Data sets are fundamental building blocks of AI systems, and this paradigm isn’t likely to ever change. Without a corpus on which to draw, as human beings employ daily, models can’t learn the relationships that inform their predictions.
But why stop at a single corpus? An intriguing by ABI Research anticipates that while the total installed base of AI devices will grow from 2.69 billion in 2019 to 4.47 billion in 2024, comparatively few will be interoperable in the short term. Rather than combine the gigabytes to petabytes of data flowing through them into a single AI model or framework, they’ll work independently and heterogeneously to make sense of the data they’re fed.
That’s unfortunate, argues ABI, because of the insights that might be gleaned