How to Build LLMs on Your Company’s Data While on a Budget
Description
Large Language Models (LLMs) are taking AI mainstream across companies and individuals. However, public LLMs are trained on general-purpose data. They do not include your own corporate data and they are black boxes on how they are trained. Because terminology is different for healthcare, financial, retail, digital-native and other industries, companies today are looking for industry-specific LLMs to better understand the terminology, context and knowledge that better suits their needs. In contrast to closed LLMs, open source-based models can be used for commercial usage or customized to suit an enterprise’s needs on their own data. Learn how Databricks makes it easy for you to build, tune and use custom models, including a deep dive into Dolly, the first open source, instruction-following LLM, fine-tuned on a human-generated instruction dataset licensed for research and commercial use. In this session, you will: - See a real-life demo of creating your own LLMs specific to your industry - Learn how to securely train on your own documents if needed - Learn how Databricks makes it quick, scalable and inexpensive - Deep dive into Dolly and its applications Talk by: Sean Owen Connec…
Description from YouTube. Full content on the video page.
Topics
More from Databricks
NewsHow AI and Data Keep 2.3 Million Lawns Healthy | TruGreen & Databricks
TruGreen uses Databricks Genie and Lakehouse to manage 2.3 million lawns with AI that optimizes service timing and predicts customer churn using weather, soil, and service data. The system enables non-technical branch managers to take daily actions through customized reports without requiring data expertise.
NewsHow FOX Sports Uses AI to Power Search
Fox Sports rebuilt their search system on Databricks to handle rapidly changing sports information by continuously streaming player, team, and content data into the index while computing real-time trends. The system uses semantic vector search with time-weighted ranking to surface fresh content higher, doubling the rate at which users find what they're looking for.
NewsHow AI Helps Match Doctors With Communities in Need | Databricks for Good
Databricks provides pro bono services and compute discounts to help nonprofits stay lean through its Databricks for Good program. The video demonstrates the Virtue Foundation agent, which uses Genie and interactive hex maps to identify underserved populations and medical facility distribution in Kenya.
NewsOmnigent: Open-Source Meta-Harness for AI Agents | Matei Zaharia
Omnigen is an open-source meta-harness developed by Databricks that acts as an orchestration and control layer to wrap, manage, and combine multiple AI coding agents. The platform introduces contextual security policies, cost controls, multi-agent task routing, and sandbox integrations to enable collaborative workflows and centralized governance.
NewsBuilding Agents on Databricks with Custom Apps and Omnigent
This video demonstrates how to build, update, and govern custom AI agents on Databricks using Agent Bricks, Databricks Apps, and Omnigent. The tutorial shows how to integrate Model Context Protocol servers, track execution with MLflow traces, schedule automated agent tasks, and manage security policies through Unity AI Gateway.
NewsGoverning AI Strategy with Unity AI Gateway
The Unity AI gateway provides centralized monitoring, cost tracking, and governance for enterprise AI models, MCP servers, and coding agents. Administrators can use the platform to set budget limits, configure external providers, and enforce input policies that block personally identifiable information.
