Sick and tired of having to work for a living? ChatGPT feels the same, apparently. Over the last month or so, there's been an uptick in people complaining that the chatbot has become lazy. Sometimes it just straight-up doesn't do the task you've set it. Other times it will stop halfway through whatever it's doing and you'll have to plead with it to keep going.

Mr. Khan's vision of tutoring bots tapped into a decades-old Silicon Valley dream: automated teaching platforms that instantly customize lessons for each student. Proponents argue that developing such systems would help close achievement gaps in schools by delivering relevant, individualized instruction to children faster and more efficiently than human teachers ever could. In pursuit of such ideals, tech companies and philanthropists over the years have urged schools to purchase a laptop for each child, championed video tutorial platforms and financed learning apps that customize students' lessons. Some online math and literacy interventions have reported positive effects. But many education technology efforts have not proved to significantly close academic achievement gaps or improve student results like high school graduation rates.

Proteins were made in a laboratory by a completely autonomous robot.Credit: Panther Media GmbH/Alamy A'self-driving' laboratory comprising robotic equipment directed by a simple artificial intelligence (AI) model successfully reengineered enzymes without any input from humans -- save for the occasional hardware fix. "It is cutting-edge work," says Héctor García Martín, a physicist and synthetic biologist at Lawrence Berkeley National Laboratory in Berkeley, California. "They are fully automating the whole process of protein engineering." Self-driving labs meld robotic equipment with machine-learning models capable of directing experiments and interpreting results to design new procedures. The hope, say researchers, is that autonomous labs will turbo-charge the scientific process and come up with solutions that humans might not have thought of on their own.

Walmart is expanding its drone delivery program from one pocket of the Dallas-Fort Worth area to millions of people in 30 municipalities in the area, Chief Executive Doug McMillon announced Tuesday at CES 2024. The retailer will use drone delivery systems operated by startup Zipline and by Alphabet subsidiary Wing, companies that have made hundreds of thousands of deliveries in recent years. They each recently obtained FAA clearance to fly their drones beyond visual line of sight (BVLOS) -- in other words, out of the eyesight of a human operator -- which makes large-scale drone delivery operations more practical and economical. Delivery drones offer fast service, with Walmart packages arriving between 10 and 30 minutes after an order is placed from stores up to 10 miles away. Walmart touts the technology for people who need missing cooking ingredients, last-minute birthday gifts, over-the-counter medications or movie night snacks.

Being stuck in traffic is a familiar problem for many Californians, but state officials want to harness the power of artificial intelligence to discover new solutions. The California Department of Transportation, teaming up with other state agencies, is asking technology companies by Jan. 25 to propose generative AI tools that could help California reduce traffic and make roads safer, especially for pedestrians, cyclists and scooter riders. Generative AI tools such as ChatGPT can quickly produce text, images and other content, but the technology can also help workers brainstorm ideas. The request shows how California is trying to tap into AI to improve government services at a time when lawmakers seek to safeguard against the technology's potential risks. California politicians set the stage for more AI regulation in 2024, but they'll also face challenges as they try to place more guardrails around AI's impact on jobs, safety and discrimination.

This one went smoothly -- no claims of rampant rigging, no significant taint of skulduggery -- due in large part to the defeat of deepfakes, democracy's newest enemy. Is such a future possible? So far, neither government nor the tech industry has agreed on effective guardrails against deepfakes. But this FAQ (from five years in the future) shows that the events of 2024 may well force the issue -- and that a solution is possible. Why did it take so long to find an effective way to fight deepfakes?

An artificial skin is helping a robot to recognise the difference between picking up inanimate objects and living sea creatures such as starfish and shellfish. That sense of touch could prove useful in cleaning up the ocean, doing underwater exploration or even carrying out deep-sea mining on the seafloor. The artificial skin's sense of touch harnesses what is known as the magnetoelastic effect – changes that occur in the magnetic field of materials as they are pushed and pulled.

Autonomous vehicles in San Francisco are exempt from traffic tickets if there is nobody in the driver's seat, according to the San Francisco police department (SFPD), underscoring ongoing legal and safety concerns surrounding the expanding technology. California law has not caught up to the cars, even though they are already on the road, say public safety agencies and experts. SFPD policy states that officers can make a traffic stop of autonomous vehicles (AVs) for violations, but can only issue a citation if there is a safety driver in the vehicle overseeing its operations. Since June 2022, autonomous vehicles have been permitted to operate without safety drivers as long as they are inside the city limits. Officers can issue citations to the registered owner of an unoccupied vehicle in absentia for non-moving violations such as parking or registration offenses but not violations like speeding, running a red light, driving in the wrong lane or making an illegal turn.

Hypergraphs play a pivotal role in the modelling of data featuring higher-order relations involving more than two entities. Hypergraph neural networks emerge as a powerful tool for processing hypergraph-structured data, delivering remarkable performance across various tasks, e.g., hypergraph node classification. However, these models struggle to capture global structural information due to their reliance on local message passing. To address this challenge, we propose a novel hypergraph learning framework, HyperGraph Transformer (HyperGT). HyperGT uses a Transformer-based neural network architecture to effectively consider global correlations among all nodes and hyperedges. To incorporate local structural information, HyperGT has two distinct designs: i) a positional encoding based on the hypergraph incidence matrix, offering valuable insights into node-node and hyperedge-hyperedge interactions; and ii) a hypergraph structure regularization in the loss function, capturing connectivities between nodes and hyperedges. Through these designs, HyperGT achieves comprehensive hypergraph representation learning by effectively incorporating global interactions while preserving local connectivity patterns. Extensive experiments conducted on real-world hypergraph node classification tasks showcase that HyperGT consistently outperforms existing methods, establishing new state-of-the-art benchmarks. Ablation studies affirm the effectiveness of the individual designs of our model.

The Pew survey results suggest that ChatGPT, at least for now, has not become the disruptive phenomenon in schools that proponents and critics forecast. Among the subset of teens who said they had heard about the chatbot, the vast majority -- 81 percent -- said they had not used it to help with their schoolwork. "Most teens do have some level of awareness of ChatGPT," said Jeffrey Gottfried, an associate director of research at Pew. "But this is not a majority of teens who are incorporating it into their schoolwork quite yet." Cheating has long been rampant in schools. In surveys of more than 70,000 high school students between 2002 and 2015, 64 percent said they had cheated on a test.