ShadowLeak zero-click flaw in ChatGPT Deep Research leaks Gmail data via hidden HTML prompts, bypassing security
Category: robotics/AI – Page 8
17,500 Phishing Domains Target 316 Brands Across 74 Countries in Global PhaaS Surge
The phishing-as-a-service (PhaaS) offering known as Lighthouse and Lucid has been linked to more than 17,500 phishing domains targeting 316 brands from 74 countries.
“Phishing-as-a-Service (PhaaS) deployments have risen significantly recently,” Netcraft said in a new report. “The PhaaS operators charge a monthly fee for phishing software with pre-installed templates impersonating, in some cases, hundreds of brands from countries around the world.”
Lucid was first documented by Swiss cybersecurity company PRODAFT earlier this April, detailing the phishing kit’s ability to send smishing messages via Apple iMessage and Rich Communication Services (RCS) for Android.
Microsoft starts rolling out Gaming Copilot on Windows 11 PCs
Microsoft has begun rolling out the beta version of its AI-powered Gaming Copilot to Windows 11 systems for users aged 18 or older, excluding those in mainland China.
Tagged as a “personal gaming sidekick,” Gaming Copilot will also be pushed to Xbox mobile app users on Apple and Android devices starting next month.
To start using Gaming Copilot in the Game Bar, Windows users must install the Xbox PC app on their PC and use the Windows logo key + G keyboard shortcut to open the Game Bar. Next, they can find the Gaming Copilot icon in the Home Bar, open the widget, and log in to their Xbox account.
Scientists Train AI to Forecast Over 1,000 Diseases, Years in Advance
Scientists said Wednesday that they had created an AI model able to predict medical diagnoses years in advance, building on the same technology behind consumer chatbots like ChatGPT.
Based on a patient’s case history, the Delphi-2M AI “predicts the rates of more than 1,000 diseases” years into the future, the team from British, Danish, German and Swiss institutions wrote in a paper published in the journal Nature.
Researchers trained the model on data from Britain’s UK Biobank – a large-scale biomedical research database with details on about half a million participants.
Intel & NVIDIA Announce Strategic Collaboration
This collaboration will integrate NVIDIA’s AI and accelerated computing technologies with Intel’s CPUs and x86 ecosystem, using NVIDIA NVLink for seamless connectivity.
For data centers, Intel will build NVIDIA-custom x86 CPUs that NVIDIA will integrate into its AI infrastructure platforms and offer to the market. However, the spotlight is on personal computing, for which Intel will build and offer to the market x86 system-on-chips (SOCs) that integrate NVIDIA RTX GPU chiplets. These new x86 RTX SoCs are designed to “power a wide range of PCs that demand integration of world-class CPUs and GPUs.”
Are tech monopolies just becoming even bigger monopolies with less competition? It’s worth noting that Intel has actually done something similar before with AMD, and Kaby Lake-G is now largely viewed as a failure. Still, it’s hard to imagine this happening if Intel weren’t facing serious challenges. NVIDIA’s $5 billion investment in Intel, through common stock purchased at $23.28 per share, goes beyond a mere hint.
AI model offers accurate and explainable insights to support autism assessment
Scientists have developed and tested a deep-learning model that could support clinicians by providing accurate results and clear, explainable insights—including a model-estimated probability score for autism.
The model, outlined in a study published in eClinicalMedicine, was used to analyze resting-state fMRI data—a non-invasive method that indirectly reflects brain activity via blood-oxygenation changes.
In doing so, the model achieved up to 98% cross-validated accuracy for Autism Spectrum Disorder (ASD) and neurotypical classification and produced clear, explainable maps of the brain regions most influential to its decisions.
New light-powered gears fit inside a strand of hair
Researchers at the University of Gothenburg have made light-powered gears on a micrometer scale. This paves the way for the smallest on-chip motors in history, which can fit inside a strand of hair. The research is published in the journal Nature Communications.
Gears are everywhere—from clocks and cars to robots and wind turbines. For more than 30 years, researchers have been trying to create even smaller gears in order to construct micro-engines. But progress stalled at 0.1 millimeters, as it was not possible to build the drive trains needed to make them move any smaller.
Researchers from Gothenburg University, among others, have now broken through this barrier by ditching traditional mechanical drive trains and instead using laser light to set the gears in motion directly.
The AI model that teaches itself to think through problems, no humans required
Artificial intelligence is getting smarter every day, but it still has its limits. One of the biggest challenges has been teaching advanced AI models to reason, which means solving problems step by step. But in a new paper published in the journal Nature, the team from DeepSeek AI, a Chinese artificial intelligence company, reports that they were able to teach their R1 model to reason on its own without human input.
When many of us try to solve a problem, we typically don’t get the answer straight away. We follow a methodical process that may involve gathering information and taking notes until we get to a solution. Traditionally, training AI models to reason has involved copying our approach. However, it is a long, drawn-out process where people show an AI model countless examples of how to work through a problem. It also means that AI is only as good as the examples it is given and can pick up on human biases.
Instead of showing the R1 model every step, researchers at DeepSeek AI used a technique called reinforcement learning. This trial-and-error approach, using rewards for correct answers, encouraged the model to reason for itself.