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How to choose an AI project that will succeed
Jose Quesada

After mentoring over 165 projects for AI Deep Dive/Data Science Retreat, Jose came with a set of rules to pick a good project. In this talk, he will cover:
How you don't need all that much data (Minimum viable corpus), thanks to pre-trained models
How your idea should pass the 'eyebrow test.'
How you only need to be in the ballpark of a good idea
How picking a problem that moves you helps to avoid pitfalls
How to produce unique data using hardware (sensors, cheap electronics)
How you need a gold standard
How computing at the edge avoid privacy problems
How to avoid projects with 'the gorilla problem.'

Bio: Jose has started businesses in Berlin, San Francisco and Toronto. Originally from Spain, he has lived in 10 countries. The companies he started to train people from literally all over the world. After more than 200 participants in 20 batches, he has a network in multiple locations that gives him a broad perspective. He studied Fine arts and psychology before doing his Ph.D. in Machine Learning in Boulder Colorado. He paid for studies by selling his paintings.

More: aigeeks.org and http://aideepdive.com/