How to Pick between Traditional AI, Supervised Machine Learning, and Deep Learning [Thoughts]

In a pre-AI world, in order to build an application, you needed to reduce your idea to a process—a set of rules by which your software would operate to accomplish the goal you set. Sometimes this was easy; for example, a customer relationship manager like Salesforce is naturally reducible to rules.

In a post-AI world, you can build applications for ... See more

So how does deep learning do this? Fundamentally, these algorithms use massive amounts of data from a specific domain to make a decision that optimizes for a desired outcome. It does this by training itself to recognize deeply buried patterns and correlations connecting the many data points to the desired outcome. This pattern-finding process is ea

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By thinking about a ML problem first as a set of inputs and desired outputs, you can reason whether the input is even sufficient to predict the output. 

In a pre-AI world, you needed to define the rules of the game you were playing—to think from first principles and apply them to your circumstances. In a post-AI world, you need to build and use models that recognize underlying patterns—patterns that can’t be reduced to simple rules.

Consider building software. Pre-AI, you needed to define exactly wh... See more