arXiv 2511.010192025-11-06cs.CLcs.AIcs.CEcs.LGphysics.ao-ph

OceanAI：一个用于准确、透明、近实时海洋学洞察的对话平台

OceanAI: A Conversational Platform for Accurate, Transparent, Near-Real-Time Oceanographic Insights

North Carolina State University（北卡罗来纳州立大学）；NOAA（国家海洋和大气管理局）

Bowen Chen, Jayesh Gajbhar, Gregory Dusek, Rob Redmon, Patrick Hogan, Paul Liu, DelWayne Bohnenstiehl, Dongkuan Xu, Ruoying He

备注：: A related presentation will be given at the AGU(American Geophysical Union) and AMS(American Meteorological Society) Annual Meetings

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AI总结：

OceanAI将开源大语言模型与NOAA实时海洋数据流结合，通过实时API调用生成可验证、可复现的海洋学回答与可视化，在盲比中优于现有AI聊天产品，为海洋决策支持提供了透明可扩展的框架。

摘要：

人工智能正在变革科学领域，但通用对话式AI系统经常产生未经证实的“幻觉”，损害科学严谨性。我们提出了OceanAI，这是一个对话平台，它将开源大语言模型（LLMs）的自然语言流畅性与对美国国家海洋和大气管理局（NOAA）托管的权威海洋学数据流的实时、参数化访问相结合。每个查询，例如“2024年波士顿港的最高水位是多少？”，都会触发实时API调用，识别、解析并将相关数据集合成为可复现的自然语言响应和数据可视化。在与三种广泛使用的AI聊天界面产品的盲比中，只有OceanAI生成了带有原始数据引用的NOAA来源数值；其他产品要么拒绝回答，要么提供了无依据的结果。OceanAI为可扩展性而设计，连接多个NOAA数据产品和变量，支持海洋灾害预报、生态系统评估和水质监测等应用。通过将输出建立在可验证的观测基础上，OceanAI提升了透明度、可复现性和可信度，为海洋领域内AI赋能的决策支持提供了一个可扩展的框架。公开演示可在 https://oceanai.ai4ocean.xyz 获取。

英文摘要：

Artificial intelligence is transforming the sciences, yet general conversational AI systems often generate unverified "hallucinations" undermining scientific rigor. We present OceanAI, a conversational platform that integrates the natural-language fluency of open-source large language models (LLMs) with real-time, parameterized access to authoritative oceanographic data streams hosted by the National Oceanic and Atmospheric Administration (NOAA). Each query such as "What was Boston Harbor's highest water level in 2024?" triggers real-time API calls that identify, parse, and synthesize relevant datasets into reproducible natural-language responses and data visualizations. In a blind comparison with three widely used AI chat-interface products, only OceanAI produced NOAA-sourced values with original data references; others either declined to answer or provided unsupported results. Designed for extensibility, OceanAI connects to multiple NOAA data products and variables, supporting applications in marine hazard forecasting, ecosystem assessment, and water-quality monitoring. By grounding outputs and verifiable observations, OceanAI advances transparency, reproducibility, and trust, offering a scalable framework for AI-enabled decision support within the oceans. A public demonstration is available at https://oceanai.ai4ocean.xyz.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。