Perhaps I missed it in the article, but these hands were played online, not live, right?
Also, I think it's pretty interesting that it wasn't until the 30k hand mark that the AI started to become consistently profitable, and it wasn't until 80k hands played that this profitably was statistically greater than 0. I think this suggests that the AI's ability to win isn't from some sort fundamentally better strategy against all opppnents, rather, its improved ability to learn from opponents and exploit them over a large sample size. This bot can't just sit down at a random online table and start crushing, which is a good thing.
Yeah, it may well be so for the first time, but after a few months of continuous playing the AI should be able to squash all competition at once, at the first game. It is basically the same with chess, though AI doesn't seem to be used there so much. Chess bots use, for example, opening and endgame databases so they don't need to play every game from a cold start, so to speak. This roughly corresponds to the level of AI "expertise" in playing poker acquired after a number of games.
This is what we humans call experience.