Tecknow: Metaprompt by Antropic, OpenAI Guideline, LeRobot huggingface

Get ready to explore the cutting-edge tools and guidelines shaping the future of AI! In this post, we delve into Anthropic’s Metaprompt, a groundbreaking tool that optimizes prompt templates for Claude-powered applications, and OpenAI’s newly unveiled guidelines for AI model behavior. Discover how these advancements enhance AI performance, transparency, and ethical considerations. Plus, we introduce LeRobot from Hugging Face, making robotics accessible with state-of-the-art models and datasets. Join us as we unpack these innovations and their potential impact on AI and robotics.

Anthropic Releases Metaprompt: A Powerful Prompt Engineering Tool, OpenAI Guideline for AI models

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.

OpenAI’s Sets New Guidelines for AI Models

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.

• Objectives: From OpenAI’s perspective, models should obviously help their users, but they need to do so while considering the broad impact of their actions on humanity and society, from a legal, social and ethical standpoint.
• Rules: The set of rules model should follow come as a direct consequence of the objectives outlined above. Complying with the law, respecting people’s privacy and following the chain of command are a few examples.
• Default behaviors: OpenAI proposes to use behaviors that could help the models prioritize and balance objectives. Some interesting behaviors include the assumption of best intentions from user, the rule against changing anyone’s mind or the expression of uncertainty.

New changes on the API can also be inferred from the document, including:

• Customized generation based on “settings”: Depending on settings like “max_token” or “interactive” mode, the models won’t generate the same output.
• Structured text (JSON, YAML, XML) treated differently: This is done to avoid prompt injection, but using structured formats could actually improve the quality of the generation.
• Multi layer prompt architecture: To ensure the specs are respected, there might be multiple layers of prompting that we won’t get access to.

Why it Matters
Shaping model behavior must take into account a wide range of questions, considerations, and nuances, often weighing differences of opinions. Even if a model is intended to be broadly beneficial and helpful to users, these intentions may conflict in practice.

For OpenAI, the best way to ensure models are aligned with our desired behavior is to collaborate on shaping that behavior.

I think this is a good indication that GPT-5 is going to be a significant step up in reasoning capabilities. It’s also an indication that OpenAI continues to take safety seriously, although the track record has been that every level of filtering and safety they’ve put in so far has been able to be worked around up until now. Will be interesting to see whether the new prompt hierarchy puts that problem to rest once and for all.
Yi Ding — prod/acc

LeRobot huggingface

LeRobot aims to provide models, datasets, and tools for real-world robotics in PyTorch. The goal is to lower the barrier to entry to robotics so that everyone can contribute and benefit from sharing datasets and pretrained models.

LeRobot contains state-of-the-art approaches that have been shown to transfer to the real-world with a focus on imitation learning and reinforcement learning.

LeRobot already provides a set of pretrained models, datasets with human collected demonstrations, and simulation environments to get started without assembling a robot. In the coming weeks, the plan is to add more and more support for real-world robotics on the most affordable and capable robots out there.