So What’s AI’s Dirty Little Secret?
One could read the massively hyped claims of the trillions in productivity gains and then how far AI still has to go for real-world application and end up quite befuddled. Not to mention some proclaiming AI taking over the world (that one still confuses me a bit).
There is one thing I agree on with an NYT piece explaining why they think AI is “stuck” so far away from practical implementation:
To get computers to think like humans, we need a new A.I. paradigm, one that places “top-down” and “bottom-up” knowledge on equal footing. Bottom-up knowledge is the kind of raw information we get directly from our senses, like patterns of light falling on our retina. Top-down knowledge comprises cognitive models of the world and how it works.
To prove the point that most approaches aren’t optimal, they go on to say that academic labs are too small to tackle properly integrating the many separate moving parts a full AI solution would require. On the other hand, corporate labs have the resources to tackle big questions, but in a world of quarterly reports and bottom lines, they tend to concentrate on narrow problems.
With some sectors seeing the incredible impact of AI already, those that are securing the right mix of talent and technology are pulling ahead of the competition markedly. So even though many initiatives may not be making the desired progress, as a whole, the market is moving very rapidly towards digital transformation. Having said that, AI is generally leveraged to produce insights, as a classifier, basically to generate knowledge- business is still required to make courageous decisions.
So in my opinion, the dirty little secret is that AI is only one small but very important part of a greater cognitive framework. Speaking of the “optimal approach” at diwo we’re making a quantum leap from data-driven insights and creating new knowledge to the realm of decision-making. Check out the new world of Cognitive Decision-Making and see why this business-first approach can deliver value on day one.
NYT article cited:
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