user4418: The new Komodo 13 MCTS has been announced with the claim that:

Komodo 13 MCTS thinks like no other chess engine in the world.
  Inspired by the ideas of AlphaZero and Leela, Larry and Mark set out
  to reinvent Komodo. What they came up with was Komodo 13 MCTS - a
  engine which searches for candidate moves in an incredible new way,
  and finds moves no other engine can

They are clearly trying to cash in on the publicity behind AlphaZero and LeelaZero. But is the hype justified? 
There seems to be no mention of an AlphaZero like database of training results. Is the use of MCTS on its own enough to produce worthwhile improvements? More detailed information seems to be hard to find (possibly for commercial reasons).

user12873: Komodo doesn't use machine learning, it just uses roughly the same search algorithm that A0/L0 uses. It still relies on the human-built heuristics it's used.

user10075: There are a number of benefits to using MCTS instead of alpha-beta search, mainly in the realm of analysis.
Firstly, Alpha-Beta Search only attempts to find the best move in a position. As a result, MultiPV is implemented in alpha-beta engines by searching all the root moves, then searching the root again, skipping the root move, then searching again skipping the two already-found root moves, etc. 
This significantly reduces the strength of alpha-beta engines in analysis, where you often want to take a look at multiple possible variations. MCTS, by contrast, expands out portions of the whole tree making the PV of every move considered by MCTS available. There is therefore no strength hit when enabling MultiPV for MCTS engines, and Komodo MCTS can therefore be much stronger than alpha-beta engines when MultiPV is set to high values.
With regards to the results of the search, MCTS has the advantage of being able to reflect the possibility of the opponent going wrong, as it assumes that all reasonable moves have some chance of being chosen. By contrast, alpha-beta engines always assume that the opponent will play the move that the engine considers best.
As a result, alpha-beta engines can often evaluate situations which are deadly tactical landmines to be dead draws, whereas Komodo MCTS can take this into account, further improving its performance in analysis of human games.

user15223: Komodo MCTS isn't a neural-network based engine. It just uses a different search algorithm, in particular MCTS instead of AB. Alphazero also used MCTS, so KMCTS is an "Alphazero lite" in that sense; however a distinguishing factor of Alphzero is that it uses a neural network to perform the evaluation, and KMCTS does not do that.
Is MCTS "better" than AB? Yes and no. From what I've seen, MCTS is exceptionally better when you want multiple PVs (because they effectively get it for free, while AB engines need to spend computational power). However MCTS loses firepower in tactical shoot-outs, and it's also really bad at winning a technical position. For example I remember seeing a KMCTS game in TCEC where its eval read "I have a forced checkmate" one move and then "wait, I don't, I only have a very large advantage" another, and then back to "I have a forced checkmate", etc.
Having said all that, KMCTS eliminated regular Komodo from the latest TCEC cup, so it's absolutely a respectable engine. In a straight-up game against another engine, it's not as strong as Stockfish or Leela, but it's comparable to everything else.

4418: <p>The new Komodo 13 MCTS has been <a href="https://komodochess.com/Komodo13.htm" rel="nofollow noreferrer">announced</a> with the claim that:</p>

<blockquote>
  <p>Komodo 13 MCTS thinks like no other chess engine in the world.
  Inspired by the ideas of AlphaZero and Leela, Larry and Mark set out
  to reinvent Komodo. What they came up with was Komodo 13 MCTS - a
  engine which searches for candidate moves in an incredible new way,
  and finds moves no other engine can</p>
</blockquote>

<p>They are clearly trying to cash in on the publicity behind AlphaZero and LeelaZero. But is the hype justified? </p>

<p>There seems to be no mention of an AlphaZero like database of training results. Is the use of MCTS on its own enough to produce worthwhile improvements? More detailed information seems to be hard to find (possibly for commercial reasons).</p>
 12873: <p>Komodo doesn't use machine learning, it just uses roughly the same search algorithm that A0/L0 uses. It still relies on the human-built heuristics it's used.</p>
 10075: <p>There are a number of benefits to using MCTS instead of alpha-beta search, mainly in the realm of analysis.</p>

<p>Firstly, Alpha-Beta Search only attempts to find the best move in a position. As a result, MultiPV is implemented in alpha-beta engines by searching all the root moves, then searching the root again, skipping the root move, then searching again skipping the two already-found root moves, etc. </p>

<p>This significantly reduces the strength of alpha-beta engines in analysis, where you often want to take a look at multiple possible variations. MCTS, by contrast, expands out portions of the whole tree making the PV of every move considered by MCTS available. There is therefore no strength hit when enabling MultiPV for MCTS engines, and Komodo MCTS can therefore be <a href="http://talkchess.com/forum3/viewtopic.php?f=2&amp;t=70681" rel="nofollow noreferrer">much stronger than alpha-beta engines when MultiPV is set to high values</a>.</p>

<p>With regards to the results of the search, MCTS has the advantage of being able to reflect the possibility of the opponent going wrong, as it assumes that all reasonable moves have some chance of being chosen. By contrast, alpha-beta engines always assume that the opponent will play the move that the engine considers best.</p>

<p>As a result, alpha-beta engines can often evaluate situations which are deadly tactical landmines to be dead draws, whereas Komodo MCTS can take this into account, further improving its performance in analysis of human games.</p>
 15223: <p>Komodo MCTS isn't a neural-network based engine. It just uses a different search algorithm, in particular MCTS instead of AB. Alphazero also used MCTS, so KMCTS is an "Alphazero lite" in that sense; however a distinguishing factor of Alphzero is that it uses a neural network to perform the evaluation, and KMCTS does not do that.</p>

<p>Is MCTS "better" than AB? Yes and no. From what I've seen, MCTS is exceptionally better when you want multiple PVs (because they effectively get it for free, while AB engines need to spend computational power). However MCTS loses firepower in tactical shoot-outs, and it's also really bad at winning a technical position. For example I remember seeing a KMCTS game in TCEC where its eval read "I have a forced checkmate" one move and then "wait, I don't, I only have a very large advantage" another, and then back to "I have a forced checkmate", etc.</p>

<p>Having said all that, KMCTS eliminated regular Komodo from the latest TCEC cup, so it's absolutely a respectable engine. In a straight-up game against another engine, it's not as strong as Stockfish or Leela, but it's comparable to everything else.</p>
