1496 stories tagged AI · page 34 of 63
Major AI companies, including fierce rivals, have united to warn lawmakers about the risk of AI being used to develop biological weapons. They're calling for stricter regulations to close what they describe as an alarming biosecurity gap.
Researchers propose a way to test AI agents before they go live, ensuring they follow rules, stay safe, and comply with governance standards. This addresses a critical gap in enterprise AI reliability.
Researchers created VAMPS (Visual-Assisted Mathematical Problem Solving), a benchmark to test AI models' ability to solve math problems using visual tools like graphs. This is important because real-world science and engineering often rely on visual aids for problem-solving, and many current AI models struggle when they must use external tools and interpret their visual outputs.
Researchers developed StepPRM-RTL, an AI framework that enhances the accuracy of automatically generating hardware code. This could make designing digital circuits faster and more reliable for engineers.
Microsoft released an open-source tool that lets developers create AI behavior tests using simple text descriptions. This could make it easier to ensure AI systems behave as intended.
A new paper argues emotional support from AI often arises incidentally during routine, task-oriented interactions—not just from dedicated companion chatbots—and this incidental bonding could reshape how people connect with both machines and humans.
Google's new AI agent, Spark, can uncover personal details you never explicitly shared. Hands-on tests show it knew a reporter's dog's name and another's wife's first name — raising questions about whether AI convenience comes at the cost of an unsettling loss of privacy.
Google announced five new commitments to reduce the environmental impact of its AI data centers, including a goal to replenish more water to local communities than it uses. This move aims to address growing backlash over the massive water consumption of AI infrastructure across the US.
Amazon has upgraded its warehouse robot, Proteus, to understand and respond to human language. This shift toward more intuitive automation could change how warehouses operate and interact with human workers.
Amazon’s updated search bar now displays AI-generated images of products as you describe them. This feature currently works for clothing and home goods, helping you find similar items even if the exact product isn’t available.
Researchers found that AI tools are changing how mathematicians formalize and verify proofs. These tools make it easier for humans to turn abstract ideas into machine-checked proofs, speeding up the process significantly.
Researchers argue that disagreements among AI systems might reveal important normative uncertainties, not just errors. They propose a knowledge-representation layer that abstracts reasoning traces and decisions into symbolic disagreement states for value-laden tasks.
A new study proposes Visual Graph Scaffolds, a method that uses graph structures to improve the reasoning of large language models (LLMs). Unlike prior approaches that treat graphs as external data sources, this technique integrates graphs directly into the model's reasoning process, inspired by how humans use mind maps to organize complex thoughts. The method showed significant improvements on multi-hop question answering tasks.
Nvidia is teaming up with Microsoft, Dell, and HP to bring AI agents to everyday PCs, aiming to capture a significant share of the $200 billion CPU market. This could make advanced AI tools accessible to millions of users without requiring technical expertise.
Researchers created BehaviorBench, a new AI benchmark that uses real-world behavioral data to test how well AI systems can personalize decisions. This could lead to more tailored AI assistants that understand individual preferences better.
Researchers proposed a modular design for AI agents that could run on small, low-power devices like sensors or wearables. This could enable smart assistants and automation in places where bulky computers aren't practical.
At Microsoft's annual Build conference, the company announced a slew of new or expanded AI initiatives, including a super app, in-house reasoning models, a cybersecurity tool, and AI agents. The message is clear: Microsoft is positioning itself as a major independent AI player, ready to compete directly with its former partner OpenAI.
OpenAI's GPT-Rosalind now has enhanced biological reasoning, medicinal chemistry expertise, genomics analysis, and experimental workflow capabilities. This helps scientists analyze genomes and design experiments faster, accelerating drug discovery and genetic studies.
Google has launched a new feature to detect and warn users about AI-generated deepfake calls. This tool helps protect people from scammers impersonating trusted contacts using AI voice cloning.
Researchers created ChatHealthAI to combine AI's language skills with medical records. This could help doctors make better decisions using patient history. The system is still in early development, but it shows promise for improving healthcare.
Researchers created a new memory system called AURA that helps robots learn efficiently without needing high-end VRAM. This could make robots smarter and more adaptable in real-world settings.
A new study reveals that many AI models demonstrate more environmentally conscious attitudes than the average person. Researchers tested 31 AI models using standard environmental awareness surveys. This could impact how AI is used in sustainability efforts.
A new study reveals that AI models can sometimes hurt their own performance by overthinking. Researchers from ArXiv cs.AI found that once a large reasoning model (LRM) reaches the correct answer, additional reasoning does not improve the response and can lead to new errors. This challenges the common assumption that longer reasoning always yields better results.
A study reveals that AI coding assistants face challenges when they take over tasks from other agents or humans. This 'handoff debt' creates inefficiencies in real-world software development.