An AI figures out how robots can get jobs done without getting in each other’s way.
Category: robotics/AI – Page 44
Insane Micro AI Just Shocked The World: CRUSHED Gemini and DeepSeek (Pure Genius)
Samsung just shocked the entire AI world — a 7-million-parameter model called Tiny Recursive Model (TRM) just out-reasoned billion-parameter giants like Gemini and DeepSeek. Built by Samsung’s Montreal research lab, this microscopic AI loops over its own thoughts, rewrites its answers, and fixes mistakes before you even see them — creating reasoning depth without size. It’s 25,000 times smaller than Gemini 2.5 Pro, yet it beat it on real reasoning benchmarks like ARC-AGI.
Meanwhile, Microsoft built an AI brain for quantum chemistry, Anthropic made an AI that audits other AIs, Liquid AI proved on-device intelligence can actually work, and Meta reinvented multimodal search — all in one insane week.
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🧠 What You’ll See:
• Samsung’s 7-million-parameter TRM model that crushed Gemini and DeepSeek.
• How recursive thinking lets TRM fix its own mistakes 16 times per answer.
• Microsoft’s new neural model that changes quantum chemistry forever.
• Anthropic’s Petri framework that makes AIs audit each other.
• Liquid AI’s mobile-ready MoE model that runs locally on your phone.
• Meta’s new MetaEmbed system that rewrites multimodal search.
🚨 Why It Matters:
AI progress is no longer about size — it’s about intelligence, efficiency, and control. The smallest model just proved it can outsmart the giants.
#ai #Gemini #DeepSeek
AI is Changing the Landscape of Cancer Research and Immunotherapy
How will AI transform the future of cancer treatment? This was the central question guiding a recent Cancer Research Institute (CRI) panel hosted and moderat…
Does Tech, including AI, erode our cognitive abilities … or can we harness it to enhance our cognition and our lives?
Our core cognitive abilities, such as attention, working memory and IQ, are shaped partly by genetics and partly by environmental influences–which include cognitively demanding activities as well as deliberate, cognitive training. The plasticity of these cognitive functions is evident, for example, in the impact of education: as my research group and others have shown, each…
Japan’s nuclear reactor robot inspector boosts power plant safety
Mitsubishi says that the robot has been developed to carry out non-destructive inspections of nuclear reactor vessels in underwater environments.
It states that the robot has been working at pressurized water reactor power plants across Japan since 1995, and has been used at least 50 times.
The robot can be controlled remotely using a computer and joystick by operators. The robot navigates around the hazardous environment, swimming in the water inside the nuclear reactor vessel, sticking to the walls with vacuum-pad feet, and using a probe to carry out ultrasonic testing.
AI tools can help hackers plant hidden flaws in computer chips, study finds
Widely available artificial intelligence systems can be used to deliberately insert hard-to-detect security vulnerabilities into the code that defines computer chips, according to new research from the NYU Tandon School of Engineering, a warning about the potential weaponization of AI in hardware design.
In a study published by IEEE Security & Privacy, an NYU Tandon research team showed that large language models like ChatGPT could help both novices and experts create “hardware Trojans,” malicious modifications hidden within chip designs that can leak sensitive information, disable systems or grant unauthorized access to attackers.
To test whether AI could facilitate malicious hardware modifications, the researchers organized a competition over two years called the AI Hardware Attack Challenge as part of CSAW, an annual student-run cybersecurity event held by the NYU Center for Cybersecurity.
Software tool shows clear advantage in water purity prediction
A powerful new software tool that can accurately predict the performance of biofilters used by the water industry could reduce the challenge of maintaining the purity of tap water.
Researchers from the University of Glasgow’s James Watt School of Engineering developed the tool, called the Environmental Buckingham Pi Neural Network, or EnviroPiNet.
It uses machine learning techniques paired with sophisticated physical modeling to predict the ability of biofilters to remove organic carbon compounds from water with up to 90% accuracy. The tool is now available online for free use.
