Orca vs ChatGPT Plugins

Recent advancements in artificial intelligence have paved the way for pioneering research in machine learning, specifically targeting the refinement of smaller AI models. Inspired by this notion, Microsoft Research introduces "Orca," a cutting-edge methodology designed to upgrade the learning processes of these compact AI constructs by utilizing the robust explanation traces produced by larger foundation models like GPT-4.

This innovative approach tackles several challenges encountered in the realm of AI imitation learning, such as the limited learning signals derived from the superficial outputs of larger models, the restrictive nature of small and homogeneous training datasets, and critically, the deficiency of stringent evaluation parameters that directly influence the overall quality and reliability of these models. Orca is a testament to Microsoft's commitment to evolving AI learning and potentiating smaller models' ability to reason, explain, and ultimately understand much like their large-scale counterparts.

OpenAI follows an iterative deployment philosophy, and as part of this approach, it is gradually releasing plugins for ChatGPT. The purpose of this gradual release is to study the real-world use of the plugins, assess their impact, and identify any safety and alignment challenges that may arise. Getting these aspects right is essential for OpenAI to achieve its mission.

Since the launch of ChatGPT, users have expressed interest in having access to plugins, and many developers are experimenting with similar ideas. OpenAI is initially rolling out plugins to a small set of users and plans to gradually increase access as it learns more. After an alpha period, API users who want to integrate plugins into their products will also have access. OpenAI is excited to build a community that will help shape the future of the human-AI interaction paradigm.

Developers who have been invited off the waitlist can use OpenAI's documentation to build a plugin for ChatGPT. Once the plugin is created, it is listed in the prompt shown to the language model, along with documentation that instructs the model on how to use each one. The first set of plugins has been created by Expedia, FiscalNote, Instacart, KAYAK, Klarna, Milo, OpenTable, Shopify, Slack, Speak, Wolfram, and Zapier.