OpenAI's CriticGPT is designed to identify bugs and errors in code generated by ChatGPT, helping human trainers spot mistakes during Reinforcement Learning from Human Feedback (RLHF). It is trained on a dataset of code samples with intentional bugs, teaching it to recognize and flag various coding errors.
CriticGPT's accuracy plays a crucial role in AI training effectiveness. As a multimodal large language model (MLLM), CriticGPT is capable of understanding trajectory videos in robot manipulation tasks and providing valuable preference feedback. By generating preference labels with high accuracy, CriticGPT can enhance the performance of reinforcement learning algorithms and guide control policy learning more efficiently2. This not only improves the overall AI training process but also showcases the potential of MLLMs in empowering a broader spectrum of visual robot tasks.
AI chatbots, including OpenAI's ChatGPT and Microsoft's Copilot, spread a debunked claim that there would be a 1-2 minute delay in CNN's broadcast of the presidential debate between President Joe Biden and former President Donald Trump. This false claim suggested that the delay would be used to edit parts of the debate's footage before it reached the public. CNN promptly denied the allegation.