CoreWeave introduces autonomous improvement capabilities for AI agents
Artificial intelligence cloud operator CoreWeave Inc. today announced the launch of a new offering that gives enterprise outfits the ability to deploy AI agents that can learn and improve themselves autonomously using real-world data.
The current lifecycle for AI agents operates through a slow, iterative mechanic of running evaluations and fine-tuning based on reviewing metrics. This is because generative AI large language models, the “brains” that underpin agents, can behave differently between testing and real user scenarios.
After watching this cycle take place so many times within its own infrastructure, CoreWeave decided to short-circuit the process by eliminating the bottleneck and allowing enterprises to launch agents that can learn and adapt in the field.
“Most enterprises are stuck in a cycle of building and testing agents before they ever reach real users, and that cycle is becoming too slow and too expensive to sustain,” said Nick Patience, vice president and practice lead for AI platforms at the Futurum Group.
