I previously discussed the capabilities we might expect from future AI systems, illustrated through GPT2030, a hypothetical successor of GPT-4 trained in 2030. GPT2030 had a number of advanced capabilities, including superhuman programming,

Given their advanced capabilities, future AI systems could pose significant risks to society. Some of this risk stems from humans using AI systems for bad ends (misuse), while some stems from the difficulty

I'm experimenting with hosting guest posts on this blog, as a way to represent additional viewpoints and especially to highlight ideas from researchers who do not already have a platform. Hosting

Two years ago, I commissioned forecasts for state-of-the-art performance on several popular ML benchmarks. Forecasters were asked to predict state-of-the-art performance on June 30th of 2022, 2023, 2024, and 2025. While there were

GPT-4 surprised many people with its abilities at coding, creative brainstorming, letter-writing, and other skills. How can we be less surprised by developments in machine learning? In this post, I’ll forecast the properties of large pretrained ML systems in 2030.