Meta releases ‘Self-Taught Evaluator’ AI model to reduce human involvement in AI development 

Meta, the parent company of Facebook, has introduced a new artificial intelligence model called the “Self-Taught Evaluator,” aimed at significantly reducing human input in AI training and evaluation.

According to a Reuters report, the development which was revealed on Friday, highlights Meta’s commitment to advancing autonomous AI systems.

Unlike traditional models that rely on human-generated data for training, the Self-Taught Evaluator was trained entirely using AI-generated data.

This groundbreaking approach eliminates the need for human intervention during the training phase, offering a potential path toward fully autonomous AI agents capable of self-learning and correction.

According to Meta researchers, the AI tool can learn from its own mistakes, positioning it as a major step forward in the AI field. Jason Weston, one of Meta’s lead researchers on the project, emphasized the significance of this model.

“We hope, as AI becomes more and more super-human, that it will get better and better at checking its work so that it will actually be better than the average human. 

“The idea of being self-taught and able to self-evaluate is basically crucial to the idea of getting to this sort of super-human level of AI,” Weston said.

Meta explained in a publication last month that the Self-Taught Evaluator is based on a “chain of thought” technique.

This technique involves breaking down complex problems into smaller, logical steps, which improves accuracy in fields like coding, mathematics, and science.

Reducing reliance on human feedback 

The Self-Taught Evaluator is expected to reduce the dependency on a process known as Reinforcement Learning from Human Feedback (RLHF), which requires human experts to label data and verify responses.

• This process is often expensive and time-consuming.
• Meta’s AI tool, however, aims to leverage Reinforcement Learning from AI Feedback (RLAIF), a concept that allows AI systems to refine their responses without human guidance.
• This could revolutionize AI training and development, cutting costs and improving efficiency.
• With the introduction of this new AI model, Meta is moving closer to its goal of developing autonomous digital assistants capable of carrying out complex tasks without human supervision.
• While other companies like Google and Anthropic have also explored RLAIF, Meta stands out by releasing its models for public use.
• The Self-Taught Evaluator demonstrates Meta’s ongoing push for greater accessibility in AI development, setting it apart from competitors that keep their models private.