[ExI] Superhuman Poker

[Dylan Distasio]

Agree with everything said here.  While these results on the surface are
impressive, they are also very brittle.

The inability of self driving cars to get anywhere near the level 5
endpoint is a great example to demonstrate how little actual intelligence
is behind these algos.   Once (big IF) we see Level 5 self driving cars
that can perform as well or better as humans in all conditions and
circumstances, I will start to worry about the rise of AI and the
singularity.

On Thu, Jul 18, 2019 at 10:41 AM Dave Sill <sparge at gmail.com> wrote:

> On Thu, Jul 18, 2019 at 9:06 AM John Clark <johnkclark at gmail.com> wrote:
>
>> On Thu, Jul 18, 2019 at 8:05 AM Dave Sill <sparge at gmail.com> wrote:
>>
>> *> Unlike the human genius, the poker program can't talk or understand
>>> speech or converse in any language. It's like an idiot savant. If if could
>>> talk, it'd just say "I just pick the statistically best play".*
>>>
>>
>> People were always asking human geniuses like Einstein and Feynman how
>> they got their ideas but they could never give satisfactory answers, if
>> they could we'd all be as smart as they were.
>>
>
> At least Einstein and Feynman could talk intelligently about abstract
> concepts. But, no, I don't think that knowing how they got their ideas
> would one as smart as they were. They weren't special because of their
> knowledge, they were special because of their intelligence.
>
> *> Machine learning isn't self-modifying code. The code never changes. The
>>> learning process builds huge tables of statistics recording the outcomes of
>>> different plays.*
>>>
>>
>> I don't know what you mean by that, the changes that the program made in
>> its own code is the very thing that made it extraordinary; if it only
>> used the code that the humans had written it would play lousy Poker.
>>
>
> You're mistaken about how it works. From
> https://www.nature.com/articles/d41586-019-02156-9:
>
>
>
>
>
>
> *The key breakthrough was developing a method that allowed Pluribus to
> make good choices after looking ahead only a few moves rather than to the
> end of the game.Pluribus teaches itself from scratch using a form of
> reinforcement learning similar to that used by DeepMind’s Go AI, AlphaZero.
> It starts off playing poker randomly and improves as it works out which
> actions win more money. After each hand, it looks back at how it played and
> checks whether it would have made more money with different actions, such
> as raising rather than sticking to a bet. If the alternatives lead to
> better outcomes, it will be more likely to choose theme in future.By
> playing trillions of hands of poker against itself, Pluribus created a
> basic strategy that it draws on in matches. At each decision point, it
> compares the state of the game with its blueprint and searches a few moves
> ahead to see how the action played out. It then decides whether it can
> improve on it. And because it taught itself to play without human input,
> the AI settled on a few strategies that human players tend not to use.*
>
> Pluribus isn't modifying it's own code. When I said it'd say "I just pick
> the statistically best play", that was overly simplified. It more like "I
> pick the statistically best play and continually look at my previous play
> and try different things and adjust the probabilities so I can do better
> next time".
>
> *> These AIs are learning very narrowly-defined games in very simple
>>> domains and a tiny set of well-defined rules.*
>>>
>>
>> I think you're whistling through the graveyard. Everyday the field of
>> AI's expertise becomes less narrow, and the super impressive thing is we
>> didn't teach them how to do it, they taught themselves.
>>
>
> I think you're anthropomorphizing.
>
> *> What they do is impressive to us in the same way that a calculator is
>>> impressive to us at doing arithmetic. *
>>>
>>
>> A calculator doesn't get better at arithmetic every day and it can't
>> teach itself things.
>>
>
> I didn't say it was the same thing, just impressive in the same way.
>
> Things become unstable and unpredictable when the tool becomes more
>>> intelagent than the tool user. It's called a singularity.
>>>
>>
> Intelligence isn't everything, John. You have to consider motivation,
> drive, understanding, knowledge, abilities, etc.
>
> -Dave
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