All 3,125 AI stories, newest first · page 18 of 131
A new study from MIT and Stanford published in Nature reveals that large language models often produce logically correct answers by mimicking surface-level patterns rather than demonstrating genuine reasoning, raising reliability concerns for critical applications in healthcare, finance, and law.
Researchers introduced HSS-Synth, the first data synthesis pipeline specifically designed for humanities and social sciences (HSS). It covers 14 mainstream fields and aims to generate high-quality, diverse training data for large language models (LLMs) in open-ended domains.
avatarin used OpenAI’s GPT-Realtime to create a 24/7 multilingual retail agent for Yamada Denki. In just two weeks, 30,000 shoppers interacted with the agent, and 92% of survey responses were positive.
Researchers introduced GoGoTB, an agentic AI framework that uses large language models to automate functional verification of integrated circuits, detecting interface mismatches and tying coverage data to specification requirements to reduce costly silicon respins.
The European Union has announced new rules requiring mandatory labels on AI-generated content that appears authentic, including images, videos, audio, and text, to combat misinformation and enhance digital transparency.
Researchers introduce CaM-Wolf, the first AI agent for social deduction games that integrates both text and visual perception and generation, enabling more human-like social interaction in games like Werewolf.
Researchers introduced BridgeAlign, a new preference-alignment pipeline designed specifically for humanities and social sciences (HSS). Unlike existing methods that focus on objective correctness, BridgeAlign handles nuanced, subjective judgments, making it a first-of-its-kind approach for broad HSS disciplines.
The Bioinformatics Open Source Conference (BOSC) experimented with AI to pre-review abstracts, reducing the workload on human reviewers. This approach could help other conferences manage the surge in submissions enabled by generative AI.
Researchers introduced B1ade, a lightweight AI system that combines a small embedding model and a compact language model. It achieves top performance in retrieval tasks without needing massive training data or expensive hardware.
Researchers introduced AI SciBrief, a system that uses multi-stage prompt chaining to generate high-quality scholarly digests. This method outperforms traditional single-shot prompting in accuracy and reliability.
A University of Cambridge study found that seven large language models (LLMs) consistently failed to match the emotional perception of 3,011 human participants when evaluating sympathy in news headlines, with significant gaps across sociodemographic groups.
Nvidia CEO Jensen Huang launched an initiative championing open-weight AI models, prompting a sharp response from Anthropic's Dario Amodei as top frontier labs join forces to push for federal review processes in Washington.
Researchers argue that AI evaluation scores should be treated as temporary knowledge claims, not absolute truths. They warn that combining different evaluation methods can create an illusion of higher accuracy than actually exists.
Researchers introduced AHA-Memes, the first large-scale Arabic hateful meme benchmark with fine-grained, multi-label annotations. This dataset enables more precise detection of hate speech in Arabic memes, addressing a critical gap in online safety for Arabic-speaking communities.
Google's AI Mode in Search helps users plan and book offline activities like concerts, travel, and dining by consolidating information and providing step-by-step guidance directly in search results.
xAI is suing Minnesota Attorney General Keith Ellison to block a new law banning 'nudification' apps, arguing it violates the First Amendment. The company says the law's vague language and severe penalties could force it to restrict Grok Imagine's image-editing features.
A new arXiv study finds that AI models trained with reinforcement learning (RL) develop superior internal representations for mathematical reasoning compared to supervised fine-tuning (SFT) models, explaining their better performance on math problems.
A new ArXiv paper identifies a fundamental epistemic problem in AI evaluation: benchmark inferences do not compose. Even when each link in a chain of reasoning is warranted, the chain itself may not hold, meaning strong benchmark performance does not guarantee real-world reliability.
Researchers introduced TraceCoder, an AI coding tool that records every step of code generation. It makes AI-generated code fully transparent and auditable, addressing key limitations of current systems.
Developer Wladimir Avila distributed a 56-million-parameter AI model across three ESP32-S3 microcontrollers using the ESP-NOW wireless protocol, demonstrating low-cost distributed AI on hobbyist hardware.
OpenAI has reduced the cost of its GPT-5.6 model by 20% for enterprise Luna and Terra services, aiming to help businesses deploy AI workflows at scale more affordably.
British AI neocloud company Nscale has acquired Anyscale, a startup whose software helps companies scale AI workloads across data centers and servers. The deal lets Nscale control more of the technology stack needed to power AI systems, from hardware to workload orchestration.
Researchers introduced evidence-ledger adjudication, a workflow that pairs AI-generated claims with evidence packets, assigns support relations, and routes unsupported or contradicted claims back to the author for review. The system was tested on a 2,335-row blind benchmark built from AVeriTeC, CLIMATE-FEVER, and SciFact.
Microsoft introduced its own AI models, tools, and a competitor to Mythos, positioning itself as a direct competitor to OpenAI and Anthropic. The company told Wall Street it plans to drive growth through these new technologies.