Originally published in Forbes When Henry Castellanos first presented his machine learning model to his company’s executives, he found himself fighting off a certain self-doubt that is so common among data professionals, it’s almost universal. On one hand, his model looked great. It did a sturdy job predicting which dental patients would fail to show
Originally published in Forbes Most predictive AI projects fail to launch into production. The number crunching is sound and the data scientist delivers a viable machine learning model – but stakeholder objections sadly preclude deployment. To better meet stakeholders where they are,...
Originally published in Forbes After decades chairing and keynoting myriad machine learning conferences, I have witnessed time and again that event programs often signal emerging industry trends. This year, I’m chairing an event where a couple dozen enterprises...
Originally published in Forbes Generative AI and predictive AI ought to live together in harmony. They solve different problems and present distinct value propositions, so they should compete no more than a water park and a ski resort....
Originally published in Forbes The future is the ultimate unknown. There’s no more coveted business knowledge than, “What’s going to happen?” Yet, since we can’t eliminate uncertainty, we can only do the next best thing: Manage it....
Originally published in AI Realized Now “Shouldn’t a great model be a sure bet to deploy?” Eric Siegel opened his AI Realized keynote by answering his own question. A technically strong model is not a sure bet,...
Originally published in Forbes Predictive AI offers tremendous potential – but it has a notoriously poor track record. Outside Big Tech and a handful of other leading companies, most initiatives fail to deploy, never realizing value. Why?...
Originally published in Forbes Predictive AI and generative AI are two very different animals that, it turns out, desperately need one another. Since they serve different purposes, projects that employ them are often siloed away from each...
Originally published in Forbes Executives know the importance of predictive AI. As Unilever CDO Morgan Vawter wrote, “Its practical deployment represents the forefront of human progress: improving operations with science.” But there’s bad news for data scientists: Your predictive...
Originally published in Forbes To know that we’re in an AI bubble, you don’t need OpenAI chair Bret Taylor or Databricks CEO Ali Ghodsi to admit it, as they have. Nor do you need to analyze the telltale economics of...
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