Former poker pro here.
Top professionals are building their strategy around game theory. They'll attempt to play in such a way that they aren't exploitable and look to deviate when they've spotted a weakness in their opponent's play.
Basically, the game theory optimal strategy is unexploitable. In every situation, the best you can do is break even by also playing the optimal strategy. If you deviate from optimal strategy, the optimal strategy will beat you, but it's possible that a strategy tailored to taking advantage of your specific deviations would beat you more quickly.
Unexploitable play typically means that you bet a size with a range of holdings that would make your opponent indifferent to all of his options (And the converse is true when facing a bet). For humans, this means that they gravitate to a few standard bet sizes, while a computer could, in theory, balance their range with much more granularity.
Last I read, for training the neural net it'll play billions+ hands against versions of itself designed to exploit various weaknesses. It'll start out by performing random actions, for example, say it'll have a 33% chance to call your bet, raise, or fold. It then starts to see that it does better when it raises your bet with the nuts and also as a bluff. Eventually, it arrives at an equilibrium strategy.
Since computers are much better at randomness than humans are, they're able to more effectively play these types of strategies and with more complexity of bet sizing. There is what's called a mixed strategy, a strategy where given a situation with the same hole cards you will call, raise, or fold to a bet with some non-zero probability. Doing that as a human is very difficult, but it's something computers manage to do quite easily.