Lithium-ion batteries have become a key component in the rise of electric mobility, but forecasting their health and lifespans is limiting the technology. While they've proven successful, the capacity of lithium-ion batteries degrades over time, and not just because of the ageing process that occurs during charging and discharging -- known as "cycling ageing." Lithium-ion battery cells also suffer degradation from so-called "calendar ageing," which occurs during storage, or simply when the battery is not in use. It's determined by three main factors: the rest state of charge (SOC), the rest temperature, and the duration of the rest time of a battery. Given that an electric vehicle will spend most of its life parked, predicting the cells' capacity degradation from calendar ageing is crucial; it can prolong battery life and pave the way for mechanisms that could even circumvent the phenomenon.

Last month, Facebook parent Meta unveiled an artificial intelligence chatbot said to be its most advanced yet. BlenderBot 3, as the AI is known, is able to search the internet to talk to people about almost anything, and it has abilities related to personality, empathy, knowledge and long-term memory. BlenderBot 3 is also good at peddling anti-Semitic conspiracy theories, claiming that former US President Donald Trump won the 2020 election, and calling Meta Chairman and Facebook co-founder Mark Zuckerberg "creepy". It's not the first time an AI has gone rogue. In 2016, Microsoft's Tay AI took less than 24 hours to morph into a rightwing bigot on Twitter, posting racist and misogynistic tweets and praising Adolf Hitler.

DeepMind, a U.K.-based firm that is part of Alphabet, Google's parent company, has developed an artificial intelligence and machine learning system that can predict the three-dimensional structure of proteins, decoding the amino acids that make up each protein. Last year, the system had 350,000 entries. Then on July 28, DeepMind co-founder and chief executive Demis Hassabis announced the expansion of the company's database of folded proteins to more than 200 million -- nearly all catalogued proteins known to science, including those in humans, plants, bacteria, animals and other organisms -- and that the company is making them publicly available and free, accessible with no more effort than a Google search. The database is called AlphaFold, and it is the equivalent of a James Webb Space Telescope for biology, providing astounding new visuals of a world beyond.

In the Pixar movie Up, a cartoon dog called Dug sports a magical collar of sorts that can translate his barks and whines into fluent human speech. Elsewhere in the real world, very well-trained dogs can be taught to press buttons that produce human speech for simple commands like "outside," "walk," and "play." Humans have always been fascinated by the potential to communicate with the animals that they share the world with, and recently, machine learning, with its ever more advanced capabilities for parsing human speech, has presented itself as a hopeful route to animal translation. An article in the New York Times this week documented major efforts from five groups of researchers that looked at using machine-learning algorithms to analyze the calls of rodents, lemurs, whales, chickens, pigs, bats, cats, and more. Typically, artificial intelligence systems learn through training with labeled data (which can be supplied by the internet, or resources like e-books).

DeepMind's attempt to teach an AI to play soccer started with a virtual player writhing around on the floor--so it nailed at least one aspect of the game right from kickoff. But pinning down the mechanics of the beautiful game--from basics like running and kicking to higher-order concepts like teamwork and tackling--proved a lot more challenging, as new research from the Alphabet-backed AI firm demonstrates. The work--published this week in the journal Science Robotics--might seem frivolous, but learning the fundamentals of soccer could one day help robots to move around our world in more natural, more human ways. "In order to'solve' soccer, you have to actually solve lots of open problems on the path to artificial general intelligence [AGI]," says Guy Lever, a research scientist at DeepMind. "There's controlling the full humanoid body, coordination--which is really tough for AGI--and actually mastering both low-level motor control and things like long-term planning."

Autonomous driving company Cruise and US regulators said on Thursday that the General Motors subsidiary had recalled software deployed on 80 vehicles after a June crash in San Francisco involving a Cruise car operating autonomously injured two people. The incident occurred one day after the state of California granted Cruise a permit to start a commercial driverless ride-hail service in the state. The flawed software was updated by early July, Cruise said in a filing with the US National Highway Traffic Safety Agency. The crash occurred when a Cruise vehicle attempting to make an unprotected left turn across a two-lane street was struck by a car that was traveling in the opposite direction and speeding in a turn lane. Cruise said in its NHTSA filing that its software had predicted that the other car would turn right and determined that it was necessary to brake hard in the midst of its own vehicle's left turn to avoid a front-end collision.

Chip designer Nvidia Corp on Wednesday said that U.S. officials told it to stop exporting two top computing chips for artificial intelligence work to China, a move that could cripple Chinese firms' ability to carry out advanced work like image recognition and hamper a business Nvidia expects to generate $400 million in sales this quarter. Nvidia shares fell 4% after hours. The company said the ban, which affects its A100 and H100 chips designed to speed up machine learning tasks, could interfere with completion of developing the H100, the flagship chip Nvidia announced this year. Shares of Nvidia rival Advanced Micro Devices were down 2% after hours. An AMD spokesman told Reuters it had received new license requirements that will stop its MI250 artificial intelligence chips from being exported to China but it believes its MI100 chips will not be affected.

A gearbox driven by an external magnetic field can power tiny but powerful robots that crawl like a caterpillar or jump almost 40 times their own height, despite having no batteries or motors on board. The technology could lead to medical robots that can travel through the human body, taking samples or delivering drugs. Soft robots – which have no batteries, motors or electronics and are powered and controlled remotely by light or magnets – are a popular field of research because their simplicity enables them to be highly miniaturised. But they may be lacking in power when the task requires puncturing skin or opening collapsed cavities. Now, Chong Hong at the Max Planck Institute for Intelligent Systems in Germany and his colleagues have created a gearbox that measures around 3 millimetres across and is equipped with cogs as small as 270 micrometres in diameter.

Since 2016, Tesla has been marketing an expensive option called Full Self-Driving. A reasonable person might infer from the name that the software package enables a car to drive itself, fully. No car available for consumers to buy is capable of full self-driving. The California Department of Motor Vehicles has rules on its books that ban the advertisement of cars as "self-driving" when they are not. But it has never enforced those rules.

Robotaxi safety operator is an occupation that exists only in our time, the result of an evolving technology that's advanced enough to get rid of a driver--most of the time, and in controlled environments--but not good enough to convince authorities that they can do away with human intervention altogether. Today, self-driving companies from the US, Europe, and China are racing to bring the technology to commercial application. Most of them, including Apollo, the self-driving arm of Baidu, have started on-demand robotaxi trials on public roads but still need to operate with various constraints. With an associate degree in human resources, Liu has no academic training related to this job, But he has always loved driving, and he acted as the driver for his boss in a previous role. When he heard about the self-driving technologies, his curiosity pushed him to look up related jobs online and apply.