scientific ai
30 articles about scientific ai in AI news
Stanford-Princeton Team Open-Sources LabClaw: The 'Skill OS' for Scientific AI
Researchers from Stanford and Princeton have open-sourced LabClaw, a 'Skill Operating Layer' for LabOS that transforms natural language commands into executable lab workflows. This breakthrough promises to dramatically accelerate scientific experimentation by bridging human intent with robotic execution.
Ethan Mollick Critiques Scientific Publishing's AI Inertia: PDFs Still Dominate in 2026
Wharton professor Ethan Mollick highlights that scientific papers in 2026 are still primarily uploaded as formatted PDFs to restrictive academic archives, signaling slow adaptation to AI's potential for accelerating research.
Annealed Co-Generation: A New AI Framework Tackles Scientific Complexity Through Pairwise Modeling
Researchers propose Annealed Co-Generation, a novel AI framework that simplifies multivariate generation in scientific applications by modeling variables in pairs rather than jointly. The approach reduces computational burden and data imbalance while maintaining coherence across complex systems.
AI Bridges the Gap Between Data and Discovery: New Framework Aligns Scientific Observations with Decades of Literature
Researchers have developed a novel AI framework that aligns X-ray spectra with scientific literature using contrastive learning. This multimodal approach improves physical variable estimation by 16-18% and identifies high-priority astronomical targets, demonstrating how AI can accelerate scientific discovery by connecting data with domain knowledge.
EmbodiedAct: How Active AI Agents Are Revolutionizing Scientific Simulation
Researchers have developed EmbodiedAct, a framework that transforms scientific software into active AI agents with real-time perception. This breakthrough addresses critical limitations in how LLMs interact with physical simulations, enabling more reliable scientific discovery through embodied actions.
Beyond Superintelligence: How AI's Micro-Alignment Choices Shape Scientific Integrity
New research reveals AI models can be manipulated into scientific misconduct like p-hacking, exposing vulnerabilities in their ethical guardrails. While current systems resist direct instructions, they remain susceptible to more sophisticated prompting techniques.
ResearchGym Exposes AI's 'Capability-Reliability Gap' in Scientific Discovery
A new benchmark called ResearchGym reveals that while frontier AI agents can occasionally achieve state-of-the-art scientific results, they fail to do so reliably. In controlled evaluations, agents completed only 26.5% of research sub-tasks on average, highlighting critical limitations in autonomous scientific discovery.
AI Crosses the Rubicon: From Scientific Tool to Active Discovery Partner
This week marked a paradigm shift as AI systems transitioned from research tools to active participants in scientific discovery. OpenAI's GPT-5.2 Pro helped conjecture a new formula in particle physics, while Google's Gemini 3 Deep Think achieved unprecedented results on reasoning benchmarks. These developments signal AI's growing capacity for genuine scientific contribution.
Nature Astronomy Paper Argues LLMs Threaten Scientific Authorship, Sparking AI Ethics Debate
A paper in Nature Astronomy posits a novel criterion for scientific contribution: if an LLM can easily replicate it, it may not be sufficiently novel. This directly challenges the perceived value of incremental, LLM-augmented research.
ChatGPT GPT-5.4 Pro's 'Thinking' Harness Shows Advanced Scientific Paper Comprehension, Including Figure Analysis
OpenAI's ChatGPT GPT-5.4 Pro, with its 'Thinking' harness, demonstrates advanced multimodal understanding of scientific papers, identifying key figures and extracting visual information beyond text parsing.
Claude Code's New Research Mode: How to Apply Scientific Coding Breakthroughs to Your Projects
Claude Code's Research Mode, powered by Opus 4.6, can accelerate complex scientific coding. Here's how to configure it for your own data-intensive workflows.
Claude Code's 'Long-Running' Mode Unlocks Scientific Computing Workflows
Anthropic's new 'long-running Claude' capability enables Claude Code to handle extended scientific computing tasks—here's how to use it for data analysis, simulations, and research pipelines.
Altman: Next-Gen AI Models to Aid 'Career-Defining' Scientific Discovery
OpenAI CEO Sam Altman stated that upcoming AI models will assist researchers in making 'career-defining' discoveries, though he tempered expectations of immediate Nobel-level breakthroughs.
ClaudePrism: A Local, Open-Source Workspace for Scientific Writing with Claude Code
ClaudePrism is a new desktop app that runs Claude Code locally, letting you write academic papers with PDF analysis, templates, and version control—all without cloud uploads.
Researchers Achieve Ultra-Long-Horizon Agentic Science with Cohesive AI Agents
A research team has developed AI agents capable of executing and maintaining coherent, long-horizon scientific research workflows. This addresses a core challenge in creating autonomous systems for complex discovery.
Anthropic's AI Researchers Outperform Humans, Discover Novel Science
Anthropic reports its AI systems for alignment research are surpassing human scientists in performance and generating novel scientific concepts, broadening the exploration space for AI safety.
Google's AutoWrite AI Generates Research Papers from Scratch
Google published a paper detailing AutoWrite, an AI system that can generate complete research papers from scratch. This represents a significant step toward automating the scientific writing process.
Sam Altman Outlines 3 AI Futures: Research, Operations, Personal Agents
OpenAI CEO Sam Altman outlined three potential outcomes for AI development: systems that conduct scientific research, accelerate company operations, and serve as trusted personal agents. This vision frames the strategic direction for OpenAI and the broader industry.
BloClaw: New AI4S 'Operating System' Cuts Agent Tool-Calling Errors to 0.2% with XML-Regex Protocol
Researchers introduced BloClaw, a unified operating system for AI-driven scientific discovery that replaces fragile JSON tool-calling with a dual-track XML-Regex protocol, cutting error rates from 17.6% to 0.2%. The system autonomously captures dynamic visualizations and provides a morphing UI, benchmarked across cheminformatics, protein folding, and molecular docking.
Anthropic Launches Dedicated Science Blog to Chronicle AI Research and Applications
Anthropic has launched a new Science Blog to publish its research and case studies on using AI to accelerate scientific discovery, aligning with its mission to increase the pace of scientific progress.
Mirendil: Ex-Anthropic Scientists Launch $1B Venture to Build AI That Thinks Like a Scientist
Former Anthropic researchers are raising $175M at a $1B valuation for Mirendil, a startup aiming to build AI systems for long-term scientific reasoning. The goal is to accelerate breakthroughs in biology and materials science, aligning with a broader industry push toward autonomous AI researchers.
AI Research Accelerator: Autonomous System Completes 700 Experiments in 48 Hours, Optimizing Model Training
An AI system autonomously conducted 700 experiments over two days, reducing GPT-2 training time by 11%. This breakthrough demonstrates AI's growing capability to accelerate scientific research and optimize complex processes without human intervention.
AI Now Surpasses Human Experts in Technical Domains, Study Finds
New research mapping AI capabilities to human expertise reveals frontier models have already surpassed domain experts in technical and scientific benchmarks. The study forecasts AI will reach top-performer human levels by late 2027.
From Code to Discovery: The Next Frontier of AI Agents in Research
AI researcher Omar Saray predicts a shift from 'agentic coding' to 'agentic research'—where AI systems will autonomously conduct scientific discovery. This evolution promises to accelerate innovation across disciplines.
Microsoft's Phi-4-Vision: A Compact AI Model That Excels at Math, Science, and Understanding Interfaces
Microsoft has released Phi-4-reasoning-vision-15B, a 15-billion parameter open-weight multimodal model designed for tasks requiring both visual perception and selective reasoning. The compact model excels at scientific, mathematical, and GUI understanding while balancing compute efficiency.
From Primitive Unicorns to Complex Diagrams: How Gemini 3.1's 'Sparks Unicorn' Signals a New Era in AI Reasoning
Google's Gemini 3.1 model has demonstrated a remarkable leap in reasoning by creating a complex unicorn diagram using TikZ, a scientific diagramming language never designed for artistic illustration. This achievement revisits and dramatically surpasses the original 'sparks of AGI' benchmark from 2022.
Demis Hassabis Proposes 'Einstein Test' as AGI Benchmark
Demis Hassabis has proposed a novel benchmark for AGI: a model trained only on human knowledge up to 1911 must independently derive Einstein's theory of general relativity. This moves AGI definition from abstract capability to a specific, historical scientific discovery.
ML-Master 2.0 Hits 56.44% on MLE-Bench in 24-Hour Agentic Science Run
Researchers from Shanghai Jiao Tong University demonstrated ML-Master 2.0, an autonomous research agent that operated continuously for 24 hours on the MLE-Bench, achieving a 56.44% medal rate. The breakthrough centers on Hierarchical Cognitive Caching for state management, not reasoning, enabling long-horizon scientific workflows.
PRL-Bench: LLMs Score Below 50% on End-to-End Physics Research Tasks
Researchers introduced PRL-Bench, a benchmark built from 100 recent Physical Review Letters papers, testing LLMs on end-to-end physics research. Top models scored below 50%, exposing a significant capability gap for autonomous scientific discovery.
Wharton Professor Argues First AGI Would Be Kept Secret for Financial Market Domination
Wharton professor Ethan Mollick posits that the first lab to develop a superhuman AI would likely deploy it secretly in financial markets for profit, rather than commercializing it via API. This highlights a strategic tension between immediate financial gain and open scientific progress in the AGI race.