Self-Correcting ML + Multimodal Search with Elastic

Join the Elastic Washington, D.C. User Group for an engaging meetup! 🎉

📅 Date & Time

Wednesday, September 16th
5:30 PM - 7:30 PM EDT

📍 Location

Elastic Arlington Office
4100 Fairfax Drive, Ste 500, Arlington, VA 22203

🚗 Parking

• The building’s parking garage is operated by Colonial Parking, located off N. Randolph Street.
• Book a spot on SpotHero
• A Metro Station is conveniently located across the street.

🗓️ Agenda

• 5:30 PM: Doors open; say hi, grab a seat, and enjoy some food.
• 6:00 PM: Dashboards to Decisions: A Self-Correcting ML Loop with Elastic Observability - Kritika Berry
• 6:40 PM: Building Multimodal Search with Elastic and Jina - Josh Phifer, Principal Solutions Architect at Elastic
• 7:20 - 7:30 PM: Networking & refreshments

💡 Talk Abstracts

• Dashboards to Decisions: A Self-Correcting ML Loop with Elastic Observability
  Kritika Berry (Software Engineer)
  Most ML pipelines face a drop in accuracy or a spike in latency as they train, often going unnoticed until someone downstream complains. This talk will demonstrate how to integrate Elastic Observability into your ML workflow, allowing the pipeline to monitor itself. Logs, metrics, and traces will feed back into the system to catch drift and errors, triggering corrective actions automatically.

• Building Multimodal Search with Elastic and Jina
  Josh Phifer, Principal Solutions Architect at Elastic
  This session will showcase two demos using Elastic and Jina for multimodal search. The first demo features an artwork search experience where users can search using text, images, or both. The second demo applies similar concepts to video, allowing users to find specific scenes or topics with simple questions. We’ll also discuss the implementation details and trade-offs behind each approach.