Large Language Models

Industrial insight and articles from Winder.AI, focusing on the topic Large Language Models

Enterprise AI Assistants: Combatting Fragmentation

Published
Author
Dr. Phil Winder
CEO

Enterprise AI Assistants unify disparate data sources, providing real-time insights and access control. Building domain-specific assistants and orchestrating them (hierarchical or federated) offers scalability, specialized features, and better performance than single-vendor solutions. Ultimately, organizations need a tailored approach that consolidates knowledge, fosters collaboration, and addresses evolving AI integration challenges.

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Large Language Model Fine-Tuning via Context Stacking

Published
Author

Fine-tuning Large Language Models (LLMs) can be a resource-intensive and time-consuming process. Businesses often need large datasets and significant computational power to adapt models to their unique requirements. Attentio, co-founded by Julian and Lukas, is changing this landscape with an innovative technique called context stacking. In this video, we explore how this method works, why it is so efficient, and what it means for enterprises looking to embed custom knowledge directly into their AI models.

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