6th December 2023
05:00 PM - 07:00 PM MST
27th August 2025
06:00 PM - 08:00 PM PST
1631 North First Street, Suite 200, San Jose, CA 95112
“As AI systems—especially those powered by large language models (LLMs)—become more integrated into enterprise applications, evaluating their quality goes far beyond just measuring accuracy. Traditional testing metrics fall short in capturing the nuanced behavior and real-world impact of these models.
This session explores three critical pillars for modern AI system evaluation:
Robustness: Refers to how consistently an AI system performs under varying, unexpected, or adversarial inputs.
• Focus areas:
• Edge case testing and stress testing
• Resistance to prompt injection (for LLMs)
• Detecting brittle behavior in slightly altered inputs
Fairness: Ensures the model does not produce biased, discriminatory, or unethical outputs.
• Focus areas:
• Identifying biased training data or outputs
• Using fairness testing tools and metrics (e.g., demographic parity, equal opportunity)
• Domain-specific risk assessment (e.g., healthcare, finance)
Explainability: Helps stakeholders understand why the model produced a certain output.
• Focus areas:
• Model interpretability techniques (e.g., SHAP, LIME)
• Visualizing token importance in LLM outputs
• Generating human-readable explanations for decisions”
A practical QA framework for testing robustness, fairness, and explainability
Tools and techniques testers can use without deep ML knowledge
Why traditional QA approaches need to evolve for AI-centric applications
This topic aims to empower QA professionals to not just test but trust AI systems by adding ethical and safety layers to the evaluation process.
Radhika Naik is a Quality Engineering Leader at Apexon, with 16+ years of experience driving enterprise QA transformations and scaling automation across global teams. She specializes in continuous testing, quality strategy, and embedding QE into DevOps pipelines. Radhika has led successful quality initiatives in fintech, health tech, and SaaS, delivering faster release cycles without compromising on product stability.
Radhika is passionate about creating inclusive, collaborative QE teams that embrace innovation, tooling, and process excellence. Her leadership approach is rooted in coaching, metrics-driven decision-making, and enabling teams to own quality from day one.
RAG, or Retrieval-Augmented Generation, is one of the most widely utilized techniques in the AI landscape, addressing a variety of use cases ranging from natural language processing to knowledge retrieval. In this talk, we will delve into the fundamentals of RAG, providing a comprehensive understanding of how it works and its practical applications. Attendees will learn about the basic implementation of RAG in different scenarios, which can significantly enhance the performance of AI systems by combining the strengths of retrieval-based and generative models. Additionally, we will cover the basics of embedding techniques, which are crucial for transforming data into a format suitable for RAG, enabling more effective information retrieval and processing. By the end of the session, participants will be equipped with the foundational knowledge needed to leverage RAG in their own projects.
Understanding RAG: Gain a solid grasp of Retrieval-Augmented Generation, its components, and how it enhances AI capabilities.
Implementation Insights: Learn the basic steps to implement RAG in various applications, boosting both efficiency and accuracy.
Embedding Techniques: Discover the fundamentals of embedding, essential for optimizing data retrieval and integration within RAG frameworks.
Practical Use Cases: Explore real-world examples of RAG in action, highlighting its versatility across different industries and applications.
Kumar Abhishek, a technology leader in the field of engineering, brings more than 11 years of valuable experience in software testing to the table. He is deeply passionate about nurturing world-class engineering teams characterized by high skill levels, motivation, and exceptional efficiency. Abhishek has successfully led engineering teams in the creation of innovative software test systems that are robust, scalable, sustainable, and aligned with business objectives. He brings expertise in live and on-demand video streaming, and internet-based content delivery networks (CDNs) which enables him to contribute significantly to the success of projects and initiatives. Throughout his career, he has consistently demonstrated his ability to establish, oversee, and guide exceptionally efficient engineering teams.
Abhishek is esteemed in the industry and acted as an expert judge for both the Globee Award for Technology and the Globee Award for Disruptor in 2024. Moreover, he secured the Gold award in Titan Business Award in 2024, under the category “Management – Best Quality Management Strategy”. Abhishek’s expertise extends to speaking engagements at various software conferences, and he holds the title of IEEE Senior member.
Abhishek has a proven track record of delivering high-quality products and solutions for various networking and streaming clients, such as Hotstar, Amazon Prime, Apple, and Netflix. Abhishek is passionate about AI and its applications in NLP.
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Join the 24th software testing meetup in Bangalore by The Test Tribe happening on 15th May, 2023. Learn about Develop a reporting server for test automation reports & leveraging LowCode/NoCode.
Event Type: Event
Event Attendance Mode: OfflineEventAttendanceMode
Event Status: EventScheduled
Performer: Organization
Performer Name: The Test Tribe
Performer URL: www.thetesttribe.com
Start Date: 2025-07-31 17:53
End Date: 2025-07-31 17:53
Ticket URL: https://www.townscript.com/v2/e/the-test-tribe-24th-bangalore-meetup/booking/tickets
Entry Price: 100
Currency: INR
Availability: InStock
Availability Starts: 27/05/2023
Currently Founder & CEO at AlgoShack, Former Senior Vice President at Sutherland Global Services, Former Director & Head of Healthcare Vertical at Computer Sciences Corporation, Former Managing Director at FCG. 32 years of experience focused on product engineering, innovation & IP creation. In his 15+ years of experience in senior leadership positions, Vadeesh has been responsible for strategic planning, end-to-end operations, and P&L. He has built globally competitive leadership teams, orchestrated strategic customer engagements, and created significant value for stakeholders.
Gender: Male
Job Title: Founder & CEO
Currently Founder & CEO at AlgoShack, Former Senior Vice President at Sutherland Global Services, Former Director & Head of Healthcare Vertical at Computer Sciences Corporation, Former Managing Director at FCG. 32 years of experience focused on product engineering, innovation & IP creation. In his 15+ years of experience in senior leadership positions, Vadeesh has been responsible for strategic planning, end-to-end operations, and P&L. He has built globally competitive leadership teams, orchestrated strategic customer engagements, and created significant value for stakeholders.
Gender: Male
Job Title: Founder & CEO
