Data scientists are producing models that are making substantial contributions to the business, and thus more and more models are being used in production applications. But as a result, data scientists face several challenges.
Exciting news up here at the off grid cabin location, we now have actual real high speed internet! With Starlink service we have a true high speed connection, and it even uses less power than the Viasat installation did.
Many enterprise leaders have taken a “Field of Dreams” approach to AI ROI — “If we build it, profits will come.” While it’s one thing to take that approach for smaller pilot projects, it’s another thing when you’re consistently being asked to fund initiatives with seven-figure price tags.
Few are able to answer basic questions such as “What’s the ROI of our AI investments?” or “What’s the exposure to our AI compliance risks?”
Is the best practice for Enterprise AI to keep ModelOps independent from data science in both practice and platform?
Welcome to the next post in the series about living life off the grid in the mountains of Colorado while working as the CTO of ModelOp.
Data scientists are producing models that are making substantial contributions to the business, and thus more and more models are being used in production applications. But as a result, data scientists face several challenges.
Exciting news up here at the off grid cabin location, we now have actual real high speed internet! With Starlink service we have a true high speed connection, and it even uses less power than the Viasat installation did.
Many enterprise leaders have taken a “Field of Dreams” approach to AI ROI — “If we build it, profits will come.” While it’s one thing to take that approach for smaller pilot projects, it’s another thing when you’re consistently being asked to fund initiatives with seven-figure price tags.
Few are able to answer basic questions such as “What’s the ROI of our AI investments?” or “What’s the exposure to our AI compliance risks?”
Is the best practice for Enterprise AI to keep ModelOps independent from data science in both practice and platform?
Welcome to the next post in the series about living life off the grid in the mountains of Colorado while working as the CTO of ModelOp.
