Language Models that Run Themselves Accelerate the Advent of AGI

IBL News | New York

Language models that speed up and automate tasks with text or code, also called “autonomous AI,” “self-prompting,” or “auto-prompting” have become the latest trend in generative AI.

These models develop and execute prompts that can lead to new prompts, becoming truly powerful.

OpenAI developer Andrej Karpathy said, “Stringing them together in loops creates agents that can perceive, think, and act, their goals defined in English in prompts.”

At the moment, the most popular self-prompting example is the experimental open-source application “Auto-GPT”.

According to its coding team, this Python application is designed to independently develop and manage business ideas and generate income.

The program plans step-by-step, justifies decisions, and develops plans, which it documents.

The system integrates GPT-4 for text generation, accesses the Internet for data retrieval, stores data, and generates speech via the Elevenlabs API. It’s even capable of self-improvement and bug-fixing by generating Python scripts via GPT-4.

Projects like Baby-AGI or Jarvis (HuggingGPT) work with the same idea as Auto-GPT by automating complex tasks autonomously.

The team behind HuggingGPT explained, “By leveraging the strong language capability of ChatGPT and abundant AI models in Hugging Face, HuggingGPT is able to cover numerous sophisticated AI tasks in different modalities and domains and achieve impressive results in language, vision, speech, and other challenging tasks, which paves a new way towards advanced artificial intelligence.”

Experts agree that GPT-4 is going a little AGI (Artificial General Intelligence) with autonomous AI. “Models that apply self-improvement of language models could get rapidly more powerful as we approach the possibility of real-life AGIs, experts say.