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  • CIS
    Members: Free
    IEEE Members: Free
    Non-members: Free
    Duration: 00:18:29
20 Jul 2022

Knowledge-driven expert systems have been considered "too brittle/fragile" for real-world applications.
Well-engineered
brute-force end-2-end machine-learning solutions are often considered a
practical approach to overcome expert systems limitations.
But the
experience in real world projects shows that this is not true, and both
approach "alone" are often doomed to failure when a model needs to be
put into work in a real-world scenario.

In this presentation I will try to:Promote a culture of critical evaluation of ML solutions (no myths, no magic, no free lunch, complexity requires hard work :) )Present
Expert.ai current approach (which is not perfect and could suffer from a
number of the issues I will be presenting) and possible future
directions.

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