Answers.Body: <p>While I was in the middle of writing this question I came up with a probable answer, so I'll write it here. AlphaZero is actually running through the same positions <em>far more</em> than 10,000 times, it's just doing it on a set of positions roughly 10,000 large. So each position has many playouts run on it, each >= in length than the last.</p>
  
  <p>Stockfish looks at millions of positions and evaluates each only once (not taking things like iterative deepening search into account). Meanwhile, AlphaZero repeatedly looks at promising branches based off their previous preformance. This explains why it only looks at 10,000 moves, since it's usually only sampling the best it can find.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-01-09T15:30:29.870Z
Answers.Text: No, there is absolutely no sense in running the same evaluation algorithm on the same position many times as the answer will be the same each time.
Answers.UserDisplayName: RemcoGerlich
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Answers.CreationDate: 2019-01-09T17:40:13.043Z
Answers.Text: I meant playout simulations.
Answers.UserDisplayName: Inertial Ignorance
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Answers.CreationDate: 2019-03-04T01:31:58.337Z
Answers.Text: A0 does not do playout simulations.
Answers.UserDisplayName: Oscar Smith
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Answers.CreationDate: 2019-03-04T06:41:35.953Z
Answers.Text: @Oscar Smith yees
Answers.UserDisplayName: Inertial Ignorance
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Answers.LastEditDate: 2019-01-09T17:40:04.260Z
Answers.UserDisplayName: Inertial Ignorance
Answers.Body: <p>Because alphazero's evaluation algorithm is far more complex and takes up way more computing power than normal chess engines evaluation algorithm.</p>
  
  <p>In fact if you were to fairly compute how much processing power each engine uses, no doubt alphazero takes up way more power to beat normal engines.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-01-14T00:01:50.977Z
Answers.Text: That's certainly not the case. MCTS is a well-known algorithm that's been widely applied (see e.g. Komodo MCTS). Leela is also an adaptation of AlphaZero that's capable of giving Stockfish a run for its money on quite normal, commercially-available hardware.
Answers.UserDisplayName: Allure
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Answers.Text: @Allure leela is an open source engine that has been subject to who knows how much training. The computing power to fine tune itself before the game itself needs to be accounted for. The point of machine learning is to use up less computing power on a problem never encountered before. A fair comparison would be leela vs stockfish the same amount of training time and computing power using the same time a computer programmer would make stockfish.
Answers.UserDisplayName: Matthew Liu
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Answers.CreationDate: 2019-01-09T15:35:37.313Z
Answers.LastActivityDate: 2019-01-09T15:35:37.313Z
Answers.UserDisplayName: Matthew Liu
Answers.Body: <p>Very simple. Running a large neural network with floating numbers can’t be quicker than running a simple C++ function on integers.</p>
  
  <p>AI machine learning is not new to chess. There were serious attempts before Google established. Unfortunately, nobody had the determination, skills and resources to do a good job. Nobody wanted to invest money. Before Google's chess journey, the chess engine community believed:</p>
  
  <blockquote>
    <p>AI chess will not beat classical programming because neural networks
    (or other models) run much slower.</p>
  </blockquote>
  
Answers.ContentLicense: CC BY-SA 4.0
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Answers.Text: Any reference for this quote?
Answers.UserDisplayName: Kortchnoi
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Answers.CreationDate: 2019-01-11T00:34:34.403Z
Answers.Text: @Kortchnoi It's not a quote it's understanding.
Answers.UserDisplayName: SmallChess
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Answers.Text: @Kortchnoi It's essentially a mini "brain" evaluating a position versus some standard C++ functions. It makes sense that the brain has orders of magnitude more complexity.
Answers.UserDisplayName: Inertial Ignorance
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Answers.CreationDate: 2019-01-12T08:30:05.250Z
Answers.Text: @InertialIgnorance the last quote makes much sens to me but I was looking for a reference, i.e. someone who had written that "prediction" in the past.
Answers.UserDisplayName: Kortchnoi
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Answers.CreationDate: 2019-01-12T20:19:04.907Z
Answers.Text: @Kortchnoi Not sure about that then. SmallChess might have been paraphrasing the general consensus, I'm not sure if it was a quote.
Answers.UserDisplayName: Inertial Ignorance
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-01-13T10:01:43.707Z
Answers.Text: @InertialIgnorance Correct. It was not a quote. It was general consensus.
Answers.UserDisplayName: SmallChess
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-01-13T10:02:04.630Z
Answers.Text: @Kortchnoi If you would like a quote, please start a new question.
Answers.UserDisplayName: SmallChess
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-01-13T21:50:31.430Z
Answers.Text: @SmallChess done [here](https://chess.stackexchange.com/questions/23499/alphazero-and-the-revenge-of-the-artificial-intelligence)
Answers.UserDisplayName: Kortchnoi
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Answers.CreationDate: 2019-01-09T09:16:55.877Z
Answers.LastActivityDate: 2019-01-09T09:25:09.770Z
Answers.LastEditDate: 2019-01-09T09:25:09.770Z
Answers.UserDisplayName: SmallChess
Body: <p>According to Deep mind's <a href="https://deepmind.com/blog/alphazero-shedding-new-light-grand-games-chess-shogi-and-go/" rel="nofollow noreferrer">article</a>, Alpha Zero searches roughly 10,000 moves per decision, while Stockfish is around 10,000,000 moves. I'm aware that Alpha Zero uses Monte Carlo Tree Search while Stockfish uses minimax, but why would this cause 1000 times less moves to be considered? </p>
  
Tags: <engines><stockfish><calculation><alphazero>
Title: Why does AlphaZero evaluate on the order of 1000 times less moves than Stockfish?
ThreadText: # Why does AlphaZero evaluate on the order of 1000 times less moves than Stockfish?
  
  (Asked by: username_0 on 2019-01-09)
  
  According to Deep mind's [article](https://deepmind.com/blog/alphazero-shedding-new-light-grand-games-chess-shogi-and-go/), Alpha Zero searches roughly 10,000 moves per decision, while Stockfish is around 10,000,000 moves. I'm aware that Alpha Zero uses Monte Carlo Tree Search while Stockfish uses minimax, but why would this cause 1000 times less moves to be considered?
  
  **Tags:** engines, stockfish, calculation, alphazero
  
  
  ---
  
  ## 3 answers
  
  ### Answer by username_5 on 2019-01-09. Score: 4 | Accepted answer
  
  Very simple. Running a large neural network with floating numbers can’t be quicker than running a simple C++ function on integers.
  
  AI machine learning is not new to chess. There were serious attempts before Google established. Unfortunately, nobody had the determination, skills and resources to do a good job. Nobody wanted to invest money. Before Google's chess journey, the chess engine community believed:
  
  > AI chess will not beat classical programming because neural networks
  > (or other models) run much slower.
  
  > **Comments:**
  > **username_6**: Any reference for this quote?  
  > **username_5**: @username_6 It's not a quote it's understanding.  
  > **username_0**: @username_6 It's essentially a mini "brain" evaluating a position versus some standard C++ functions. It makes sense that the brain has orders of magnitude more complexity.  
  > **username_6**: @username_0 the last quote makes much sens to me but I was looking for a reference, i.e. someone who had written that "prediction" in the past.  
  > **username_0**: @username_6 Not sure about that then. username_5 might have been paraphrasing the general consensus, I'm not sure if it was a quote.  
  > **username_5**: @username_0 Correct. It was not a quote. It was general consensus.  
  > **username_5**: @username_6 If you would like a quote, please start a new question.  
  > **username_6**: @username_5 done [here](https://chess.stackexchange.com/questions/23499/alphazero-and-the-revenge-of-the-artificial-intelligence)  
  
  ---
  
  ### Answer by username_0 on 2019-01-09. Score: 0
  
  While I was in the middle of writing this question I came up with a probable answer, so I'll write it here. AlphaZero is actually running through the same positions *far more* than 10,000 times, it's just doing it on a set of positions roughly 10,000 large. So each position has many playouts run on it, each >= in length than the last.
  
  Stockfish looks at millions of positions and evaluates each only once (not taking things like iterative deepening search into account). Meanwhile, AlphaZero repeatedly looks at promising branches based off their previous preformance. This explains why it only looks at 10,000 moves, since it's usually only sampling the best it can find.
  
  > **Comments:**
  > **username_1**: No, there is absolutely no sense in running the same evaluation algorithm on the same position many times as the answer will be the same each time.  
  > **username_0**: I meant playout simulations.  
  > **username_2**: A0 does not do playout simulations.  
  > **username_0**: @username_2 yees  
  
  ---
  
  ### Answer by username_3 on 2019-01-09. Score: -1
  
  Because alphazero's evaluation algorithm is far more complex and takes up way more computing power than normal chess engines evaluation algorithm.
  
  In fact if you were to fairly compute how much processing power each engine uses, no doubt alphazero takes up way more power to beat normal engines.
  
  > **Comments:**
  > **username_4**: That's certainly not the case. MCTS is a well-known algorithm that's been widely applied (see e.g. Komodo MCTS). Leela is also an adaptation of AlphaZero that's capable of giving Stockfish a run for its money on quite normal, commercially-available hardware.  
  > **username_3**: @username_4 leela is an open source engine that has been subject to who knows how much training. The computing power to fine tune itself before the game itself needs to be accounted for. The point of machine learning is to use up less computing power on a problem never encountered before. A fair comparison would be leela vs stockfish the same amount of training time and computing power using the same time a computer programmer would make stockfish.  
  
  ---
  
  