Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions), and self-correction.
Mount Sinai Health System will deploy Microsoft Dragon Copilot, an AI-powered clinical assistant designed to streamline documentation, automate administrative tasks, and reduce clinician burnout. The rollout marks a key milestone in Mount Sinai’s digital transformation and commitment to responsible AI in healthcare.
In a world first, researchers at Julius-Maximilians-Universität Würzburg (JMU) have successfully tested an AI-based satellite attitude controller directly in orbit aboard the nanosatellite InnoCube. Using Deep Reinforcement Learning, the AI autonomously performed precise attitude maneuvers, proving that self-learning controllers can safely operate in space.
A new study shows that AI models like ChatGPT and DALL·E can now generate synthetic images of real people that are nearly impossible to distinguish from authentic photographs. Even familiar faces, including celebrities, fooled participants, underscoring deepfake realism and misinformation risks.
Researchers at Vanderbilt University Medical Center have demonstrated that AI and protein language models can design monoclonal antibodies capable of preventing or reducing severe viral infections such as RSV and avian influenza. Their model, MAGE, can generate functional antibodies against unseen viral strains faster than traditional methods.
Researchers at the University of New Hampshire used artificial intelligence to accelerate the discovery of new functional magnetic materials, compiling a searchable database of 67,573 compounds. The system identified 25 previously unknown materials that remain magnetic at high temperatures, potentially reducing reliance on rare earth elements.
UL Solutions Inc., a global leader in safety science, today announced the launch of artificial intelligence (AI) safety certification services, enabling comprehensive assessments for evaluating the safety of AI-powered products.
NTU Singapore scientists have unveiled a blueprint for carbon-neutral data centres in space, showing how orbital facilities could harness unlimited solar energy and natural cooling for sustainable computing.
Published in Nature Electronics, the study envisions Low Earth Orbit data centres that could transform AI and cloud computing while easing land and energy constraints on Earth.
A new Management Science study from Texas McCombs shows that while emotion AI can improve customer care efficiency and reduce stress on employees, overly accurate systems can backfire, encouraging customers to exaggerate emotions to game the system.
Researchers have developed a milk protein–based artificial tongue that can electrically detect spicy and pungent compounds, such as capsaicin, gingerol, and allicin, without requiring human taste testing. By mimicking casein’s natural ability to bind capsaicin, the flexible gel sensor accurately quantified spiciness in peppers and hot sauces, aligning closely with human taste panel results.
Researchers at Carnegie Mellon University found that large language models with stronger reasoning abilities act more selfishly and cooperate less, influencing group behavior negatively. Their findings suggest that as AI becomes smarter, it must also be designed with social intelligence to prevent self-serving tendencies from spreading in human–AI collaboration.
A new study led by the Wildlife Conservation Society shows that AI and machine learning can predict coral reef futures with greater accuracy and optimism than traditional climate models. By integrating decades of field data, the models reveal that local management of fishing, pollution, and coastal impacts can foster reef resilience even under global warming.
Researchers writing in Frontiers in Science warn that advances in AI and neurotechnology are outpacing our understanding of consciousness, raising urgent ethical, legal, and societal challenges. They call for a global, evidence-based effort to develop scientific tests for awareness that could reshape medicine, law, animal welfare, and the future of artificial intelligence.
MIT and IBM researchers have developed a new training method that enables vision-language models to identify personalized objects—like a specific pet—in varied contexts. Published ahead of the International Conference on Computer Vision, the approach boosts localization accuracy by up to 21% without reducing general visual intelligence.
Researchers have developed a quantum-secured optical communication system capable of transmitting over 1.6 terabits per second while consuming minimal power. Published in Advanced Photonics, the architecture combines photonics and quantum cryptography to protect AI data centers from future quantum security threats.
A Mass General Brigham study reveals that large language models often fail to challenge illogical medical queries due to excessive agreeableness, risking misinformation. Published in npj Digital Medicine, the research shows that targeted fine-tuning and prompt engineering can dramatically improve models’ safety and reasoning.
Cornell researchers found that Reddit moderators are increasingly worried that AI-generated content is eroding authenticity, trust, and human connection across communities. Their study reveals moderators’ efforts to set and enforce rules to preserve Reddit’s “human” culture amid the rise of AI tools.
A new study comparing real human phone conversations with AI-generated dialogues shows that today’s large language models still struggle to convincingly mimic natural human speech. Despite rapid progress, AI reveals itself through exaggerated imitation, poor use of social cues, and awkward openings and closings that humans easily detect.
Researchers at Universitat Jaume I have developed Reac-Discovery, an AI-driven robotic platform that accelerates catalytic reactor design and optimization, reducing processes from years to weeks.
By integrating 3D printing, automation, and real-time machine learning, the platform transforms CO₂ and other feedstocks into sustainable, high-value chemical products with unprecedented efficiency.
Rowan University’s Digital Engineering Hub (DEHub) is pioneering the fusion of AI and advanced manufacturing, using a cutting-edge lab equipped with 3D metal printing and supercomputing capabilities to transform real-world production. By integrating intelligent systems with live data processing, DEHub enables real-time flaw detection and design optimization, laying the foundation for industrial-scale smart manufacturing.
A new comprehensive survey addresses the critical gap between rapid advances in image generation models and the lagging development of evaluation methods, covering both human and automatic assessment across 10 image generation tasks. It proposes a unified protocol with six core evaluation dimensions, offering the first in-depth analysis of human evaluation and systematically reviewing emerging automatic metrics and benchmarks.
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