OpenAI’s latest artificial intelligence system, o1, has been released with a bold promise. The company claims that o1 works in a way that is closer to how a person thinks than previous large language models (LLMs). This new level of AI capability has raised questions about the potential for machine general intelligence (AGI) and its implications on humanity.
AGI refers to an AI system with human-like reasoning and generalization abilities. While some researchers believe AGI might be imminent, others argue that it requires significant advancements beyond current LLMs. Yoshua Bengio, a deep-learning researcher, notes that there are still “pieces missing” in current LLM architectures.
The new capabilities of o1 have sparked debate about the potential for AGI. OpenAI’s LLM has demonstrated impressive abilities in generalizing from one task to another, abstract reasoning, and planning. However, this increased power also poses risks to humanity, as noted by Bengio.
The revolution in LLMs over the past few years has led to speculation about AGI. Researchers like Subbarao Kambhampati, a computer scientist at Arizona State University, now believe that AGI is a more relevant topic than ever. However, the definition of AGI remains elusive, and most researchers agree that it requires significant advancements beyond current LLMs.
The new capabilities of o1 have also raised questions about the limits of LLMs. While larger models like o1 have demonstrated impressive abilities, smaller LLMs struggle with tasks that require chain-of-thought (CoT) prompting. CoT prompting involves showing an LLM how to break down a problem into smaller steps to solve it.
The use of transformer architecture has taken LLMs significantly beyond previous achievements, allowing models to learn the statistical structure of training data and predict new tokens. However, this increased power also poses risks to humanity, as noted by researchers like Francois Chollet, who left Google to start a new company.
In conclusion, o1’s promise of new cognitive capability has sparked debate about the potential for AGI. While some researchers believe AGI might be imminent, others argue that it requires significant advancements beyond current LLMs. The limits of LLMs and the risks of increased power will need to be carefully considered as we move forward in the development of AI systems like o1.
Source: https://www.nature.com/articles/d41586-024-03905-1