?v=_sBBaNYex3E It's not national level gymnastics but it's better co-ordinated than most humans.
Re: How much did AlphaGo Zero cost? (2018)
#105Earlier quoted context omitted.
I think the problem you'd find is that "bit trained" is probably highly non-trivial. For example, I expect that the training required to go from 7-year-old child to Go grand master requires a completely different number of bits of information than the training required to go from blanks-late NN to NN Go Grand master. I also suspect that the difference in what is being learned may well dominate the difference in train…
Can't help but remark that "7-year-old child" is not a valid go rank. Some 7 year olds are surprisingly good at playing go :)
Re: How much did AlphaGo Zero cost? (2018)
#106Earlier quoted context omitted.
Is human&computer better than computer only?
Not really, humans barely provide insight (if anything), which chess engines don’t already consider. Deep Blue could evaluate 200 million different moves... per second. And that’s from 1997. The few and rare times an engine gets funky is usually in end-game positions where the engine can’t seem to find a sacrifice to win the game and will output a current position as drawn. These cases are few and I very much doubt t…
However I agree that the games between AlphaGo and Stockfish are really interesting. It strikes me that the AlphaGo version of chess looks a lot more human; it seems to place value on strategic ideas (activity, tempo, freedom of movement) that any human player would recognise.
Re: How much did AlphaGo Zero cost? (2018)
#107Alpha Go Zero inspired the development of an open source version, Leela Go Zero which Leela Chess Zero is forked from by the same guy who made Stock Fish. Lots of people contribute what I imagine are amounts of CPU Power/money to the Leela Chess Zero project[1]. Would love to see Alpha Chess vs Leela Chess. [1] https://training.lczero.org/ [edit] I've caused terrible confusion by melding Leela Go and Leela Chess when…
AFAIK Garry Kasparov to this day does computer&human vs. computer&human chess research, and it's far from a solved problem.
But Kasparov and others have given up on the idea that a human provides any unique insight into chess anymore. Computers are just better.
Re: How much did AlphaGo Zero cost? (2018)
#108Re: How much did AlphaGo Zero cost? (2018)
#109Earlier quoted context omitted.
AFAIK Garry Kasparov to this day does computer&human vs. computer&human chess research, and it's far from a solved problem.
Is human&computer better than computer only?
Re: How much did AlphaGo Zero cost? (2018)
#110Another way of thinking about how efficient the brain is: By the article’s numbers, about 5.5 million TPU hours were required to train the machine to play as well as a Go champion. A Go champion might have trained for 8 hours a day, for 15 years (age 5 to 20). That is about 40 000 hours. In other words, machines required 137 times longer to learn the game, and at twice the power consumption! There is still a lot of r…
>KataGo's latest run used about 29 GPUs, rather than thousands (like AlphaZero and ELF), first reached superhuman levels on that hardware in perhaps just three to six days, and reached strength similar to ELF in about 14 days. With minor adjustments and a few more GPUs, starting around 40 days it roughly began to match or surpass Leela Zero in some tests with different configurations, time controls, and hardware. And finally after about four months of training time, the current run may be wrapping up fairly soon, but we hope to be able to continue it or begin another run in the future.