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By TechRepublic
August 13, 2021
![[article image]](https://cacm.acm.org/system/assets/0004/0741/081321_TechRepub_MLOps.large.jpg?1628882189&1628882188 "A colorful abstraction of digital transformation, AI, and other themes, with an eyeball at the center.")
The artificial intelligence (AI)/machine learning (ML) software development and deployment lifecycle is still very nascent. The challenge of moving models into production is exacerbated by a demand for speed and a shortage of qualified ML engineers. But there's hope that things may soon get better.
A new crop of platforms and tools are sprouting, defined loosely as MLOps, which is itself a derivative of DevOps.
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