MarkTechPost@AI 2024年12月05日
Allen Institute for AI: Open-Source Innovations with Ethical Commitments and Contributions in 2024
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Allen Institute for AI (AI2) 在2024年持续推动人工智能研究和应用,发布了一系列开源项目,包括大型语言模型OLMo、多模态模型Molmo和科研辅助系统OpenScholar等。这些项目旨在促进人工智能领域的协作发展,并强调负责任的人工智能开发。AI2还积极参与伦理规范和开放研究资源的构建,例如Impact License Project和NAIRR Pilot,致力于构建安全可靠的AI系统,推动人工智能技术的良性发展。

💡AI2于2024年2月发布了完全开源的大型语言模型OLMo,其预训练数据、训练代码和模型权重均公开,旨在促进LLM领域的研究和发展,OLMo基于包含3万亿个token的Dolma数据集训练,提供500多个检查点和评估结果。

🖼️AI2于2024年9月推出了多模态AI模型家族Molmo,旗舰模型Molmo-72B拥有720亿个参数,性能与GPT-4o等闭源模型相当,它能够处理文本和图像数据,并支持图像分析、对象识别等功能。

📚AI2与华盛顿大学合作,于2024年11月发布了OpenScholar,这是一个旨在帮助研究人员检索和理解科学文献的AI系统,它利用先进的检索系统和微调的语言模型,从4500万篇开放获取的学术论文中提取信息,并提供可靠的答案。

🤝AI2致力于AI的伦理发展,推出了Impact License Project,旨在促进AI开发的透明度、问责制和协作,并将技术进步与社会福祉相结合,并参与NAIRR Pilot项目,提供开放的AI数据、模型和评估工具。

🔬AI2旗舰工具Semantic Scholar不断发展,整合自然语言处理技术,增强科学文献的可访问性和可用性,截至2022年,该平台包含超过2亿篇出版物,提供自动摘要和引用上下文等功能。

Allen Institute for AI (AI2) was founded in 2014 and has consistently advanced artificial intelligence research and applications. OLMo is a large language model (LLM) introduced in February 2024. Unlike proprietary models, OLMo is fully open-source, with its pre-training data, training code, and model weights freely available to the public. This transparency is designed to foster collaborative advancements in the field of LLMs, allowing researchers to study and refine these models more effectively. Built on AI2’s Dolma dataset comprising three trillion tokens, OLMo’s training framework offers over 500 checkpoints and evaluations captured at every 1,000 training steps. This initiative aims to support the development of safe and trustworthy AI systems by providing a robust and accessible platform for experimentation.

In September 2024, AI2 introduced Molmo, a family of multimodal AI models capable of processing text and visual data. The flagship model, Molmo-72B, contains 72 billion parameters and rivals the performance of proprietary models like OpenAI’s GPT-4o. Molmo achieved these capabilities using a curated dataset of approximately 600,000 images, emphasizing quality over quantity in data preparation. This model can analyze and describe images and supports advanced functionalities like identifying specific items within images, making it a valuable tool for augmented reality and AI-assisted visual analysis.

In November 2024, AI2, in collaboration with the University of Washington, launched OpenScholar, an AI system designed to aid researchers in navigating the rapidly expanding body of scientific literature. OpenScholar integrates advanced retrieval systems with fine-tuned language models to provide comprehensive, citation-backed answers to research queries. It draws from a database of over 45 million open-access academic papers, ensuring accurate and well-sourced responses. By addressing challenges such as fabricated references and improving output quality through iterative self-feedback mechanisms, OpenScholar represents a significant leap forward in AI-assisted research.

AI2 has also demonstrated its commitment to the ethical development of AI through initiatives like the Impact License Project (ImpACT), introduced in August 2023. These licenses promote transparency, accountability, and collaboration in AI development, aligning technological advancements with societal well-being. Also, AI2’s involvement in the National Artificial Intelligence Research Resource (NAIRR) Pilot reinforces its dedication to open, collaborative AI research by offering accessible ecosystems of data, models, and evaluation tools.

The institute’s flagship tool, Semantic Scholar, continues to evolve, integrating natural language processing techniques to enhance the accessibility and usability of scientific literature. As of 2022, Semantic Scholar includes over 200 million publications, offering features like automated summaries and citation context insights. These enhancements empower researchers to synthesize information efficiently, streamlining the research process.

AI2 remains at the forefront of AI research through these initiatives, prioritizing openness, collaboration, and ethical practices. By advancing tools like OLMo, Molmo, OpenScholar, and Semantic Scholar and promoting responsible AI usage, the institute continues to contribute to the AI community and society. Its efforts underline the importance of transparent, open-source development in driving innovation and addressing the challenges posed by the rapidly evolving AI landscape.

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Allen Institute for AI 开源AI 大型语言模型 多模态AI 科研辅助
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