A clump of human brain cells can play the classic computer game . While its performance is not up to par with humans, experts say it brings biological computers a step closer to useful real-world applications, like controlling robot arms. In 2021, the Australian company Cortical Labs used its neuron-powered computer chips to play . The chips consisted of clumps of more than 800,000 living brain cells grown on top of microelectrode arrays that can both send and receive electrical signals. Researchers had to carefully train the chips to control the paddles on either side of the screen.

It sounds like science fiction - a factory, located hundreds of kilometres above the Earth, churning out high-quality materials. But a Cardiff-based company is a step closer to making this a reality. Space Forge have sent a microwave-sized factory into orbit, and have demonstrated that its furnace can be switched on and reach temperatures of around 1,000C. They plan to manufacture material for semiconductors, which can be used back on Earth in electronics in communications infrastructure, computing and transport. Conditions in space are ideal for making semiconductors, which have the atoms they're made of arranged in a highly ordered 3D structure.

We introduce \textit{Nocturne}, a new 2D driving simulator for investigating multi-agent coordination under partial observability. The focus of Nocturne is to enable research into inference and theory of mind in real-world multi-agent settings without the computational overhead of computer vision and feature extraction from images. Agents in this simulator only observe an obstructed view of the scene, mimicking human visual sensing constraints. Unlike existing benchmarks that are bottlenecked by rendering human-like observations directly using a camera input, Nocturne uses efficient intersection methods to compute a vectorized set of visible features in a C++ back-end, allowing the simulator to run at $2000+$ steps-per-second. Using open-source trajectory and map data, we construct a simulator to load and replay arbitrary trajectories and scenes from real-world driving data. Using this environment, we benchmark reinforcement-learning and imitation-learning agents and demonstrate that the agents are quite far from human-level coordination ability and deviate significantly from the expert trajectories.

Robots equipped with the π0.5 AI model were tested in homes they had never seen before An AI enabling robots to do chores like making the bed or cleaning up spills in homes it has never seen before could allow many more robots to become generally useful, its creators say. Large language models (LLMs) like ChatGPT have improved robots' ability to carry out spoken requests. However, most robots work well only in environments in which they have been trained; their performance quality sharply falls when confronted with new and unfamiliar spaces.

Feedback is New Scientist's popular sideways look at the latest science and technology news. You can submit items you believe may amuse readers to Feedback by emailing feedback@newscientist.com Feedback has reached an age where even a small amount of alcohol makes us sleepy, so the notion of going to a wine tasting holds no appeal. It seems a terribly time-consuming and expensive way to have a nap. However, purveyors of fermented grapes could soon have a new demographic to cater to: rats.

After a first date it's normal to wonder if those warm, fuzzy feelings are reciprocated. Now, experts are one step closer to an app that will tell you if they're'just not that into you'. Researchers have trained a computer - using data from wearable technology that measures respiration, heart rates and perspiration – to identify the type of conversation two people are having. In experiments with 16 pairs of participants, it was able to differentiate four different conversation scenarios with as much as 75 per cent accuracy. Lead author Iman Chatterjee, from the University of Cincinnati, said the technology could one day give you honest feedback about yourself or your date.

We introduce \textit{Nocturne}, a new 2D driving simulator for investigating multi-agent coordination under partial observability. The focus of Nocturne is to enable research into inference and theory of mind in real-world multi-agent settings without the computational overhead of computer vision and feature extraction from images. Agents in this simulator only observe an obstructed view of the scene, mimicking human visual sensing constraints. Unlike existing benchmarks that are bottlenecked by rendering human-like observations directly using a camera input, Nocturne uses efficient intersection methods to compute a vectorized set of visible features in a C back-end, allowing the simulator to run at 2000 steps-per-second. Using open-source trajectory and map data, we construct a simulator to load and replay arbitrary trajectories and scenes from real-world driving data.

Scientists have unveiled a hybrid computer made of electronics and human brain-like tissues called'Brainoware.' It's part of a growing field called biological computing. The new technology features a brain'organoid' made of human stem cells which sit atop a circuit board that feeds the organoid information and reads its responses. This biological-electronic hybrid was able to identify people's by voice and make predictions about a complex math problem. The researchers claim the discovery represents a significant step toward hybrid computers, which merge man and machine to perform complex computing problems using a fraction of the power needed by conventional computers.

The idea of indestructible killer robots may sound like something straight out of the Terminator movie. But they could soon become a reality, as scientists have just witnessed metal healing itself for the first time, without any human intervention. A US-based study has overturned everything we thought we knew about metals by revealing that cracks from wear and tear can actually mend themselves under certain conditions. It's a discovery that has the potential to revolutionise engineering, with the prospect of self-healing engines, planes and even robots now on the horizon. 'This was absolutely stunning to watch first-hand,' said Brad Boyce, a scientist at Sandia National Laboratories who led the study with Texas A&M University.

"Hated in the Nation," an episode of Netflix's dystopian sci-fi series "Black Mirror," predicted it: Thousands of robotic bees buzz from flower to flower, pollinating plants to make up for declining insect populations. And while the episode's robots eventually turn against their human inventors, killing over 387,000 people by ramming their artificial stingers into victims' heads, the MIT scientists working on perfecting today's aerial robots likely believe we don't need to worry about that. Despite the show's foreboding take on robotic bees, researchers at the Massachusetts Institute of Technology are one step closer to perfecting the artificial aerial critters. In a paper published March 15, a group of researchers at MIT showed that using resilient muscle-like actuators and self-repairing technology can vastly improve the robustness of robotic bees. "Insects flying are incredibly difficult to understand," said Kevin Chen, an assistant professor at MIT, head of the institute's Soft and Micro Robotics Laboratory, and the senior author of the paper.