As firms are finding out, the unit economics of AI/ML is not exactly like software. It requires more manual manipulation of data than one might expect – including ingesting data, cleaning data, tuning models – and deployment doesn’t scale like pure software does. Every customer has their own unique datasets. The Department of Defense has had enough trouble adapting its hardware-oriented acquisition system to buying software. Will AI/ML present an even greater challenge or does it lend itself to the traditional labor services model? The Center for Government Contracting of the George Mason University School of Business and the Wharton Aerospace Community co-hosted an important discussion on the scalability, unit economics and cost estimating methodologies of AI/ML projects with a tremendous panel including: Sheldon Fernandez, CEO of Darwin AI; Ryan Connell, DCMA Commercial Pricing; and Diego Oppenheimer, CEO with Algorithmia with his colleague Craig Perrin. The panel is moderated by Ellen Chang. This podcast was produced by Eric Lofgren. Soundtrack by urmymuse: "reflections of u". You can follow us on Twitter @AcqTalk and find more information at AcquisitionTalk.com.
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Event: What's the price of an AI/ML product?
acquisitiontalk.substack.com
Event: What's the price of an AI/ML product?
Jul 02, 2021
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Event: What's the price of an AI/ML product?