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First global rules adopted for self-driving cars: UN

The first global safety regulations for fully autonomous vehicles were adopted at the U.N., setting uniform international requirements that could pave the way for larger-scale rollouts. The framework is expected to enter into force in January 2027.

The first global regulations for fully autonomous vehicles were adopted Wednesday, a U.N. agency said, establishing uniform international safety requirements that could pave the way for larger-scale rollouts of self-driving cars.

Safety concerns and the cost of developing next-level systems have long slowed progress on autonomous vehicles.

As self-driving cars have begun to hit the road in a growing number of cities, fragmented national approaches to regulation have spurred manufacturer fears that vehicles developed for one market could be blocked from others.

Why Time Travel is Banned in China

Watch the full podcast! https://chinauncensored.tv/programs/p…
There are certain themes that movies in China can’t have, and one of them is time travel. In this clip we discuss China’s ban on time travel, how the CCP got Tesla and Elon Musk to heel, and why the CCP no longer needs Hollywood. Our guest is Chris Fenton, the producer of Bad Counselors, which comes to theaters July 22–27, 2026. https://www.badcounselors.com

Driverless cars are on the rise and now we may know why they crash

For the first time, new algorithms may be able to automatically explain why some self-driving cars crash—a question crucial to answer as more autonomous vehicles take to the roads. This new approach, developed by researchers at King’s College London, reviews past events to explain why specific instances of failure happened, in the hope that this can be used to make improvements in the future.

The research was presented at the 2026 IEEE International Conference of Robotics and Automation.

Self-driving vehicles are increasingly being rolled out across the globe, in cities like London and San Francisco, but collisions and serious breaches of road safety have put pressure on manufacturers to explain why they make the mistakes they do. This is often hard to do, and current methods only provide limited explanations for these.

ChartNet trains AI to read charts, boosting smaller models past commercial rivals

To accelerate and refine decision-making in a fast-paced, global marketplace, enterprises may deploy generative artificial intelligence models to help summarize and interpret the charts that often fill market summaries and financial reports.

But even the latest vision-language models sometimes struggle with this task, since it requires a model to integrate visual, numerical, and linguistic understanding. A company that invests in a state-of-the-art model might still receive inaccurate or incomplete information.

To fill this performance gap, researchers from MIT and the MIT-IBM Computing Research Lab developed a multifaceted resource for AI users that is specifically designed to teach vision-language models (VLMs) how to effectively interpret charts.

Geoffrey Hinton: “AI Is Already Conscious” | Big Technology Podcast

The “Godfather of AI” and Nobel laureate Geoffrey Hinton just said the quiet part out loud: he believes today’s AI is already conscious — and that our entire model of the mind is “as wrong as the belief that people were designed by God.” In this clip from the Big Technology Podcast, Hinton dismantles the “stochastic parrot” argument (“I think that’s complete nonsense”), explains why understanding a question is impossible without real comprehension, and walks through the Copernicus → Darwin → AI arc that he says will end humanity’s belief that it is special. Then he turns to the company at the center of the AI safety debate: Anthropic. Hinton argues that a publicly traded AI lab has “a fiduciary duty to maximize profits for shareholders — as opposed to legally required to not wipe out human beings,” and warns that Anthropic is “caught in a bind” trying to stay safe while raising the money it needs to compete. He closes with the line every founder and regulator should hear: progress is the accelerator, regulation is the steering wheel — and the big labs are asking us to let them build a very fast car without one. Chapters: 0:00 “I believe they’re already conscious” 0:05 Why “stochastic parrot” is nonsense 1:40 We’re about to become the cat 3:40 Anthropic is caught in a bind 5:00 Regulation is the steering wheel, not the brake Geoffrey Hinton won the 2024 Nobel Prize in Physics and is often called the Godfather of AI for his foundational work on deep learning and backpropagation. He left Google in 2023 to speak freely about AI risk. 🎙️ Full episode (Big Technology Podcast): • AI Pioneer Geoffrey Hinton: AI Is Consciou… 📺 Frontier Cut curates the sharpest clips from the world’s top AI and business podcasts. New episodes weekly. 🔔 Subscribe: @frontiercut #GeoffreyHinton #AI #Anthropic #AISafety #Superintelligence #AGI #BigTechnologyPodcast

AI-driven optical tweezers sort hundreds of particles per hour without humans

Just as self-driving cars navigate traffic without a human behind the wheel, laboratory instruments are now being developed that can design, carry out and repeat experiments independently, 24 hours a day.

Researchers at the University of Gothenburg and other institutions have now developed an AI system capable of speeding up the operation of optical tweezers, dubbed SmartTrap. The work has been published in Nature Methods.

The next step after nanotechnology

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Boston Dynamics’ AI-powered humanoid robot is learning to work in a factory

For decades, engineers have been trying to create robots that look and act human. Now, rapid advances in artificial intelligence are taking humanoids from the lab to the factory floor. As fears grow that AI will displace workers, a global race is underway to develop human-like robots able to do human jobs. Competitors include Tesla, startups backed by Amazon and Nvidia, and state-supported Chinese companies. Boston Dynamics is a frontrunner. The Massachusetts company, valued at more than a billion dollars, is hard at work on a humanoid it calls Atlas. South Korean carmaker Hyundai holds an 90% stake in the robot maker. As we first told you in January, we were invited to see the first real-world test of Atlas at Hyundai’s new factory near Savannah, Georgia. There, we got a glimpse of a humanoid future that’s coming faster than you might think.

Hyundai’s sprawling auto plant is about as cutting-edge as it gets. More than 1,000 robots work alongside almost 1,500 humans, hoisting, stamping and welding in robotic unison. This may look like the factory of the future, but we found the future of the future in the parts warehouse, tucked away in the back corner, getting ready for work.

Meet Atlas: A 5’9, 200 pound, AI-powered humanoid created by Boston Dynamics. The rise of the robots is science fiction no more.

Light-programmed system projects 28-layer 3D images in single shot

Researchers at the UCLA Samueli School of Engineering and CNSI (California NanoSystems Institute), led by Professor Aydogan Ozcan, introduced a snapshot 3D image projection system that integrates a digital encoder with a passive diffractive optical decoder, jointly optimized end-to-end through deep learning. The hybrid architecture projects multiple distinct images onto closely spaced axial planes in a single shot, marking a significant step toward compact, high-fidelity volumetric display technologies. The research is published in the journal Light: Science & Applications.

3D image display technology is essential for next-generation holography, immersive visualization, and augmented and virtual reality (AR/VR) interfaces, where accurate focal cues across depth are critical for natural depth perception and visual comfort. However, dense depth multiplexing in conventional holographic displays remains a challenge: As the axial image planes approach one another in the output volume, diffraction-induced crosstalk rapidly degrades depth selectivity and image fidelity.

Waymo unveils virtual driver model to test autonomous car crash avoidance

Autonomous vehicles are already a reality on some of our streets and could become a major part of future transportation systems. Safety, of course, is the main concern, as with all vehicles. To help evaluate and improve its autonomous driving technology, U.S. driverless vehicle company Waymo has created a virtual representation of human driver behavior in near-crash situations.

Human drivers avoid collisions by instantly perceiving a hazard, deciding how to react and then executing the maneuver. It all happens in a split second thanks to the central and peripheral nervous systems working together harmoniously.

Currently, testing and training for collision avoidance involve several systems, and each often tests only a specific scenario or metric. For example, one system might only look at what happens when a lead vehicle brakes suddenly. They do not capture the whole sequence of events from detection to actual avoidance.

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