ModelOps Can Build AI and ML With Business Results

Share post:

A recent report by MIT Sloan Management Review and SAS called for a relatively new method called “ModelOps,” which is seen as critical to the successful delivery of artificial intelligence (AI) and machine language (ML) to businesses.

ModelOps, which stands for Model Operationalization, is a way to help IT executives bridge the gap between analysis and production teams, making the lifecycle of AI and ML “repeatable and sustainable.”

To get ModelOps to manage AI and ML, IT leaders and professionals must bring together four key elements of the business value equations, including ecosystems, data, platforms, and people.

For more information, read the original story in ZDNet.


Related articles

Target’s new AI is aimed at employees

Target is introducing a new generative artificial intelligence tool aimed at enhancing the efficiency of its store employees...

The good and the bad of AI generated code

Generative AI tools are transforming the coding landscape, making both skilled and novice developers more efficient. However, the...

Microsoft’s AI success may spell defeat for it’s climate goals

Microsoft's ambitious strides in AI technology are now posing a significant challenge to its own climate goals, as...

OpenAI’s Chief Scientist Ilya Sutskever Departs Company

Ilya Sutskever, co-founder and chief scientist of OpenAI, has officially announced his departure from the company. This move...

Become a member

New, Relevant Tech Stories. Our article selection is done by industry professionals. Our writers summarize them to give you the key takeaways