Hyundai Motor Group says it will roll out human-like robots in its factories from 2028, as major companies race to use the new technology. The South Korean firm showed off Atlas, a humanoid robot developed by Boston Dynamics, at the Consumer Electronics Show (CES) in Las Vegas on Monday. Hyundai says it plans to integrate Atlas across its global network, including a plant in the US state of Georgia that was involved in a massive immigration raid in 2025 . Other firms that have said they will use humanoid robots in their operations include Amazon, Tesla and Chinese car making giant BYD. The Atlas robots will gradually take on more tasks, said Hyundai.

When you purchase through links in our articles, we may earn a small commission. Unveiled at CES under the new Goko brand, the consumer-focused M6 borrows engineering from RobotPlusPlus's industrial robots to tackle steep inclines, rough terrain, and large lawns. Known primarily for robots that scale steel structures and automate hazardous industrial maintenance, RobotPlusPlus is at CES this week trying something new: a robot lawn mower for everyday consumers. Developed with the same engineering used in industrial surface-climbing robots, the flagship M6 is designed to handle real-world residential terrain, including steep slopes, uneven ground, and large lawn areas. The company claims the unit can traverse inclines up to 90 percent and clear obstacles as high as 75 mm (2.6 inches), capabilities uncommon among consumer-grade mowers.

Jensen Huang speaks at CES in Las Vegas on Monday. Jensen Huang speaks at CES in Las Vegas on Monday. Next generation of chips in'full production' and will arrive later this year, Jensen Huang says at CES in Las Vegas Nvidia CEO Jensen Huang said on Monday that the company's next generation of chips is in "full production" saying they can deliver five times the artificial-intelligence computing of the company's previous chips when serving up chatbots and other AI apps. In a speech at the Consumer Electronics Show in Las Vegas, the leader of the world's most valuable company revealed new details about its chips, which will arrive later this year and which Nvidia executives are in the company's labs being tested by AI firms, as Nvidia faces increasing competition from rivals as well as its own customers. The Vera Rubin platform, made up of six separate Nvidia chips, is expected to debut later this year, with the flagship server containing 72 of the company's graphics units and 36 of its new central processors.

For Taro Ueno, a psychiatrist and president of Susmed, the idea to develop an app for insomnia came from observing how doctors in Japan overprescribe sleeping pills. Japan's medical industry has generally been slow to embrace digital technology, with many clinics still keeping patient records and writing prescriptions on paper. But a few domestic startups have recently launched chatbot-powered apps designed to help treat a range of conditions, such as hypertension, alcohol addiction and insomnia. Unlike the plethora of lifestyle apps anyone with a smartphone can download, these are prescription-only medical apps whose efficacy has been demonstrated in clinical trials. For Taro Ueno, a psychiatrist and brain researcher, the idea to develop an app for insomnia came from observing how doctors in Japan overprescribe sleeping pills. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Nvidia CEO Jensen Huang speaks about autonomous-driving vehicles during a Nvidia keynote address at CES 2026, an annual consumer electronics trade show, in Las Vegas, Nevada, on Monday. LAS VEGAS - Autonomous driving technology is expected to dominate the CES trade show in Las Vegas this week as investors bet that artificial intelligence will invigorate an industry beset by slow progress, high costs, safety incidents and regulatory scrutiny. Just as automakers have hit the brakes on electric vehicle (EV) plans and look for their next money maker, a slew of auto suppliers and start ups are lining up to show off their latest autonomous vehicle hardware and software. Partnerships and deals that promise to take away much of a driver's responsibilities, or remove the need for a human driver completely, are expected to be announced. This year you will see more and more focus on AI and autonomous, said C.J. Finn, U.S. automotive industry leader for PwC, adding that how companies use AI to solve the challenge of rolling out driverless cars safely will be closely watched. That connectivity on autonomous, I do think will be front and center.

A supporter of Maduro holds a painting of him in Caracas. A supporter of Maduro holds a painting of him in Caracas. Minutes after Donald Trump announced a "large-scale strike" against Venezuela early on Saturday morning, false and misleading AI-generated images began flooding social media. There were fake photos of Nicolás Maduro being escorted off a plane by US law enforcement agents, images of jubilant Venezuelans pouring into the streets of Caracas and videos of missiles raining down on the city - all fake. The fabricated content intermixed with real videos and photos of US aircraft flying over the Venezuelan capital and explosions lighting up the dark sky.

When you purchase through links in our articles, we may earn a small commission. Ecovacs' latest robot mower adds smarter mapping and an integrated trimmer The Goat LiDAR Pro arrives at CES with the promise of solving common robot mower complaints, from poor edge coverage to inconsistent navigation. Ecovacs has introduced a new robot mower at CES as the company pushes further into lawn care. The Goat LiDAR Pro brings smarter navigation and more complete edge trimming, aiming to reduce the cleanup typically left behind by earlier-generation robot mowers. Equipped with Ecovacs's HoloScope 360 suite, the Goat LiDAR Pro uses a combination of LiDAR and vision sensors to map the mowing area in three dimensions, enabling more precise path planning and obstacle avoidance.

Graphs arise across diverse domains, from biology and chemistry to social and information networks, as well as in transportation and logistics. Inference on graph-structured data requires methods that are permutation-invariant, scalable across varying sizes and sparsities, and capable of capturing complex long-range dependencies, making posterior estimation on graph parameters particularly challenging. Amortized Bayesian Inference (ABI) is a simulation-based framework that employs generative neural networks to enable fast, likelihood-free posterior inference. We adapt ABI to graph data to address these challenges to perform inference on node-, edge-, and graph-level parameters. Our approach couples permutation-invariant graph encoders with flexible neural posterior estimators in a two-module pipeline: a summary network maps attributed graphs to fixed-length representations, and an inference network approximates the posterior over parameters. In this setting, several neural architectures can serve as the summary network. In this work we evaluate multiple architectures and assess their performance on controlled synthetic settings and two real-world domains -- biology and logistics -- in terms of recovery and calibration.

We study the extent to which standard machine learning algorithms rely on exchangeability and independence of data by introducing a monotone adversarial corruption model. In this model, an adversary, upon looking at a "clean" i.i.d. dataset, inserts additional "corrupted" points of their choice into the dataset. These added points are constrained to be monotone corruptions, in that they get labeled according to the ground-truth target function. Perhaps surprisingly, we demonstrate that in this setting, all known optimal learning algorithms for binary classification can be made to achieve suboptimal expected error on a new independent test point drawn from the same distribution as the clean dataset. On the other hand, we show that uniform convergence-based algorithms do not degrade in their guarantees. Our results showcase how optimal learning algorithms break down in the face of seemingly helpful monotone corruptions, exposing their overreliance on exchangeability.

AB S TRACT This study evaluates the performance of various classifiers in three distinct models: r esponse, r isk, and r esponse - r isk, concerning credit card mail campaigns and default prediction. In the r esponse model, the Extra Trees classifier demonstrates the highest recall level (79.1%), emphasizing its effectiveness in identifying potential responders to targeted credit card offers. Conversely, in the r isk model, the Random Forest classifier exhibits remarkable specificity of 84.1%, crucial for identifying customers least likely to default. Furthermore, in the multi - class r esponse - r isk model, the Random Forest classifier achieve s the highest accuracy (83.2%), indicating its efficacy in discerning both potential responders to credit card mail campaign and low - risk credit card users . In this study, we optimized various performance metrics to solve a specific credit risk and mail responsiveness business problem.