Sparks of Artificial General Intelligence: Early experiments with GPT-4 - Summary

Arxiv URL: https://arxiv.org/abs/2303.12712v1

Authors: Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, Harsha Nori, Hamid Palangi, Marco Tulio Ribeiro, Yi Zhang

Summary:

The paper reports on the investigation of an early version of GPT-4, which is part of a new cohort of LLMs that exhibit more general intelligence than previous AI models. The paper demonstrates that GPT-4 can solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting. The paper also discusses the challenges ahead for advancing towards deeper and more comprehensive versions of AGI.

Key Insights & Learnings:

• GPT-4 is part of a new cohort of LLMs that exhibit more general intelligence than previous AI models.
• GPT-4 can solve novel and difficult tasks that span various domains without needing any special prompting.
• GPT-4's performance is strikingly close to human-level performance, and often vastly surpasses prior models.
• GPT-4 could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system.
• The paper discusses the challenges ahead for advancing towards deeper and more comprehensive versions of AGI.

Terms Mentioned: Artificial intelligence, Large language models, GPT-4, ChatGPT, PaLM, Artificial general intelligence, AGI, Mathematics, Coding, Vision, Medicine, Law, Psychology, Next-word prediction, PII Detection

Technologies / Libraries Mentioned: OpenAI