Imagine sitting at a desk, eyes fixed on a blank screen, fingers hovering over keys you never touch. A sentence forms in your mind. Moments later, the computer displays the words you intended. For someone whose body no longer responds to the brain’s commands, that simple act of communication can feel out of reach. Brain-computer interfaces aim to close the gap by reading patterns of neural activity and converting them into text or device commands. In their paper “Noninvasive decoding of type
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Millions of photos go online every day. Most people still treat a face in a picture as belonging to the person who is depicted. That assumption may no longer hold true. Software can now lift a face from one photograph and drop it into a completely different scene, or put a stranger’s face into someone else’s original setting while keeping the pose, expression, clothes, and background. The results look real enough that ordinary viewers, and sometimes the detection software itself, accept them
Artificial Intelligence is now fundamentally integrated into the planning and execution of cyber-attacks. Europol’s 2026 threat assessment report identifies the combination of automation and AI as a defining feature of modern criminal ecosystems. AI vulnerabilities and AI-enabled fraud are becoming primary concerns for global organizations. Phishing demonstrates this transition clearly. AI-generated messages are increasingly personalized and context-aware, accurately mirroring internal corpo
A regional court in Munich has determined that Google bears legal responsibility for statements produced by its artificial intelligence within search results. This follows a legal case in which the AI generated false allegations against two publishers based in Munich. This unprecedented decision serves as a significant signal across the globe; the judiciary is reminding the platform of its duties in shaping the modern information environment. Google has launched an appeal against the verdict.
The Ukrainian military is stepping up its campaign to destroy vehicles supplying Russian forces along crucial roads in occupied Ukraine using new AI drone technology. Ukraine is starting to regain more ground than it is losing for the first time since 2023, analysis from the Institute for the Study of War (ISW) indicates.
After more than four years of war and increased Russian occupation of eastern and southern Ukraine, neither side has gained any significant ground in recent months.[1]
Ukrain
The Artificial Intelligence (AI) data center insurance market is expanding rapidly due to the increasing adoption of AI technologies, rising cyber threats, and heightened demand for comprehensive risk management solutions. For decades, insurance has relied on historical averages and pooled risk. That model is breaking down; over the past several years, insured losses from natural catastrophes have exceeded US$100 billion each year. In Canada, they were the costliest ever. The country’s wildf
Artificial intelligence has become integral to contemporary cyber-attack planning and execution. Recent research demonstrates how embedded AI systems now operate across organized cybercrime activities, fundamentally altering attack methodologies through increased speed and targeting precision. Europol's 2026 threat assessment identifies the integration of automation and AI as a defining characteristic of modern cybercrime. Industry reporting indicates that AI vulnerabilities and AI-enabled fra
Imagine you're a chief executive. Your AI strategy task force has just presented you with two strategic options. The first one is safe. You can use agentic AI to reduce overhead and save 10% of overall human capital costs.
With attackers able to move at AI speed, defenders cannot rely on the techniques and instincts they have come to trust. "That means putting in place stronger identity controls," said Jack Butler, a senior enterprise solutions engineer at Sumo Logic, a SecOps vendor. "That means putting in place the more robust logging program and correlation engines to detect all of these in real time and reassess signals of trust. It needs to be reassessed dynamically."[1]
As for what to do about the substan
The surge in security vulnerabilities stems primarily from organizations’ increasing adoption of agentic AI applications, particularly those utilizing technologies such as Model Context Protocol (MCP). This rapid deployment, combined with immature security practices and emerging attack vectors, is creating substantial risk exposure across the enterprise landscape.[1]
Senior Director Analyst at Gartner, Aaron Lord, explained that MCP's design philosophy prioritizes interoperability, ease of use,
SonicWall has launched its 2026 Cyber Protect Report, marking a significant shift in how the organization presents threat intelligence. Rather than focusing solely on raw data, the report prioritizes protection outcomes for business leaders. The findings indicate that while the volume of attacks remains high, adversaries are becoming more precise, with medium and high-severity incidents rising by over 20% to reach 13 billion hits.
One of the most significant findings in the 2026 report is the
Most people think of Dungeons and Dragons (D&D) as a place for imagination, dice, and heroic misadventures. Yet a team of computer scientists has turned this iconic tabletop game into something far more ambitious: a laboratory for understanding how artificial intelligence behaves when it must operate independently for long periods. Their research paper, Setting the DC: Tool-Grounded D&D Simulations to Test LLM Agents, paired with the recent TechXplore article on the same work, reveals why D&D
Ollama is an open-source framework that enables users to run large language models locally on their own hardware. By design, the service binds to localhost (127.0.0.1) on port 11434, making instances accessible only from the host machine. However, exposing Ollama to the public internet requires only a single configuration change: setting the service to bind to 0.0.0.0 or a public interface. At scale, these individual deployment decisions aggregate into a measurable public surface.[1]
Over the p
Large language models have become the engines behind some of the most impressive feats in contemporary computing. They write complex software, summarize scientific papers, and navigate intricate chains of reasoning. Yet as a recent study shows, these same systems falter on a task that most ten-year-olds can perform with pencil and paper. According to a new article from TechXplore and the accompanying research paper Why Can’t Transformers Learn Multiplication? Reverse-Engineering Reveals Long
A federal judge in New York has affirmed an order compelling OpenAI to produce 20 million anonymized ChatGPT interaction logs in a consolidated copyright infringement case, according to a Bloomberg report. The decision, issued on 5 January 2026, marks a setback for the AI company amid ongoing litigation over the use of copyrighted material in its model training. The ruling stems from multidistrict litigation involving 16 lawsuits against OpenAI, brought by news organizations including The New Y
The slow-motion Russian invasion of Ukraine has highlighted persistent vulnerabilities in Western military readiness, specifically concerning munitions stockpiles, supply chain resilience, and procurement agility. As the conflict continues, nations are adjusting their force posture and defense planning. These changes aim not only to support Ukraine but also to prepare for the realities of prolonged, multi-domain warfare.
While quantum computing and automation are shaping the following stages o
In an age where artificial intelligence is increasingly trusted to judge human expression, a subtle but essential flaw has emerged. Large language models (LLMs), the same systems that generate essays, screen job applications, and moderate online discourse, appear to evaluate content fairly, until they’re told who wrote it. A new study by researchers Federico Germani and Giovanni Spitale at the University of Zurich, published in Science Advances, reveals that LLMs exhibit systematic bias when t
In an age where artificial intelligence is increasingly trusted to judge human expression, a subtle but essential flaw has emerged. Large language models (LLMs), the same systems that generate essays, screen job applications, and moderate online discourse, appear to evaluate content fairly, until they’re told who wrote it. A new study by researchers Federico Germani and Giovanni Spitale at the University of Zurich, published in Science Advances, reveals that LLMs exhibit systematic bias when t
In an age where artificial intelligence is increasingly trusted to judge human expression, a subtle but essential flaw has emerged. Large language models (LLMs), the same systems that generate essays, screen job applications, and moderate online discourse, appear to evaluate content fairly, until they’re told who wrote it. A new study by researchers Federico Germani and Giovanni Spitale at the University of Zurich, published in Science Advances, reveals that LLMs exhibit systematic bias when t
In an age where artificial intelligence is increasingly trusted to judge human expression, a subtle but essential flaw has emerged. Large language models (LLMs), the same systems that generate essays, screen job applications, and moderate online discourse, appear to evaluate content fairly, until they’re told who wrote it. A new study by researchers Federico Germani and Giovanni Spitale at the University of Zurich, published in Science Advances, reveals that LLMs exhibit systematic bias when t
