Global Artificial Intelligence Virtual Conference- Webinar (Free)

Free Warm-up webinar on Oct 29th 11.00am - 11.30am PST

We are very excited to organize GAIV Conference - Dec 2025.

As we get closer to the conference, we want to invite you to participate in free Warm-Up Webinar on . October 29th (11.00am - 11.30am PST) - Wednesday

Please start registering by entering your name and email address to attend Webinar

Warmup Webinar Speakers

Jack Martin (Gen AI Program Manager, Acentra) - 11.00 AM - 11.10 AM

Edward Pollack (Data Architect, Transfinder) - 11.10 AM - 11.20 AM

Jyoti Kunal Shah (Director Engineering, ADP) - 11.20 AM - 11.30 AM

Description

Topic : Leveraging Software Design Principals for Multi-Agent AI Systems.

Jack Martin (Gen AI Program Manager, Acentra) - 11.00 AM - 11.10 AM

Abstract:

This talk examines practical strategies for leveraging AI through precise prompting, leveraging software-inspired design, and enterprise scalability. I share my path from analytics to building 4,000+ GPTs after discovering AI could automate a significant of my work. Using a few different lessons, I illustrate how explicit instructions transform outputs. I apply object-oriented principles—encapsulation, abstraction, inheritance, polymorphism—elevates prompts into modular, reusable agents. At scale, success comes from auditable prompt libraries, strict guardrails, micro-prompts, and feedback loops. Key takeaway: you can contextualize AI experiences in a very flexible manner producing more reliable, consistent, and better performing agents to support business criteria.

Who is this presentation for?

Technical and business users

Profile

Jack Martin introduces AI-first design principles for building modular, reusable, and scalable agents powered by dynamically contextualized content and data. He explores how multi-agent and orchestrated AI workflows can transform enterprise operations. Drawing on his experience building and scaling an AI program from zero to 3,500 users in nine months, and developing more than 4,000 GPTs, for Ai-GEN.co, Jack shares practical strategies for leveraging advanced prompting methodologies, and software design to deploy generative AI effectively at scale.

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Topic: Quality AI Requires Quality Data

Edward Pollack (Data Architect, Transfinder) - 11.10 AM - 11.20 AM

Abstract

As AI adoption increases rapidly and organizations clamor to take advantage of OpenAI, Copilot, and other powerful tools, many mistakes and oversights are made. These mistakes manifest themselves in security breaches, invalid results, and even offensive content. The immediate results are lost time, money, and embarrassment. What do these problems have in common? Bad data! Quality AI solutions require clean, documented, and validated data. This session dives into data quality with a strong focus on how data is maintained as it moves from transactional to analytic workloads. Some topics include: • How transactional data be maintained effectively without compromising performance. • The importance of documentation in ensuring data is used correctly. • How to validate data as it is moved, transformed, and crunched. • Security implications of handing off data to AI applications. • Ensuring that a source-of-truth exists for each data source. This is a fast-paced session that promises both helpful best practices and also some fun along the way.

Who is this presentation for?

Developers, data professionals, technical leaders, and anyone looking to ensure security, performance, and availability for AI/ML applications

Prerequisite knowledge:

Basic understanding of data/databases and AI algorithms/applications.

What you'll learn?

The role of data quality in AI, as well as best practices for maximizing data quality to improve ML/AI software applications.

Profile

Ed Pollack is a Microsoft Data Platform MVP with a passion for learning how Data Platforms work and sharing that knowledge with the community. His experiences in data architecture, database design, performance optimization, and data security are motivation for public speaking, writing, coding, and other community activities. Ed has spoken at SQL Saturday events, SQL Bits, PASS Summit, EightKB, and many other regional and international events. Ed is the organizer of the Capital Area SQL Server Group and SQL Saturday Albany, as well as a co-organizer of SQL Saturday New York City, and Future Data Driven. He has published a number of books, including "Dynamic SQL: Applications, Performance, and Security in Microsoft SQL Server", "Expert Performance Indexing in Azure SQL and SQL Server 2022", and "Analytics Optimization with Columnstore Indexes in Microsoft SQL Server: Optimizing OLAP Workloads". Ed is also an active contributor of content to SimpleTalk. In his free time, Ed enjoys video games, traveling, cooking exceptionally spicy foods, and hanging out with his amazing wife and sons.

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Topic: Adaptive Cognitive AI & Big Data Systems for Dynamic Enterprise Environments

Jyoti Kunal Shah (Director Engineering, ADP) - 11.20 AM - 11.30 AM

Abstract

Businesses are increasingly adopting cognitive artificial intelligence (AI) systems powered by Big Data to navigate today’s complex and fast-changing environments. Unlike static AI models, cognitive AI simulates human-like reasoning and learning, enabling continuous adaptation to real-time data, evolving user needs, and dynamic external conditions. The integration of Big Data enhances cognitive AI’s ability to learn from vast, diverse, and high-velocity data streams—making models more accurate, context-aware, and resilient. In this talk, I will focus on the critical factors that drive adaptability in cognitive AI, including data-driven learning mechanisms, feedback loops, and human-in-the-loop interaction. We explore cutting-edge techniques such as transformer-based models, reinforcement learning, and neuro-symbolic architectures, analyzing how each benefits from Big Data to improve scalability and responsiveness. Real-world business use cases—such as data center energy optimization, financial fraud detection, and intelligent customer support—illustrate the power of Big Data-enabled cognitive AI in delivering high-impact outcomes. Key enablers like data quality, transparency, user feedback, and system explainability are examined to understand how they shape learning trajectories and user trust. These components are vital for building adaptive enterprise AI systems that not only react to change but proactively anticipate it. I will conclude with a set of design principles for deploying enterprise-ready cognitive AI systems that continuously learn from Big Data, align with user expectations, and drive operational excellence. When supported by iterative feedback, robust data infrastructure, and ethical governance, Big Data-infused cognitive AI becomes a strategic asset, empowering organizations to make smarter, faster, and more adaptive decisions.

Who is this presentation for?

Technical and Business Audience

Prerequisite knowledge:

BigData, AI and basic technical awareness

What you'll learn?

The audience will learn how cognitive AI systems leverage Big Data to continuously adapt to dynamic business environments. They’ll understand key technologies like transformers and reinforcement learning, and how data quality, feedback, and transparency shape system performance. Real-world case studies will highlight design principles for building resilient, enterprise-ready AI.

Profile

Jyoti Shah is a seasoned technology leader with over two decades of experience in application development, digital transformation, and AI innovation. As Director of Application Development at ADP, she combines deep technical acumen with strategic vision to drive scalable enterprise solutions. With 15 years as a full stack developer, Jyoti has mastered modern technologies including GenAI, React, Angular, Java, and JavaScript. In recent years, she has led AI-powered initiatives that optimize client engagement and sales intelligence. Jyoti is also a passionate advocate for inclusion and community growth—she is one of the leaders in the IWIN (International Women's Inclusion Network) Women in Technology chapter at ADP and actively volunteers across multiple social causes. A committed mentor and hackathon judge, she is known for nurturing talent, fostering cross-functional collaboration, peer reviewing other’s work and aligning technology with business value. Jyoti’s leadership lies at the intersection of innovation, operational excellence, and impact-driven development.

Check Global Artificial Intelligence Virtual Conference Dec 15-17 speakers information:

https://www.globalbigdataconference.com/virtual/global-artificial-intelligence-conference/event-146.html

https://www.globalbigdataconference.com/virtual/global-artificial-intelligence-conference/speakers-146.html