AI This Week: OpenAI’s Mystery Product, Anthropic’s Metaprompt, IBM’s Code Models, and OpenAI’s New Guidelines
Top Announcements
OpenAI will reveal a mysterious AI product on Monday. The announcement will not introduce GPT-5 or a new search engine. However, OpenAI has developed new features that are expected to be well-received. The demo will highlight these new developments. The announcement could be open-source related due to the pressure OpenAI is receiving. It could also involve the release of Sora or be related to LLM agents, as Sam Altman strongly believes the future of AI will be built by agents. Additionally, the update will likely be based on feedback from users.
Anthropic released metaprompt, a tool that boosts performance in Claude-powered apps by turning brief task descriptions into optimized prompt templates. It uses a few-shot prompt with examples and supports variables like subject, length, and tone. Accessible via a Google Colab notebook requiring an Anthropic API key, it generates high-quality prompts for specific tasks, aiding prompt engineering. Additional resources include prompt engineering techniques, a cookbook with Jupyter notebooks, and a prompt library.
IBM just open-sourced a family of 8 code models ranging from 3 to 34B parameters and trained on 116 programming languages. They come in base or instruct mode and can be used for code generation, bug fixes, and code documentation. These new models outperform models in their size category like CodeGemma or Mistral, and are particularly good at fixing and explaining code. They even support COBOL and can translate it to a more modern language. The only negative point is that they come with small context lengths (2k to 8k tokens) which is usually incompatible with bug fixing or explanation for a dense and long codebase. The models are already available on the Hugging Face.
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Breakthrough
OpenAI unveiled its Model Spec in a recent blog post to share its view on how AI models should behave. The goal is to be transparent regarding how they shape models’ behavior and allow us to distinguish between intentional engineering decisions and genuine bugs on the model’s end. This first draft defines objectives, rules and default behaviors models should follow.
For OpenAI, the best way to ensure models are aligned with our desired behavior is to collaborate on shaping that behavior.
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