A new MIT study published in Nature Medicine finds that while AI diagnostic tools help clinicians catch errors, non-experts dangerously defer to AI recommendations — even wrong ones — with LLM-generated explanations making overconfident misdiagnoses worse, prompting researchers to call for expertise-tailored AI systems.
A groundbreaking AI training method called RLSVR transforms open-ended tasks like writing and summarization into competitive multi-agent games, achieving win rates above 75% while simultaneously boosting mathematical reasoning by up to 9% — all without requiring human judges or labeled data.
OpenAI's internal AI model, Astra, achieves stunning mathematical breakthroughs by solving or advancing ten long-standing open problems across fields including geometry, group theory, and quantum complexity, with landmark results including disproving Connes's rigidity conjecture and proving new bounds for Ramsey numbers.
Lilian Weng departs Thinking Machines due to health concerns and returns to OpenAI, where she will lead a top-level research team focused on accelerating internal research, including recursive self-improvement.
OpenAI's GPT-2 small weights are outperforming custom-trained models on instruction-following tasks despite worse test loss scores, sparking investigation into whether superior data quality, overtraining, or dropout are behind the surprising gap.
Berkeley researchers unveil PixelRAG, a groundbreaking open-source AI system that searches documents as images rather than text, preserving critical visual elements like tables and charts across 8.28 million Wikipedia pages using a fine-tuned vision model and publicly available tools on Hugging Face.
OpenAI's GPT-5.6 Sol is now training its sibling model GPT-5.6 Luna by performing senior-level research tasks, marking a major step toward the company's ambitious goal of deploying a fully automated AI researcher capable of end-to-end research with minimal human oversight by March 2028.
Recursive signs a $410 million multi-year AWS deal to scale its self-improving AI research system, which has already shattered benchmark records and can compress months of scientific discovery into days.
A powerful new open-source AI framework called DataFlow is transforming model training with 100+ operators, a visual WebUI, and dramatic performance gains, boosting math reasoning scores from 37.1% to 46.7% while topping multiple benchmarks across healthcare, finance, and legal domains.
IBM Research's chief scientist warns that AI hallucinations stem from models failing to recognize the limits of their own knowledge, urging the industry to prioritize uncertainty modeling and build energy-efficient, self-aware systems focused on practical, transparent intelligence rather than chasing abstract AGI goals.