Likelihood of discontinuous progress around the development of AGI
About AlphaZero particularly, a few things must be kept in mind.<p>First, AlphaZero still makes use of a Monte Carlo Tree Search algorithm to
search for good moves. MCTS is a powerful algorithm with a very limited scope:
zero-sum, perfect information games. So for instance, it would be very
difficult to see how to use MCTS-based AlphaZero in, e.g., training
self-driving cars.<p>Second, the AlphaZero architecture is precisely mapped onto a checkerboard and
will not learn anything about games that don&#x27;t use a checkerboard, or any
situation that is not possible to model as a game played on a checkerboard.<p>Third, the AlphaZero architecture is also precisely mapped onto the range of
moves of pieces in chess, shoggi and go. Again, AlphaZero would be useless in
any game that used pieces with different moves (e.g. a piece with a zig-zag
move, or a piece allowed to move in spirals etc).<p>All of the above of course can be mitigated with different architectural
choices, but to make those choices, implement them and validate them will take
a great deal of time.<p>So, AlphaZero doesn&#x27;t mean we&#x27;re closer to _general_ AI.
Quite the contrary: it&#x27;s a very specialised form of AI that will be very
difficult to use in any different task than chess, shoggi or go.