On Thursday, OpenAI researchers unveiled CriticGPT, a brand new AI mannequin designed to determine errors in code generated by ChatGPT. It goals to reinforce the method of constructing AI methods behave in methods people need (known as “alignment”) by Reinforcement Studying from Human Suggestions (RLHF), which helps human reviewers make giant language mannequin (LLM) outputs extra correct.
As outlined in a brand new analysis paper known as “LLM Critics Assist Catch LLM Bugs,” OpenAI created CriticGPT to behave as an AI assistant to human trainers who assessment programming code generated by the ChatGPT AI assistant. CriticGPT—based mostly on the GPT-4 household of LLMS—analyzes the code and factors out potential errors, making it simpler for people to identify errors that may in any other case go unnoticed. The researchers educated CriticGPT on a dataset of code samples with deliberately inserted bugs, instructing it to acknowledge and flag numerous coding errors.
The event of CriticGPT concerned coaching the mannequin on a lot of inputs containing intentionally inserted errors. Human trainers have been requested to switch code written by ChatGPT, introducing errors after which offering instance suggestions as if they’d found these bugs. This course of allowed the mannequin to learn to determine and critique numerous sorts of coding errors.
In experiments, CriticGPT demonstrated its means to catch each inserted bugs and naturally occurring errors in ChatGPT’s output. The brand new mannequin’s critiques have been most popular by trainers over these generated by ChatGPT itself in 63 % of circumstances involving pure bugs (the aforementioned statistic). This choice was partly because of CriticGPT producing fewer unhelpful “nitpicks” and producing fewer false positives, or hallucinated issues.
The researchers additionally created a brand new approach they name Drive Sampling Beam Search (FSBS). This technique helps CriticGPT write extra detailed opinions of code. It lets the researchers regulate how thorough CriticGPT is in searching for issues whereas additionally controlling how typically it would make up points that do not actually exist. They’ll tweak this stability relying on what they want for various AI coaching duties.
Curiously, the researchers discovered that CriticGPT’s capabilities lengthen past simply code assessment. Of their experiments, they utilized the mannequin to a subset of ChatGPT coaching information that had beforehand been rated as flawless by human annotators. Surprisingly, CriticGPT recognized errors in 24 % of those circumstances—errors that have been subsequently confirmed by human reviewers. OpenAI thinks this demonstrates the mannequin’s potential to generalize to non-code duties and highlights its means to catch refined errors that even cautious human analysis may miss.
Regardless of its promising outcomes, like all AI fashions, CriticGPT has limitations. The mannequin was educated on comparatively brief ChatGPT solutions, which can not totally put together it for evaluating longer, extra complicated duties that future AI methods may sort out. Moreover, whereas CriticGPT reduces confabulations, it would not remove them fully, and human trainers can nonetheless make labeling errors based mostly on these false outputs.
The analysis group acknowledges that CriticGPT is handiest at figuring out errors that may be pinpointed in a single particular location inside the code. Nevertheless, real-world errors in AI outputs can typically be unfold throughout a number of elements of a solution, presenting a problem for future mannequin iterations.
OpenAI plans to combine CriticGPT-like fashions into its RLHF labeling pipeline, offering its trainers with AI help. For OpenAI, it is a step towards creating higher instruments for evaluating outputs from LLM methods which may be tough for people to price with out extra assist. Nevertheless, the researchers warning that even with instruments like CriticGPT, extraordinarily complicated duties or responses should still show difficult for human evaluators—even these assisted by AI.