Meta releases AI model that can check other AI models' work

Facebook owner Meta said on Friday it was releasing a batch of new AI models from its research division.

Facebook owner Meta said on Friday it was releasing a batch of new AI models from its research division, including a "Self-Taught Evaluator" that may offer a path toward less human involvement in the AI development process.

The release follows Meta's introduction of the tool in an August paper, which detailed how it relies upon the same "chain of thought" technique used by OpenAI's recently released o1 models to get it to make reliable judgments about models' responses.

That technique involves breaking down complex problems into smaller logical steps and appears to improve the accuracy of responses on challenging problems in subjects like science, coding and math.

Meta's researchers used entirely AI-generated data to train the evaluator model, eliminating human input at that stage as well.

The ability to use AI to evaluate AI reliably offers a glimpse at a possible pathway toward building autonomous AI agents that can learn from their own mistakes, two of the Meta researchers behind the project told Reuters.

Many in the AI field envision such agents as digital assistants intelligent enough to carry out a vast array of tasks without human intervention.

Self-improving models could cut out the need for an often expensive and inefficient process used today called Reinforcement Learning from Human Feedback, which requires input from human annotators who must have specialised expertise to label data accurately and verify that answers to complex math and writing queries are correct.