Why Halliburton's SVP of Technology Says Don't Start With AI | Sriram Srinivasan, Halliburton
Summary
Halliburton SVP of Global Technology Sriram Srinivasan advises executives to prioritize business use cases, data readiness, and domain context before adopting AI. He explains how Databricks tools help Halliburton manage massive amounts of operational data and previews the future of AI as a collaborative coworker and physical operator.
Summary generated by brickster.ai from the video transcript.
More from Databricks
TutorialsTutorial: Genie for Data Engineers, Data Scientists, and Everybody Else
This tutorial demonstrates how to use Databricks Genie to build a live web app and data pipeline from a 700-million-row IoT dataset. The process covers getting the data from the Databricks Marketplace, running exploratory data analysis, building pipelines and jobs with Genie Code, querying data on mobile, and receiving shared data locally.
TutorialsHow to Build Customer 360 Profiles with AI | CustomerLake Profile Agents Demo
CustomerLake profile agents uses AI to ingest new data sources and define identity resolution matching rules. The system normalizes data and launches runs to create unified customer profiles.
ReleasesIntroducing Agent Memory on Databricks
Databricks announced Agent Memory, a new tool for Agent Bricks that allows AI agents to store and recall past conversations and user data using lakebase architecture. By connecting session stores and memory stores through automated memory pipelines, agents can retain context across multiple sessions to improve task performance and reduce token usage.
TutorialsBuilding Production-Ready AI Agents on Databricks | Agent Bricks Demo
Building production ready AI agents on Databricks involves a six step workflow spanning vector search indexing, agent as code, MLflow tracing, Unity Catalog registration, evaluation, and deployment with review apps. MLflow tracing and evaluation metrics help monitor agent execution steps, relevance, safety, and topic adherence in real time.
NewsShorts extracted from Parallel Coding Agents with Lakebase
Coding agents can use git worktrees and branch databases to work safely in parallel. This allows multiple agents to test features against isolated database branches without interfering with production or each other.
NewsComo a Arezzo&Co centralizou dados com a Databricks
Arezzo and Co utilized Databricks to centralize its data architecture, breaking down silos and improving data consistency across departments. This integration accelerated reporting times by over fifty percent, improved full-price sales, and provided actionable insights that drove strategic business growth.