Meta, the parent company of Facebook and Instagram, recently announced that it is releasing new AI models, including a “Self-Taught Evaluator”, from its research division. Among other things, this AI model uses AI to evaluate other AI models, potentially reducing the need for human involvement in the development process.
Meta’s Self-Taught Evaluator is nothing but a “chain of thought” reasoning technique, which is used by OpenAI’s latest model OpenAI o1 that is claimed to offer reasoning while responding.
What Meta’s new AI model does and how it is different
As per a report by news agency Reuters, this approach breaks down complex tasks into smaller, more manageable steps, improving accuracy in areas like mathematics, scientific analysis, and coding.
What sets Meta’s model apart is that it’s trained entirely on AI-generated data, eliminating the reliance on human-labeled data.
Notably, this approach of AI model may pave the way for more autonomous AI systems capable of self-improvement. By learning from its own mistakes, AI could become increasingly accurate and sophisticated without constant human intervention.
“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,” said Jason Weston, one of the researchers.
This may also streamline the development process and potentially lead to more powerful and efficient AI applications.
“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,” he added.
Other AI tools that Meta is releasing
In addition to the Self-Taught Evaluator, Meta also released other AI tools, including an update to its Segment Anything image identification model, a tool to accelerate response times in large language models, and datasets to aid in the discovery of new inorganic materials.
