Machine Learning not a panacea. About a year ago, Len Jordan, Managing director at Seattle based Madrona Ventures Group, upon finding out, we make a ML software product, looked me in the eye and said, “Vinay, I am not an expert in Machine Learning. What you have to do is – convince at least some portion of prospects not to implement machine learning. Just try to talk them out of it!” Simple advice. It ties nicely into “Machine Learning is not a Panacea” statement. Every problem can be characterized by data. Every bit of data, be it image, audio, video or tabular can be turned into numbers and math. Every problem can be turned to numbers and math. A the solution can be attempted with machine learning. The question is whether machine learning is likely to produce a model that is, A) Accurate, B) Simplifies a solution without loss of accuracy C) In use cases where it matters, it must be robust, traceable and interpretable I suggest folks interested in this topic to check out https://lnkd.in/gxMvqE8 and https://lnkd.in/gMvKkBA These articles go deeper into “What #MachineLearning Can and Cannot do” #Datascientist #Dask #Rapids #Dataengineer #HPC

What Machine Learning Can and Cannot Do

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Artificial intelligence is rapidly becoming one of the most important technologies of our era. Every day we can read about the latest AI advances from startups and large companies. Over the past few years, the necessary ingredients have come together…

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