I still think the hardest part of poker is the grind. The computer doesn't get bored or tired and play hands it doesn't have a reason too just because they are stuck in a dead streak. Taking a mostly conservative style, you'd expect the computer to out perform over time.
It would be curious to know what percentage of the time the players bluffed the AI successfully and vice versa.
An additional player requires some sort of modeling of the interaction between players, which may not be feasible. For example, Player A may have multiple co-optimal strategies with respect to his own EV, but that affects the EVs for players B and C differently. Player A can choose arbitrarily between these strategies at any frequency, but players B and C can't predict this choice at all.
On top of that, Nash equilibrium requires that each player acts independently in their best interest. Teams can be modeled as a single player if necessary, but shifting alliances over the course of a series of hands can't be easily.
And on the pure computational complexity side, the state space explodes when you can have more than one opponent in a hand simultaneously. Combinations of players in a hand scales as n!, not n.