The latest advances in
AI have provided
innovative techniques
that apply multi-
pronged approaches
to solve problems.
The second approach was an "end-game solver" that
would look at the current state of play and then help
focus the counterfactual regret minimization algo-
rithm. This was important because the primary algo-
rithm no longer had to run through all possibilities.
Libratus didn’t just learn from modeling prior match
results; it also learned while it was playing.
The third approach dealt with scenarios where the
opponent recognized certain patterns of play and
began to exploit them. The third algorithm identified
those patterns and removed them. This three-
pronged approach was both innovative and effective,
producing a system that could actually out-bluff a human.
Where Else Might This Apply?
These advances in AI are exciting for a few reasons.
For one, they keep tackling more difficult problems.
In addition, the speed at which these advances are
being made appears to be accelerating. Finally, the
algorithms are becoming more efficient so they
require less compute resources to run.
There are numerous problems that can now be tar-
geted with these new approaches, and for the pur-
pose discussing these we will look at them in three
distinct categories: Pattern Recognition, Human
Behavior and a Combination of the two.
Pattern Recognition
Pattern recognition is a key component of human
perception and it occurs within the neocortex. Any
data where the recognition of known patterns and
identification of anomalies to those known patterns
can be tackled with these techniques.
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Some examples include:
Cybersecurity – In this domain, network traffic rep-
resents vast amounts of data streaming in real time.
Identifying known and acceptable patterns in this
flow of data as well as patterns that are not recog-
nized can help flag potential security breaches and
take action to stop them immediately.
Medical Diagnoses – Whether it might be the identi-
fication of patterns of symptoms across medical
records or recognizing potential problems from med-
ical imaging that may escape detection by the human
eye, these new AI techniques can assist medical pro-
fessionals to provide even better levels of services
that can help save lives.
Legal – Think of all the time lawyers spend reviewing
contracts. This is a perfect problem to be solved by
AI, where known patterns of legal verbiage can be
identified and exceptions can be highlighted for
review by human lawyers.
Human Behavior
Poker represented a problem with imperfect infor-
mation and the need to identify patterns of human
behavior. Below are some examples where modern AI
might be applied in similar situations:
Capital Markets Trading – This is a place where his-
torical data is combined with human traits such as
fear and greed, with a little herd mentality added to
the excitement. Some of the new AI techniques have
the potential to improve performance and this could
lead to significant profits.
Psychoanalysis – This is a field in which new services
are appearing online to provide patients with more
timely and cost effective solutions. AI techniques can
be used to identify behavior patterns, coax informa-
tion from patients and offer everything from advice
to recommendations of appropriate medical profes-
sionals to consult with.
Business and Political Negotiations – There are lots
of similarities between these situations and poker,
including imperfect information, bluffing and
attempting to maximize gain. Modern AI could be
used to assist the humans involved in negotiations to
help optimize individual outcomes.