11 stories tagged Scientific Discovery
Mirendil has partnered with Google Cloud in a $100 million-plus deal to expand its infrastructure for developing self-improving AI systems. These AI models aim to accelerate scientific research and AI advancements.
Jeff Dean, former head of Google's AI division, and several other top researchers are leaving Google to start a new company focused on using AI to accelerate scientific discovery.
Researchers developed an AI system to evaluate AI-written scientific papers, testing it on four leading AI scientist frameworks. The system assesses originality, rigor, clarity, and significance, offering a new way to compare AI research quality.
Researchers introduce Prospective Hypothesis Discovery (PHD) and the HypoArena benchmark (988 cases) to evaluate how well large language models can autonomously generate grounded, discriminative, and testable hypotheses from anomalous observations and fragmented records.
Researchers are developing AI systems that could automate entire scientific research processes, from literature review to final reports. This shift could make scientific discovery faster and more accessible, though challenges remain.
Researchers developed SMCEvolve, a new AI method that makes scientific discovery faster and more reliable. It uses advanced algorithms to evolve computer programs that can solve complex problems automatically.
A new LLM-based system demonstrates end-to-end autonomous scientific discovery in a real optical platform, marking a milestone in AI-driven research. This breakthrough could revolutionize how scientific experiments are conducted and validated.
Researchers have developed an autonomous LLM agent that can independently formulate, test, and refine materials science theories. The agent successfully replicated established equations like the Hall-Petch equation and Paris law without human intervention.
Researchers introduce LABBench2, a benchmark to evaluate AI systems' ability to perform practical biology research. The new benchmark focuses on real-world capabilities beyond just knowledge and reasoning.
Researchers introduce GiantsBench, a dataset to evaluate AI's ability to anticipate scientific insights. The benchmark includes 17,000 examples across eight domains, challenging models to predict future discoveries from foundational papers.
Researchers developed a model to infer analytical solutions from visualizations of physical fields. This breakthrough could revolutionize AI-assisted scientific discovery.