Accidental OpenAI Employee Spills Details on Q* (Open AI)

OpenAI employee accidentally reveals details about the infamous Q* model in a deleted tweet. Speculation suggests that the tweet was related to planning and synthetic data, which could potentially improve the accuracy of language models by allowing more time for thinking. This concept of planning has been seen in recent AI demos, such as Mesa’s KPU and Devon, the world’s first AI software engineer. With OpenAI already working on Q* and using GPT-5, the future of AI looks fascinating.

In a recent tweet that has since been deleted, an employee of OpenAI has caused some speculation within the community regarding the infamous qstar model that the company has refused to discuss. While there is some speculation involved, there are several key points that suggest why this tweet could be of interest.

πŸ“ Summary

Noan Brown, a prominent figure in the field of artificial intelligence, works at OpenAI and recently tweeted about not achieving superhuman performance by doing better imitation learning on human data. This tweet could potentially be related to the planning model that OpenAI is allegedly working on, known as qstar. The model involves synthetic data, which is data generated by the AI itself, and planning for multi-step reasoning and thinking to achieve long-term goals.

πŸ€” Speculation on the Deleted Tweet

While the tweet from Brown could be referring to various things, many speculate that it is related to the qstar planning model, which OpenAI has been working on. Brown has previously worked on developing AI systems capable of playing poker at a superhuman level, which has significantly advanced AI capabilities in imperfect information games. In addition, his earlier tweets from 2023 suggest that he is investigating how to make these methods truly general, and that we may one day see language models that are a thousand times better than GPT-4.

πŸ”¬ Q* Breakthrough and Synthetic Data

OpenAI made a breakthrough with qstar, which involves planning for multi-step reasoning and thinking to achieve long-term goals. The company has likely solved planning and agentic behavior for small-scale models and is using computer-generated synthetic data to train new models. Brown’s tweet on better imitation learning on human data suggests that he is talking about synthetic data, which is generated by the AI itself.

πŸ€– AI Systems and Planning

The ability to plan is becoming a crucial aspect of AI systems, as it allows for multi-step reasoning and thinking to achieve long-term goals. Mesa’s kpu and Devon are examples of AI systems that use planning to increase their ability to reduce hallucinations and perform tasks more effectively. OpenAI is likely working on planning for language models, which will increase their accuracy, even though the inference cost will be higher.

🧐 Key Takeaways

  • OpenAI employee Noan Brown’s deleted tweet suggests that he could be referring to the qstar planning model.
  • The qstar model involves synthetic data and planning for multi-step reasoning and thinking to achieve long-term goals.
  • Mesa’s kpu and Devon are examples of AI systems that use planning to increase their ability to perform tasks more effectively.
  • Planning is becoming a crucial aspect of AI systems, which will increase their accuracy but also increase inference costs.

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