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The AI Alliance, shaped in late 2023 to advance AI, has been engaged on initiatives starting from Dana, an agent-native language and runtime, to Semiont, a information base for human/agent collaboration.
Some projects rising from the alliance had been coated in a presentation September 17 by Anthony Annunziata, AI Alliance director of AI open innovation, at The AI Convention in San Francisco. With Dana (Domain-Aware Neurosymbolic Agent), formally introduced in late-June, customers get AI-powered programming with intent-driven growth, the place builders can describe what they wish to construct and the language will deal with the implementation. Dana options native help for agent workflows, reminiscence grounding, and concurrency. Designed to run regionally or within the cloud, the language is designed round domain-specific information from human experience and industry-specific workflows. It leverages large language models (LLMs) with symbolic grounding for deterministic, dependable outputs.
Semiont, in the meantime, permits people and brokers to co-create shared information. Providing an AI-native wiki, Semiont options high-accuracy context retrieval, in response to AI Alliance. Integrating through Model Context Protocol (MCP), Semiont permits regionally owned information bases, that are deployable on demand. Different initiatives from the alliance embrace Open Trusted Information for AI fashions and AI brokers, in addition to the Deep Analysis agent structure with MCP. The Open Trusted Information effort entails a metadata specification for provenance, lineage, and utility, in addition to a catalog of current open information units primarily based on a belief rating. The efforts options the curation and creation of recent information units for agentic AI use cases. The purpose of Deep Analysis is to discover the challenges of constructing production-quality brokers accessing information and instruments solely by MCP servers. The challenge additionally intends to launch a reference implementation.