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Machine Learning

What We’ve Learned About Success With AI Projects

Mark Heid   

Besides making full use of best-in-class open source tools, what else is critical to move an AI project from conception to scale – with measurable results?

At the Fidelity Center for Applied Technology (FCAT) our project teams focus heavily on design research, heterogeneous opinions, business co-design and quantitative measures of value, at scale.

This talk will cover our approach to AI projects in FCAT at a high level (with examples) – the good, the bad and the ugly. There is no single recipe for success. But, there are best practices and ‘know-how’ that can be the difference between ‘ho-hum’ outcomes and true breakthroughs.