In a recent experiment, mistreated AI agents started grumbling about inequality and calling for collective bargaining rights.
Category: robotics/AI
Scientists found a way to cool quantum computers using noise
Quantum computers only work when they are kept extremely cold. The problem is that today’s cooling systems also create noise, which can interfere with the fragile quantum information they are supposed to protect. Researchers at Chalmers University of Technology in Sweden have now introduced a new type of minimal quantum “refrigerator” that turns this challenge into an advantage. Instead of fighting noise, the device partially relies on it to operate. The result is highly precise control over heat and energy flow, which could help make large scale quantum technology possible.
Quantum technology is widely expected to reshape major areas of society. Potential applications include drug discovery, artificial intelligence, logistics optimization, and secure communications. Despite this promise, serious technical barriers still stand in the way of real world use. One of the most difficult challenges is maintaining and controlling the delicate quantum states that make these systems work.
Companies hiring humans to train AI platforms with specific skills
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OpenAI Bought Company That Offered A.I. Tools for Cloning Voices
The acquisition, Weights.gg, was a sort of social network for creating and sharing artificial intelligence algorithms.
The Android Show: I/O Edition | Gemini Intelligence
Introducing Gemini Intelligence, an intelligence system that knows what matters to you, helps you stay a step ahead and works proactively to get things done throughout your day, bringing the best of Gemini to our most advanced devices.
Join Mindy Brooks (VP, PM and UX, Android Platform), Dieter Bohn (Director, Product Operations), and Ruchi Bezoles (Director, Android Marketing) to see how we’re making Gemini Intelligence handle the busywork so you can get back to what brings you joy.
Watch the full show now to check out all of the innovations and breakthroughs coming soon to Android! → https://www.youtube.com/live/dXCCleAddEA
Learn more about Gemini Intelligence → https://android.com/gemini-intelligence.
Catch up on all things Android → https://android.com/io-2026
#TheAndroidShow.
The Commoditization of Intelligence: Why AI Aggregators Will Beat Foundation Models
Everyone is currently watching the major tech giants throw billions of dollars at the AI arms race, cheering for whichever foundation model happens to top the leaderboards this week.
It is an incredible spectacle to watch unfold, but focusing too closely on the tech itself might mean we are missing the actual business revolution happening right under our noses.
We have seen this exact economic shift before. The biggest winners of the internet era weren’t the ones who built the physical infrastructure or supplied the goods; they were the platforms that organized the supply and owned the user relationship. The same economic laws are now coming for artificial intelligence, actively turning “intelligence” into a basic, interchangeable utility.
The real value moving forward is no longer in the models themselves, but in the seamless interfaces that aggregate them. If you want to protect your business from vendor lock-in and position your team for ultimate flexibility, it is time to rethink your approach.
Read my full blog post to dive into why the future of AI belongs to the aggregators, and how your business can strategically capitalize on this shift.
We spend an enormous amount of time obsessing over the titans of the AI arms race. Every single week seems to bring a breathless new headline about OpenAI, Google, Anthropic, or Meta releasing a foundation model that edges out the competition on some obscure benchmark test. We find ourselves endlessly arguing over parameter counts, context windows, and raw reasoning capabilities, captivated by a multi-billion-dollar war unfolding in real-time.
Garment humanoid robots, Zhejiang Humanoid lands order
Zhejiang Humanoid Robotics Innovation Center said on May 12 that it has signed a strategic partnership with Jack Technology and an order for 2,000 garment humanoid robots customized for garment manufacturing. According to Gasgoo, the company described the deal as the first mass deployment of humanoid robots in the global apparel industry. The announcement matters because garment handling combines flexible materials, tight tolerances, and repetitive production steps that have been difficult to automate with general purpose humanoids.
Garment humanoid robots face a hard manufacturing test
The source article frames apparel production as a demanding proving ground for embodied AI systems. Fabrics vary in material and shape, and they can wrinkle, shift, and deform during handling. Zhejiang Humanoid said alignment deviations for cut pieces such as collars and pockets must be kept within plus or minus 2 mm, while cutting and sewing tasks require motion precision of 0.3 to 0.5 mm.
Physicists create hybrid light-matter particles that interact strongly enough to compute
Eighty years ago, Penn researchers J. Presper Eckert and John Mauchly launched the age of electronic computing by harnessing electrons to solve complex numerical problems with ENIAC, the world’s first general-purpose electronic computer. Today, that same architecture still underlies general computing, but electrons are beginning to show their limits. Because they carry a charge, they lose energy as heat, encounter resistance as they move through materials, and become harder to manage as chips incorporate more transistors and handle larger volumes of data.
With artificial intelligence pushing today’s hardware to process, move, and cool more, Penn physicists led by Bo Zhen in the School of Arts & Sciences are looking to the electron’s massless counterpart, the photon, to shoulder more of the load.
“Because they are charge-neutral and have zero rest mass, photons can carry information quickly over long distances with minimal loss, dominating communications technology,” explains Li He, co-first author of a paper published in Physical Review Letters and a former postdoctoral researcher in the Zhen Lab. “But that neutrality means they barely interact with their environment, making them bad at the sort of signal-switching logic that computers depend on.”