Dec. 4, 2023, 3 p.m. | Miriam Friedel

MIT Technology Review www.technologyreview.com

Advances in machine learning (ML) and AI are emerging on a near-daily basis—meaning that industry, academia, government, and society writ large are evolving their understanding of the associated risks and capabilities in real time. As enterprises seek to capitalize on the potential of AI, it’s critical that they develop, maintain, and advance state-of-the-art ML practices…

academia advances capabilities collaborative enterprise enterprises government industry machine machine learning meaning near risks society sponsored teams tooling understanding

More from www.technologyreview.com / MIT Technology Review

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Machine Learning Research Scientist

@ d-Matrix | San Diego, Ca