What is undermining ML initiatives?

2022-04-05 03:30

Hundreds of enterprise ML practitioners were asked about their experiences and the factors that affected their teams' ability to deliver the level of business value their organizations expected from ML initiatives.

By contrast, 47% of ML teams require four to six months to deploy a single ML project, while another 43% take up to three months.

Without funds for automation, ML teams must track experiments manually.

Even though many organizations are good at identifying ML use cases and initiating projects, they fall short in investing in ML operations best practices and the tools and resources needed to make these machine learning initiatives as clear, efficient, and scalable as possible.

Developing effective ML models requires a lot of experiments.

"If teams are maxed out and struggling with visibility, reproducibility and cost-efficiency today, it will be difficult for them to add more models, experiments and deployments this year, as they expressed the desire to do. Successful ML outcomes depend on people; and with the right tools, teams can avoid burnout."

News URL

https://www.helpnetsecurity.com/2022/04/05/organizations-ml-initiatives/