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FiloBot grows by 3D printing itself. This footage has been sped up. Credit: IIT – Istituto Italiano di Tecnologia
A robot that 3D prints itself grows like a climbing plant, winding around structures at a few millimetres per minute. Its growth can be influenced by gravity, light and shade — for example, it can be programmed to grow towards the light. The researchers were inspired by plants’ ability to “conquer very challenging and mutable environments,” says roboticist Emanuela Del Dottore, who co-developed the machine.
Nature | 3 min read
Reference: Science Robotics paper
The protein-structure-prediction AI AlphaFold has helped to identify thousands of potential psychedelic molecules, which could help to develop new antidepressants. This is the first time predicted protein structures have been shown to be just as useful for drug discovery as experimentally derived ones, which can take months to determine. In one out of three cases, an AlphaFold prediction could jump-start a drug discovery project by a couple of years, estimates pharmaceutical chemist and study co-author Brian Shoichet. Others caution that AI-generated molecules seem to be helpful for some biological targets but not others, and it’s not always clear which applies.
Nature | 6 min read
Reference: bioRxiv preprint (not peer reviewed)
Features & opinion
AI is redefining intelligence as succeeding in tasks that rely on pattern recognition and prediction from data, writes a trio of communication researchers. This, they argue, limits intelligence to the ability to look backward and condemns us to repeat past mistakes. “We fear this could set limits for human aspirations and for core ideals like knowledge, creativity, imagination and democracy — making for a poorer, more constrained human future.”
Issues in Science and Technology | 4 min read
An AI tool called AlphaGeometry could (theoretically) win a bronze medal in the International Mathematical Olympiad. When presented with maths problems, existing large language models often struggle to make sense when asked to show their workings. So the team trained their model from scratch. “We were able to generate 100 million theorems and proofs so that the machine can learn all of these by itself, and then it can learn to generalise the new problems,” deep learning researcher and former maths Olympiad competitor Thang Luong tells the Nature Podcast. To win an Olympiad gold medal, the algorithm would have to become equally good at disciplines beyond geometry, such as number theory.
Nature Podcast | 32 min listen
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Today, I’m excited to discover that ChatGPT really nails the “polite, yet slightly sarcastic” tone when asked to generate a reply to an email from a predatory journal.
Your human-generated emails are always welcome at ai-briefing@nature.com.
Thanks for reading,
Katrina Krämer, associate editor, Nature Briefing
With contributions by Flora Graham, Roni Dengler and Sara Phillips
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