By thinking of every incorrect action in one task as a way to do part of a different one, we can give AI the gift of hindsight.
Background: When humans mess up, they can learn several things: that an approach to a task didn’t work, but also that the method they just tried might be helpful for some other job. But when robots try to master tasks by themselves, they typically only learn by getting a reward for every step of a job they do correctly.
Useful mistakes: IEEE Spectrum report that OpenAI, a nonprofit research company, released free software called Hindsight Experience Replay (HER) that lets an AI’s “failures” become successes. It does that by looking at how every attempt at one task could be applied to others. (The software also includes virtual environments where AIs can practice things like picking up objects or holding a pen.)
More realistic robo-training: HER doesn’t give robots rewards for getting a step of a task right—it only hands them out if the entire thing is done properly. That’s closer to how robots will learn in real life, but it usually slows training right down. Still, because every failed attempt can also get used for another job, that’s less of a problem in OpenAI’s system.
This artist is dominating AI-generated art. And he’s not happy about it.
Greg Rutkowski is a more popular prompt than Picasso.
What does GPT-3 “know” about me?
Large language models are trained on troves of personal data hoovered from the internet. So I wanted to know: What does it have on me?
An AI that can design new proteins could help unlock new cures and materials
The machine-learning tool could help researchers discover entirely new proteins not yet known to science.
DeepMind’s new chatbot uses Google searches plus humans to give better answers
The lab trained a chatbot to learn from human feedback and search the internet for information to support its claims.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.