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
ReleasesDatabricks launches across the Data + AI stack in 90 seconds
Databricks announced LTAP to unify lakebased and lakehouse data, eliminating ETL and enabling a single copy of data for analytical and operational needs. They also introduced Unity AI Gateway for governance, Genie Ontology for enterprise knowledge graphs, and open-sourced Omniant for managing multiple coding agents.
ReleasesIntroducing Omnigent: The Ultimate Meta-Harness for AI Agents
Omnigent is a new open-source meta-harness for AI agents that provides a unified interface for composition, control, and collaboration across multiple models and agent workflows. It enables stateful, data-centric policies for guardrails and allows real-time sharing and steering of live agent sessions with teammates.
NewsHow DEFRA and Natural England Accelerate Peatland Restoration with AI and Databricks
DEFRA and Natural England utilize AI and Databricks to accelerate peatland restoration by automating the mapping of peatland features and peat dams across England. This technology significantly reduces the time required for mapping, enabling faster identification and restoration of these crucial carbon-storing habitats.
NewsAI Stack Explained in 3 Layers (LLM, Agent Harness, Omnigent)
The AI stack now includes a third layer, the meta harness, which sits above individual agent harnesses. This meta harness, exemplified by Databricks' open-sourced Omnigent, allows for routing queries to appropriate agents and orchestrating tasks across multiple agents, enabling seamless interaction and context sharing between them.
NewsWhat’s coming next to Free Edition
Databricks announces the availability of Genie, GPUs, Agent Hooks, Lakehouse, and Lake Flow Designer on its Free Edition. This update provides virtually all of Databricks' production platform features for free, enabling users to learn and build data and AI projects.
