Brainberg
How to evaluate or test the product powered by large language models
AI Integration & ApplicationMeetupFreeOnline

How to evaluate or test the product powered by large language models

Wed 11 Nov ยท 00:00
50โ€“200 attendees

About this event

This meetup is moved to Nov 10th.

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Speaker: Narendra Singh Panwar | LinkedIn

Topic: How to Evaluate or Test Products Powered by Large Language Models

Agenda:
๐Ÿ•› 4:00โ€“4:05 PM PDT โ€” Welcome
๐Ÿ•› 4:05โ€“4:55 PM PDT โ€” Narendra Singh Panwar | LinkedIn - How to Evaluate or Test Products Powered by Large Language Models
๐Ÿ•› 4:55โ€“5:00 PM PDT โ€” Q&A & Closing

Summary :
LLMs and AI agents are powering the next generation of products. While the speed of development has increased significantly, evaluating the end-to-end quality of these products remains a challenge.

In this session, Narendra Singh Panwar will share practical learnings and techniques from testing consumer-facing products powered by LLMs and AI agents. The discussion will explore how traditional QA practices need to evolve when testing systems that are non-deterministic and capable of making decisions, generating responses, and completing actions.

The session will cover how teams can evaluate the non-deterministic nature of AI systems, verify factual accuracy, and determine where AI-assisted evaluation can help. Narendra will also discuss the use of LLM-as-a-Judge and where human evaluation is still necessary to assess the quality of AI-powered experiences.

The discussion will also look at AI-powered test automation and continuous customer experience monitoring as ways to support quality evaluation as AI products evolve.

Takeaways :
What attendees will learn:

  1. How to evaluate the non-deterministic behavior of LLM-powered products
  2. Approaches for fact-checking and evaluating AI-generated responses
  3. Where AI and LLM-as-a-Judge can be applied in quality evaluation
  4. Where human evaluation is still necessary
  5. How AI-powered test automation can support testing of AI products
  6. How continuous CX monitoring can help evaluate end-to-end quality
  7. How traditional QA practices can evolve for products powered by LLMs and AI agents

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