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The National Endowment for the Arts used an artificial intelligence coding agent to develop a replacement in a week for its legacy grants system.
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Read full articleThe National Endowment for the Arts used an artificial intelligence coding agent to develop a replacement in a week for its legacy grants system.
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AIs struggle to understand documents designed for humans; the DocLang working group seeks to flip that imbalance with its specification for machine-readable business documents “built from the ground up for LLM tokenizers.” The working group, founded by IBM, Nvidia, and Red Hat and hosted by the Linux Foundation’s LF AI & Data project, aims to create an open, universal, AI-native document format designed to improve how enterprises prepare, exchange, and govern document data for AI systems. ABBYY and Human Signal will also be involved in its development, and other contributors are welcome. “Enterprises today work across a fragmented landscape of document formats, including PDFs, JPEGs, and other file types built primarily for human consumption rather than AI interpretation,” the group said in its launch announcement. “This disconnect can introduce complexity, raise costs, and reduce reliability when extracting meaning from business documents,” as organizations increasingly rely on genera
LF AI & Data Foundation, a division of the Linux Foundation, launched a working group on Tuesday that will focus on the development of DocLang, a specification intended to support interoperable document processing across AI and agentic workflows. The working group, founded by premier members IBM, Nvidia and Red Hat, is tasked with the creation of an open, universal, AI-native document format designed to improve how enterprises prepare, exchange, and govern document data for AI systems. Contributors ABBYY and Human Signal will also be involved in its development. The announcement stated, “enterprises today work across a fragmented landscape of document formats, including PDFs, JPEGs, and other file types built primarily for human consumption rather than AI interpretation.” As organizations increasingly rely on generative AI and agentic systems, it said, “this disconnect can introduce complexity, raise costs, and reduce reliability when extracting meaning from business documents.” Mark C
New specification, supported by leading LF AI & Data member organizations IBM and Red Hat, as well as other organizations including ABBYY, complements the Docling open source project SAN FRANCISCO, […] The post LF AI & Data Foundation Launches DocLang Specification Working Group appeared first on AIwire.