One belief underlying the power-hungry approach to machine learning advanced by OpenAI and Mistral AI is that an artificial intelligence model must review its entire dataset before spitting out new insights.

Sepp Hochreiter, an early pioneer of the technology who runs an AI lab at Johannes Kepler University in Linz, Austria, has a different view, one that requires far less cash and computing power. He’s interested in teaching AI models how to efficiently forget.

Hochreiter holds a special place in the world of artificial intelligence, having scaled the technology’s highest peaks long before most computer scientists. As a university student in Munich during the 1990s, he came up with the conceptual framework that underpinned the first generation of nimble AI models used by Alphabet, Apple and Amazon.

Japanese tech startup Sakana AI has written the first AI-generated peer-reviewed scientific paper.

Its AI program, AI Scientist-v2, successfully passed a peer review process, and the paper was accepted at a workshop during the International Conference on Learning Representations (ICLR), a major event in AI.

The AI-generated paper underwent the same review process as human submissions, with Sakana AI collaborating with the University of British Columbia and the University of Oxford.

For decades, the Turing Test was considered the ultimate benchmark to determine whether computers could match human intelligence. Created in 1950, the “imitation game”, as Alan Turing called it, required a machine to carry out a text-based chat in a way that was indistinguishable from a human. It was thought that any machine able to pass the Turing Test would be capable of demonstrating reasoning, autonomy, and maybe even consciousness – meaning it could be considered human-level artificial intelligence, also known as artificial general intelligence (AGI).

The arrival of ChatGPT ruined this notion, as it was able to convincingly pass the test through what was essentially an advanced form of pattern recognition. It could imitate, but not replicate.

Last week, a new AI agent called Manus once again tested our understanding of AGI. The Chinese researchers behind it describe it as the “world’s first fully autonomous AI”, able to perform complex tasks like booking holidays, buying property or creating podcasts – without any human guidance. Yichao Ji, who led its development at the Wuhan-based startup Butterfly Effect, says it “bridges the gap between conception and execution” and is the “next paradigm” for AI.

The best answer will be unsettling to both the hard skeptics of AI and the true believers.

Let’s take a step back. What exactly is reasoning, anyway?

AI companies like OpenAI are using the term reasoning to mean that their models break down a problem into smaller problems, which they tackle step by step, ultimately arriving at a better solution as a result.