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> but it's surprising that the pattern recognition coupled with some tree search seems to be all you need to play Go as well as humans. Is it really all we nee

by nazka 11y ago

> but it's surprising that the pattern recognition coupled with some tree search seems to be all you need to play Go as well as humans. Is it really all we need? Or it is more that they threw a lot of hardware to it? What if if a part of its efficiency is because they threw a lot of GPUs with a huge network, rather than having a NN efficient by itself? We see that: "AlphaGos Elo when it beat Fan Hui was 3140 using 1202 CPUs and 176 GPUs. Lee Sedol has an equivalent Elo to 3515 on the same scale (Elos on different scales aren't directly comparable). For each doubling of computer resources AlphaGo gains about 60 points of Elo." It's a lot of hardware.

javierluraschi 11y ago
What does a lot of hardware means? The human brain has about 100B neurons with about 100+ dendrites per neuron, while AlphaGo has about 1K CPUs with about 2B transistors per CPU.
- nazka 11y ago
  I am wondering how much the amount of hardware they used had an effect on the bottom line, compared to the wisdom of their algorithm. Everybody knows it's a great step in AI. But how much? How much their algorithm is smart? Or simply put did they overfit by throwing a lot of layers and GPUs to the task? Or the algorithm is truly smart? What is the ratio of that. It is the same question for the data they used. Facebook, Google and others seem to agree that, at the end, the quantity and quality of data are more important than the algorithm itself. So how much is it at play here? Knowing that will be able to show us why it is performing well and how much we can appreciate their work.
  - javierluraschi 11y ago
    You can take a look at their paper... http://airesearch.com/wp-content/uploads/2016/01/deepmind-mastering-go.pdf http://airesearch.com/wp-content/uploads/2016/01/deepmind-ma... Basically, the ("lots of hardware") distributed implementation gets ~3100 points in the Elo rating against ~2900. ~2900 is still sufficient to win against Fan Hui. So I would say, that yes, this algorithm has most of the merit here.

by nazka 11y ago

javierluraschi 11y ago

What does a lot of hardware means? The human brain has about 100B neurons with about 100+ dendrites per neuron, while AlphaGo has about 1K CPUs with about 2B transistors per CPU.

nazka 11y ago
I am wondering how much the amount of hardware they used had an effect on the bottom line, compared to the wisdom of their algorithm. Everybody knows it's a great step in AI. But how much? How much their algorithm is smart? Or simply put did they overfit by throwing a lot of layers and GPUs to the task? Or the algorithm is truly smart? What is the ratio of that. It is the same question for the data they used. Facebook, Google and others seem to agree that, at the end, the quantity and quality of data are more important than the algorithm itself. So how much is it at play here? Knowing that will be able to show us why it is performing well and how much we can appreciate their work.
- javierluraschi 11y ago
  You can take a look at their paper... http://airesearch.com/wp-content/uploads/2016/01/deepmind-mastering-go.pdf http://airesearch.com/wp-content/uploads/2016/01/deepmind-ma... Basically, the ("lots of hardware") distributed implementation gets ~3100 points in the Elo rating against ~2900. ~2900 is still sufficient to win against Fan Hui. So I would say, that yes, this algorithm has most of the merit here.