Sponsored by: Labelbox | Unlocking Enterprise AI with Your Proprietary Data and Foundation Models
Description
We are starting to see a paradigm shift in how AI systems are built across enterprises. In 2023 and beyond, this shift is being propelled by the era of foundation models. Foundation models can be seen as the next evolution in using "pre-trained" models and transfer learning. In order to fully leverage these breakthrough models, we’ve seen a common formula for success: leading AI teams within enterprises need to be able successfully harness their own store of unstructured data and pair this with the right model in order to ship intelligent applications that deliver next-generation experiences to their customers. In this session you will learn how to incorporate foundation models into your data and machine learning workflows so that anyone can build AI faster and, in many cases, get the business outcome without needing to build AI models altogether. Which foundation AI models can be used to pre-label / enrich data and what specific data pipeline (data engine) will enable this? Real-world use cases of when to incorporate large language models and fine-tuning to improve machine learning models in real-time. Discover the power of leveraging both Labelbox and Databricks to streamline th…
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.
