SiliconANGLE article by Tony Baer
Predictive and prescriptive analytics are different from voice recognition, which in turn is different from entity extraction, natural language query or content generation. Some problems require hard facts, while others just require a general idea.
A colleague of ours, Jason Bloomberg, summed it up nicely: It’s a matter of precision versus salience. At this point, ML or DL models are better-suited for providing more precise answers, while generative models will be best utilized for establishing context. In many cases, the choice of approach won’t be either-or, but an “ensemble” of different models that each solve parts of the problem that are assembled into a composite answer.
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