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Keynote: Teaching LLMs New Knowledge

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Lamini demonstrates concrete ways to inject new domain knowledge into open LLMs: fine-tuning and pretraining combined with prompting and RAG, plus tooling that enforces guaranteed JSON outputs for reliable production parsing. The stack claims to ingest and teach from millions of training points without manual data transformation and offers scaling support—announcing hundreds of compute nodes becoming available—to run adaptation workflows. Emphasis is on measurable behavior change, corrected hallucinations, and shipping models that actually understand business-specific facts.

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