One evening in early September, T, a 28-year-old actor who asked to be identified by his first initial, took his seat in a rented Hollywood studio space in front of three cameras, a director, and a producer for a somewhat unusual gig. The two-hour shoot produced footage that was not meant to be viewed by…
ChatGPT and other deep generative models are proving to be uncanny mimics. These AI supermodels can churn out poems, finish symphonies, and create new videos and images by automatically learning from millions of examples of previous works. These enormously powerful and versatile tools excel at generating new content that resembles everything they’ve seen before. But…
Daron Acemoglu, Institute Professor and the Elizabeth and James Killian Professor of Economics in MIT’s School of Arts, Humanities, and Social Sciences, is the 2023 recipient of the WZB Berlin Social Science Center’s A.SK Social Science Award, one of the most highly endowed international awards in the social sciences. Acemoglu received the award for “his vastly…
This story first appeared in China Report, MIT Technology Review’s newsletter about technology in China. Sign up to receive it in your inbox every Tuesday. Ever since the Chinese government passed a law on generative AI back in July, I’ve been wondering how exactly China’s censorship machine would adapt for the AI era. The content produced by…
Goal Representations for Instruction Following <!– Figure title. Figure caption. This image is centered and set to 50% page width. –> A longstanding goal of the field of robot learning has been to create generalist agents that can perform tasks for humans. Natural language has the potential to be an easy-to-use interface for humans to…
Anant Agarwal, an MIT professor and of the founders of the EdX educational platform, recently created a stir by saying that prompt engineering was the most important skill you could learn. And that you could learn the basics in two hours. Although I agree that designing good prompts for AI is an important skill, Agarwal…
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Many people in AI will be familiar with the story of the Mechanical Turk. It was a chess-playing machine built in 1770, and it was so good its opponents were tricked…
Anyone who has ever tried to pack a family-sized amount of luggage into a sedan-sized trunk knows this is a hard problem. Robots struggle with dense packing tasks, too. For the robot, solving the packing problem involves satisfying many constraints, such as stacking luggage so suitcases don’t topple out of the trunk, heavy objects aren’t…
Rethinking the Role of PPO in RLHF TL;DR: In RLHF, there’s tension between the reward learning phase, which uses human preference in the form of comparisons, and the RL fine-tuning phase, which optimizes a single, non-comparative reward. What if we performed RL in a comparative way? Figure 1: This diagram illustrates the difference between reinforcement…
As autonomous systems and artificial intelligence become increasingly common in daily life, new methods are emerging to help humans check that these systems are behaving as expected. One method, called formal specifications, uses mathematical formulas that can be translated into natural-language expressions. Some researchers claim that this method can be used to spell out decisions…