The founder of General Motors-owned Cruise has stepped down less than a month after the driverless car company paused operations after an accident and the loss of permission to operate in California. Kyle Vogt did not give a reason for his departure from the company that he started in 2013 before it was bought by the US automotive manufacturer General Motors in 2016. San Francisco-based Cruise is seen as one of the most advanced autonomous driving companies in the world, and it had started charging passengers for journeys in some US cities. However, it paused all of its driverless cars on 26 October after California regulators revoked its licence to transport passengers without a driver after an accident on 2 October. The company recalled nearly 1,000 vehicles to update their software after the incident.

This article is from Big Technology, a newsletter by Alex Kantrowitz. For years, Google dominated search with little opposition. The format faced little disruption; it was always just a bunch of blue links. And the company's multibillion-dollar deals with phone-makers to keep Google search as a default cemented its lead. But its comfortable perch is actually, really starting to fade.

Vision and robotics systems enabled by cameras that recover 3D scene geometry are revolutionizing several aspects of our lives via technologies such as autonomous transportation, robotic surgery, and'hands-free' user interfaces. Modern 3D cameras are active devices, where a programmable light source emits coded illumination. The emitted light gets reflected from the scene and is received by a sensor to infer the 3D structure of the surroundings. In a multi-camera environment, such active 3D cameras may receive light from the sources of other cameras, resulting in large depth errors. This problem is becoming increasingly important due to the emergence of low-cost and compact active 3D cameras, which are becoming ubiquitous across a wide range of applications, from consumer devices to vehicular vision systems.

It has been three years since the arrival of GPT-3,2 a neural-network-based large language model (LLM) that could generate polished, stylish text with ease. What followed was an intense race among tech giants like Google, OpenAI, and Meta to come up with larger and larger models, often trained using texts appearing anywhere on the Internet. While storming the AI research communities, all these were much outside the scope of usual public discourse. The advancement was evident, shortcomings were subtle. But the most drastic change that ChatGPT brought forth was the sensation among the non-researchers (or researchers far from language technology or artificial intelligence) and ordinary citizens.

To come up with the new definition, the Google DeepMind team started with prominent existing definitions of AGI and drew out what they believe to be their essential common features. The team also outlines five ascending levels of AGI: emerging (which in their view includes cutting-edge chatbots like ChatGPT and Bard), competent, expert, virtuoso, and superhuman (performing a wide range of tasks better than all humans, including tasks humans cannot do at all, such as decoding other people's thoughts, predicting future events, and talking to animals). They note that no level beyond emerging AGI has been achieved. "This provides some much-needed clarity on the topic," says Julian Togelius, an AI researcher at New York University, who was not involved in the work. "Too many people sling around the term AGI without having thought much about what they mean."

Angie Wang illustrates her toddler’s language-acquisition process, and how it compares with the learning process of large language models.

To overcome this, a team has combined inkjet printing with an error-correction system guided by machine vision, to allow them to print sophisticated multi-material objects. They used this method to make a bio-inspired robotic hand that combines soft and rigid plastics to make mechanical bones, ligaments, and tendons, as well as a pump based on a mammalian heart. Citizen-scientists help identify an astronomical object that blurs the line between asteroid and comet, and how a Seinfeld episode helped scientists to distinguish the brain regions involved in understanding and appreciating humour. Type 2 diabetes affects hundreds of millions of people around the world and represents a significant burden on healthcare systems. But behaviour change programmes -- also known as lifestyle interventions -- could potentially play a large role in preventing people from developing type 2 diabetes. This week in Nature a new paper assesses how effective this kind of intervention might be.

Last month, educational psychologist Ronald Beghetto asked a group of graduate students and teaching professionals to discuss their work in an unusual way. As well as talking to each other, they conversed with a collection of creativity-focused chatbots that Beghetto had designed and that will soon be hosted on a platform run by his institute, Arizona State University (ASU). The bots are based on the same artificial-intelligence (AI) technology that powers the famous and conversationally fluent ChatGPT. Beghetto prompts the bots to take on various personas to encourage creativity -- for example, by deliberately challenging someone's assumptions. One student discussed various dissertation topics with the chatbots. Lecturers talked about how to design classes.

Can AI tell you if you will need an umbrella? AI can predict the weather 10 days ahead more accurately than current state-of-the-art simulations, says AI firm Google DeepMind – but meteorologists have warned against abandoning weather models based in real physical principles and just relying on patterns in data, while pointing out shortcomings in the AI approach. Existing weather forecasts are based on mathematical models, which use physics and powerful supercomputers to deterministically predict what will happen in the future. These models have slowly become more accurate by adding finer detail, which in turn requires more computation and therefore ever more powerful computers and higher energy demands. Rémi Lam at Google DeepMind and his colleagues have taken a different approach.

A robotic chemist working autonomously in a lab has developed an oxygen-producing catalyst from minerals found in Martian meteorites. The same procedure could one day be used to provide oxygen for astronauts on Mars. Sending supplies to a future Martian colony by spacecraft would be extremely expensive, which makes producing materials with Mars's natural resources an appealing option. But this can be difficult because there are fewer available elements on Mars than on Earth. Yi Luo at the University of Science and Technology of China in Hefei and his colleagues have developed a fully automated robot chemist.