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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.
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.
Through ModelOps, teams can be positioned to fully unleash the value of their AI investments, while addressing requirements to boost trust and minimize risk.
It is important to know the difference between MLOps and ModelOps because neither is a substitute for the other.