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What advice would you have for someone with a computer science background who wants to make a dent in AI research? How achievable is it?
Making progress towards more flexible AI, equipped with generalizable abilities rather than specific skills, is definitely doable today. But it does require broadening the scope of your research beyond pattern recognition methods (such as deep learning)
Which current sub field of ML do you find most promising for generality? My intuition would be Reinforcement Learning and Genetic Algorithms, because they don’t require human labeled data to build. But they do suffer acutely from task specificity as well..
Flexible and broad AI will come from a combination of techniques, including pattern recognition. I see program synthesis and in particular genetic programming as holding potential. But really, we should explore more.
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