Organizer: intel ai.
About the Webinar
- Date: 26th June 2025
- Time: 5:00 – 6:00 PM IST
- Free Registration
- Who Should Attend: This session is ideal for AI/ML developers, system architects, and infrastructure engineers working on Generative AI use cases, looking to optimize performance, efficiency, and scalability across the stack.
Key Takeaways:
- Understand the distinct computational demands of Generative AI workloads and why traditional infrastructure falls short.
- Learn the why and how of optimization across hardware, frameworks, and applications for Generative AI.
- Get hands-on insights into hardware acceleration technologies like Intel Xeon’s AMX, Intel AI PC’s NPU, and Gaudi AI Accelerators.
- Discover software-level tuning strategies and integration approaches that accelerate deployment while improving energy efficiency.
- Explore methods to reduce Total Cost of Ownership (TCO) without compromising performance or scalability.
- Gain the opportunity to connect with domain experts and peers, sharing real-world learnings and challenges in deploying GenAI workloads.
Apply Link
As Generative AI continues to redefine what’s possible across industries, the demand for scalable, high-performance infrastructure is rapidly increasing.
This workshop-style webinar dives deep into the cutting-edge techniques and tools that are transforming how we optimize Generative AI workloads—across hardware, software, and application layers.
Join us as we explore how to harness the full potential of hardware accelerators such as the AMX Accelerator in Intel Xeon, NPU in Intel AI PC, and Gaudi AI Accelerators to significantly boost performance and reduce total cost of ownership (TCO).
We’ll also cover best practices in AI application development and dive into software framework-level enhancements that maximize power efficiency and shorten development cycles.
Whether you’re building foundational models or deploying enterprise-scale AI apps, this session will equip you with practical strategies to scale smarter and faster.
Speaker: Anish Kumar, AI Software Engineering Manager at Intel Corporation, as he reveals how to unlock maximum performance across every layer of your GenAI stack.