Forbes November 18, 2024
Why in the world would the decades-old industry of machine learning need a completely new paradigm?
Imagine you’re developing a rocket. If you don’t stress test it—in its intended usage (via simulations, wind tunnels, etc.)—then its launch will be a shot in the dark, if not entirely scrubbed by sensible decision makers.
That’s the status of most enterprise ML projects, aka predictive AI. The industry hasn’t matured to the point where such pre-launch stress testing is commonplace. As a result, most predictive AI deployments are scrubbed. Its great potential is clear and many projects achieve it—but many more don’t.
Predictive AI’s dismal track record is readily avoidable. The first and most fundamental remedy would be to routinely establish its business...
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