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Q for Noah Gift: How to judge whether AI tools are an appropriate solution

 
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Noah,

I am just starting with a cloud-related project and am thinking that there are at least some aspects of what we're doing that might be tackled using AI-based tools. Do you have any tips on what to look for when sussing out a problem to see if AI is a suitable approach?

Gary
 
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Gary,

My recommendation is to use a greedy algorithm and I have a simulation for proof:  https://github.com/noahgift/or/blob/master/tsp_greedy_random_start.py.  In this approach to solving the traveling salesman problem, I randomly choose a starting point and then always pick the shortest path.

For solving many real-world problems, this approach makes sense.  Step one would be to look at the provider of the APIs. If they are leaders in the space:  Amazon, Microsoft and Google in that order, then they are safe choice to build solutions on top of:   https://www.zdnet.com/article/google-cloud-platform-breaks-into-leader-category-in-gartners-magic-quadrant/.  Then try out the AI API or service, like say, Google AutoML or Amazon Rekognition.  If it solves the problem for your needs, your done, if not, try another company, if that doesn't work then train the model yourself, and use a managed service like AWS Sagemaker.

This is the way I think, and believe for 80-90% of people working in AI, they will be served best by the greedy approach.
 
Gary W. Lucas
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Noah,

Thanks. I like your metaphor.  In this case, it strikes me as being excellent advice.


Gary
 
Don't get me started about those stupid light bulbs.
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