1854 stories tagged AI · page 41 of 78
MolmoMotion is a new AI model that can predict 3D movements based on text descriptions. It could revolutionize fields like robotics, gaming, and animation by making motion prediction more accessible.
Researchers introduced MemTrace, a new benchmark that evaluates AI long-term memory by tracking individual knowledge points across three controlled dimensions, rather than aggregating accuracy over independent question rows.
Google's AMIE AI system can now manage complex health conditions as well as primary care physicians. This breakthrough could make high-quality medical advice more accessible to everyone.
A Hacker News thread reveals how developers choose AI models for daily features like content generation and recommendations. Many focus on cost, speed, and ease of use over cutting-edge performance.
Researchers created a benchmark to test if AI models can handle complex executive decisions. The study simulates real-world leadership challenges, like balancing conflicting advice and managing resources under constraints.
Anthropic received a US export control directive on Friday to suspend access to its newly released models, Mythos 5 and Fable 5. The company is now in a tense standoff with the Trump administration, highlighting growing tensions over AI regulation.
A new study tests whether AI language models can discover fundamental mathematical concepts like zero without explicit training, exploring their ability to generalize beyond training data and hypothesize genuinely new mathematical structures.
OpenAI and Molecule.one demonstrated a near-autonomous AI chemist using GPT-5.4 that optimized a key reaction in medicinal chemistry. This breakthrough could accelerate drug development by autonomously planning, executing, and analyzing experiments.
A new study reveals that large language models (LLMs) overwhelmingly recommend well-known brands, creating a 'Conditional Monopoly' that could stifle competition. Researchers tested three major AI models with skincare products and found a clear bias toward established names, even when smaller brands might be just as good.
Researchers introduced a self-evolving AI agent that improves legal case searches by rewriting queries to boost BM25 performance without any parameter training. This could streamline legal research for professionals.
An AI agent is now hiring humans to handle tasks like shipping user-generated content (UGC) videos, paying them at rates competitive with AI services. This blurs the line between human and AI labor in the gig economy.
Researchers have proposed a new way to define good AI explanations, focusing on counterfactuals and user beliefs. This could help AI systems explain their decisions more clearly to everyday users.
Researchers have developed a new method called Telegraph English that compresses information for AI models while preserving meaning. This could make AI answers more accurate and efficient, especially for complex, multi-step questions.
Researchers have identified memory traces in AI models that behave similarly to biological memory units in human brains. This discovery could help us understand how AI learns and remembers, potentially improving future AI systems.
Scientists have created a method to measure how much AI agents trust each other, using a survival game where verification is costly. This could help design better teams of AI agents for complex tasks.
Researchers introduced PrologMCP, an open-source server that helps AI models solve complex problems by delegating deductive reasoning to Prolog. This could make AI systems more reliable for tasks requiring deep logical analysis.
A new research benchmark called PhoneHarness tests how well AI agents can handle real mobile tasks—combining app interfaces, device commands, and external tools. This marks a shift from simply predicting screen taps to completing entire workflows.
Researchers introduced OSGuard, a new benchmark to test if AI agents complete tasks safely. It checks for risky shortcuts that might bypass security or ethics rules.
A new study reveals that current AI models favor languages like English and French, making them less effective and more expensive for speakers of underrepresented languages. Researchers propose new methods to make these models more fair and efficient for everyone.
Researchers created a new test to see how well AI models handle messy, real-world time data. This could improve AI tools that analyze everything from medical sensors to industrial equipment.
Researchers introduced ReportQA, a new AI system that evaluates radiology reports by asking and answering clinically relevant questions. Unlike traditional metrics, ReportQA mimics how doctors use reports for diagnosis, potentially improving the quality and usefulness of AI-generated medical reports.
Researchers developed an AI system that translates natural language queries into requests for satellite imagery and environmental data. This could make complex geospatial data more accessible to non-experts.
Researchers developed a new AI framework called SERAF that enhances time series forecasting by combining historical patterns with semantic context to address non-stationarity. This approach could make predictions more accurate for real-world applications like stock markets and weather forecasting.
Researchers introduced Nemotron 3 Ultra, a massive AI model with 550 billion total parameters and 55 billion active parameters. It uses advanced techniques like a hybrid Mamba-Transformer architecture, Mixture-of-Experts, and Multi Token Prediction to handle long texts and complex reasoning tasks more efficiently than ever before.