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

TLDR

AI researchers have been developing large language models that demonstrate remarkable cross‑domain capabilities, and the latest OpenAI model, GPT‑4, was trained on an unprecedented scale of compute and data. This study investigates an early version of GPT‑4, examining its rising capabilities, implications, and societal influences as it approaches artificial general intelligence. The authors focus on uncovering GPT‑4’s limitations and the challenges toward deeper AGI, suggesting a paradigm shift beyond next‑word prediction. GPT‑4 exhibits general intelligence, solving diverse tasks in mathematics, coding, vision, medicine, law, and psychology with near‑human performance and surpassing prior models, indicating it may be an early AGI.

Abstract

Artificial intelligence (AI) researchers have been developing and refining large language models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks, challenging our understanding of learning and cognition. The latest model developed by OpenAI, GPT-4, was trained using an unprecedented scale of compute and data. In this paper, we report on our investigation of an early version of GPT-4, when it was still in active development by OpenAI. We contend that (this early version of) GPT-4 is part of a new cohort of LLMs (along with ChatGPT and Google's PaLM for example) that exhibit more general intelligence than previous AI models. We discuss the rising capabilities and implications of these models. We demonstrate that, beyond its mastery of language, GPT-4 can solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting. Moreover, in all of these tasks, GPT-4's performance is strikingly close to human-level performance, and often vastly surpasses prior models such as ChatGPT. Given the breadth and depth of GPT-4's capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. In our exploration of GPT-4, we put special emphasis on discovering its limitations, and we discuss the challenges ahead for advancing towards deeper and more comprehensive versions of AGI, including the possible need for pursuing a new paradigm that moves beyond next-word prediction. We conclude with reflections on societal influences of the recent technological leap and future research directions.