A security researcher has revealed how Windows’ native AI infrastructure can be weaponized to deliver malware. The technique uses trusted ONNX files to bypass security engines, creating a new attack vector that current defenses aren’t equipped to detect.
Researchers have unveiled a comprehensive dataset of over 77,000 annotated plankton images from the Mediterranean Sea. This collection addresses a significant geographical gap in plankton monitoring data and supports multiple research applications. The dataset promises to accelerate machine learning development and enhance understanding of marine ecosystems.
Marine scientists have introduced a groundbreaking dataset of annotated plankton images from the Mediterranean Sea, according to recent reports. The MedPlanktonSet contains 77,271 taxonomically classified images collected using Imaging FlowCytobot (IFCB) technology between November 2022 and February 2025 at six stations in the Gulf of Naples. Sources indicate this represents the first comprehensive labeled IFCB dataset specifically for Mediterranean waters, filling a significant geographical gap in plankton research resources.
New approaches to AI skill development help professionals identify role-specific applications rather than chasing every emerging tool. Strategic prompting enables workers to pinpoint where AI delivers maximum career leverage and measurable impact according to industry analysis.
As artificial intelligence dominates workplace conversations, many professionals report feeling overwhelmed by the pressure to master every new tool while struggling to identify which skills actually matter for their specific roles. According to industry analysis, the key to effective AI adoption lies not in comprehensive technical training but in strategic application of the right tools to high-value tasks.
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Multimodal artificial intelligence is expanding beyond conventional vision and language applications to address complex global challenges. A new framework emphasizes early integration of deployment constraints and interdisciplinary collaboration. This approach could accelerate AI implementation in critical areas like healthcare, climate adaptation, and autonomous systems.
Artificial intelligence research is undergoing a significant shift toward practical implementation across diverse sectors, according to reports in Nature Machine Intelligence. While multimodal AI has traditionally focused on vision and language applications, analysts suggest the field is now expanding to incorporate broader data types and deployment considerations. This evolution aims to improve understanding, prediction, and decision-making across disciplines including healthcare, engineering, and scientific research.
Bridging Machine Learning and Physical Laws in Drug Discovery In the rapidly evolving field of AI-driven drug discovery, researchers are…
Bridging Genetic Diversity and Drug Response Through Machine Learning In a groundbreaking development for precision medicine in infectious diseases, researchers…
The Tor Project has removed Firefox’s artificial intelligence and machine learning components from its latest browser release, citing concerns about unaudited “black box” behavior. This move contrasts sharply with industry trends where major browsers are aggressively integrating AI capabilities. Developers have also implemented several security enhancements and user interface improvements in the new alpha version.
The Tor Project has taken a stand against the growing trend of artificial intelligence integration in web browsers by removing Firefox‘s AI and machine learning components from the latest Tor Browser alpha release. According to reports, this decision stems from the development team’s inability to properly audit the code and behavior of these machine learning models, which they describe as “black box” systems with potentially unpredictable outcomes.
