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Inspired by nature, these soft robots received their amphibious upgrade with the help of bistable actuators.

Researchers at Carnegie Mellon University have created a soft robot that can effortlessly transition from walking to swimming or from crawling to rolling.

“We were inspired by nature to develop a robot that can perform different tasks and adapt to its environment without adding actuators or complexity,” said Dinesh K. Patel, a postdoctoral fellow in the Morphing Matter Lab in the School of Computer Science’s Human-Computer Interaction Institute. “Our bistable actuator is simple, stable and durable, and lays the foundation for future work on dynamic, reconfigurable soft robotics.”

Deep Learning (DL) advances have cleared the way for intriguing new applications and are influencing the future of Artificial Intelligence (AI) technology. However, a typical concern for DL models is their explainability, as experts commonly agree that Neural Networks (NNs) function as black boxes. We do not precisely know what happens inside, but we know that the given input is somehow processed, and as a result, we obtain something as output. For this reason, DL models can often be difficult to understand or interpret. Understanding why a model makes certain predictions or how to improve it can be challenging.

This article will introduce and emphasize the importance of NN explainability, provide insights into how to achieve it, and suggest tools that could improve your DL model’s performance.

You’re going to have strong feelings about this redesign.

Gustav Söderström has worked at Spotify for a long time; his first big project was leading the launch of its mobile app back in 2009. That makes him the perfect company leader to talk to about Spotify’s recent redesign, which introduces a visual, TikTok-like feed for discovering new content on the app’s homepage. As his boss, CEO Daniel Ek, put it last week, it’s the biggest change Spotify has undergone since we introduced mobile.


Spotify is launching a feed that will help you discover new artists, podcasts, and audiobooks.

More than 107 million science papers have just been cataloged for the public’s use thanks to a new project called The General Index.

Typically, academic studies exist behind a paywall — locking up potentially important information not only from the public but, perhaps more importantly, from other scientists.

The General Index wants to set that information free. The index acts almost like a Google search for scientific papers, but with a twist. Only snippets of the papers are provided, so it is up to users to mine the data and make sense out of it all.