The study evaluates OpenAI’s o1‑preview large language model on a wide range of complex reasoning tasks across domains such as computer science, mathematics, natural sciences, medicine, linguistics, and social sciences. It reports high success rates, including 83.3% on competitive programming, 100% on high‑school math reasoning, and superior performance in radiology reporting, chip design, anthropology, geology, quantitative investing, and social media analysis. While the model excels at intricate reasoning and knowledge integration, it still shows occasional errors on simpler problems and struggles with some highly specialized concepts.
arXiv:2607. 15686v1 Announce Type: new Abstract: We present S1-Omni, a unified multimodal reasoning model for scientific understanding, prediction, and generation.
OpenAI introduces FrontierScience, a benchmark testing AI reasoning in physics, chemistry, and biology to measure progress toward real scientific research.
arXiv:2509. 23426v3 Announce Type: replace Abstract: AI scientists are emerging computational systems that serve as collaborative partners in discovery.
OpenAI reflects on ten years of progress, from early research breakthroughs to widely used AI systems that reshaped what’s possible. We share lessons from the past decade and why we remain optimistic about building AGI that benefits all of humanity.
OpenAI introduces GPT‑6 Astra, its most capable model for business. The new model boasts advanced reasoning, computer use, and improved writing and design judgment. It is positioned as the next generation of intelligence for work.
arXiv:2603. 19005v2 Announce Type: replace-cross Abstract: Data science plays a critical role in transforming complex data into actionable insights across numerous domains.
arXiv:2608. 08883v1 Announce Type: new Abstract: Recent advances in retrieval-augmented generation (RAG) and large language models (LLMs) enable researchers to integrate AI into scientific workflows.
OpenAI has been named an Emerging Leader in Gartner’s 2025 Innovation Guide for Generative AI Model Providers. The recognition reflects our enterprise momentum, with over 1 million companies building with ChatGPT.
Endex builds the future of financial analysis, powered by OpenAI’s reasoning models.
The paper introduces UniK, a universal knowledge perception platform designed to serve both digital AI—such as chatbots and agent workflows—and physical AI, which controls robots and autonomous systems. UniK handles the entire knowledge lifecycle—ingestion, enrichment, indexing, retrieval, and continuous evaluation—across diverse modalities including text, video, molecular data, and sensor telemetry, without task‑specific fine‑tuning. In five digital AI domains, UniK paired with a 70‑billion‑parameter model matches or surpasses larger proprietary LLMs, achieving high retrieval‑augmented generation accuracy on government data, medical QA, and chemistry tasks, and it also addresses similar data challenges in physical AI world‑model training.
The paper introduces Open Tabular Insight Extraction (OpenTI), a unified framework aimed at democratizing access to insights from large table corpora. It highlights how current research is fragmented across domains like table QA, text‑to‑SQL, and data analysis agents, and shows that existing systems and benchmarks fall short of covering the full end‑to‑end scope of OpenTI. The authors propose a consolidated terminology, conduct a systematic review, and outline a research agenda for developing comprehensive OpenTI systems, evaluation methods, and interaction paradigms.
arXiv:2505. 14107v5 Announce Type: replace-cross Abstract: The emergence of groundbreaking large language models capable of performing complex reasoning tasks holds significant promise for addressing various scientific challenges, including those arising in complex clinical scenarios.