Remember when sci-fi films like Iron Man, Her, and Interstellar amazed us with AI that could think, create, and connect? Those cinematic visions have swiftly evolved into boardroom realities.
Welcome to an event that cuts through the noise to deliver clarity and actionable insights. We bridge the gap between AI’s dazzling promises and practical business implementation. Our sessions provide frameworks, real-world case studies, and measurement strategies to turn technology into tangible results.
Join us to discover how to transform sci-fi hype into Monday morning action items on your GenAI journey—and connect with fellow pioneers committed to converting AI’s potential into competitive advantage.
Yesterday, AI was hype
Today, AI is implementation
Tomorrow, AI will be your competitive advantage
Session | Topics |
9:00 AM – 9:30 AM | Registration and Networking |
9:30 AM – 9:40 AM | Introduction |
9:40 AM – 10:20 AM | The Rise of LLMsThis talk traces the evolution of language models from simple next-word predictors to advanced LLMs capable of reasoning, contextual understanding, and multimodal inputs like text and images. It covers the progression from basic encoder-decoder architectures to sophisticated transformer-based designs. |
10:20 AM – 11:00 AM | Demystifying LLM Agents: Building Blocks, Workflows, and Best PracticesThis session offers practical strategies for building effective language model (LLM) agents. A shift away from complex frameworks towards simple, composable patterns for creating agentic systems. |
11:00 AM – 11:30 AM | Tea Break and Networking |
11:30 AM – 12:15 PM | AI Agents: From Concepts to RealityExplore a production-grade multi-agent AI system built in Python-based framework that tackles real-world challenges like access control, latency, and scale where agents collaborate to turn scattered enterprise data into fast, reliable, and contextual business insights. |
12:15 PM – 12:45 PM | Democratizing LLM Fine-Tuning with FSDP and QLoRAThis session explores cutting-edge techniques such as QLoRA (Quantized Low-Rank Adaptation) and PyTorch’s FSDP (Fully Sharded Data Parallel) that enable efficient fine-tuning of very large LLMs (up to 70 billion parameters) on consumer-grade hardware, lowering barriers for developers and researchers. |
12:45 PM – 2:00 PM | Lunch |
2:00 PM – 2:30 PM | The Art of Pairing with AIThis talk focuses on best practices for leveraging AI tools effectively, avoiding pitfalls that reduce efficiency, and strategies to maximize impact whether building, prompting, or using AI. |
2:30 PM – 3:00 PM | Productionizing LLMs on k8sIn this session, we’ll explore how to deploy and scale Large Language Models (LLMs) on Kubernetes, taking advantage of its robust orchestration capabilities for containerized applications. |
3:00 PM – 3:30 PM | Moonshot InitiativeWhat if a simple visual cue could reshape the world behind you? In this session, we unveil a prototype system that fuses real-time visual recognition with generative synthesis to alter environments on the fly. By interpreting physical features as semantic signals, the system triggers dynamic scene transformation, blurring the line between perception and imagination. We’ll explore the architecture behind this responsive visual pipeline, spanning object detection, latent mapping, and generative rendering. |
3:30 PM – 4:00 PM | Tea Break |
4:00 PM – 5:00 PM | LLMs in 2025: Power, Responsibility, and What’s NextA focused discussion on the challenges and opportunities in deploying Large Language Models and Generative AI, covering security risks, ethical considerations, legal frameworks, and emerging trends shaping the future of AI. A panel discussion featuring Dr. Ravindra Babu T, Govindarajan Sundararajan, Prabakaran Kumaresshan and Preethi Sreenivasan, moderated by Vignesh K. |
