Uploaded April 2026 | Updated September 2026, 2 weeks ago
Learn how to design, train, and deploy large-scale custom generative AI models. This session will step you through data preparation, fine-tuning, and infrastructure management, and will highlight best practices for scaling large models efficiently. You’ll also see real-world examples with Adobe Firefly Foundry and NVIDIA NeMo integration that demonstrate how teams are applying these techniques to production-grade AI systems.
Speaker: Ely Greenfield | CTO | Adobe
Key Takeaways:
Data Preparation: Discover how customer images, video, and 3D assets are analyzed using vision language models to extract unique world context and specific visual style.
Fine-Tuning: Learn how very large generative AI models are fine-tuned at scale. enabling distributed training across tens of thousands of customer assets, using NVIDIA's technology stack (including CUDA and NCCL).
Infrastructure Management: Understand how AI infrastructure is built to serve large and varied customer bases, each with dozens of personalized models deployed concurrently, while maintaining secure isolation, performance efficiency, and production reliability.
Industry: Media & Entertainment
Topic: Agentic AI / Generative AI - Video Generation
Technical Level: Technical - Intermediate
Intended Audience: Developer / Engineer
NVIDIA Technology: Cloud / Data Center GPU, NeMo, NVIDIA AI Enterprise
#NVIDIAGTC
Learn how to design, train, and deploy large-scale custom generative AI models. This session will step you through data preparation, fine-tuning, and infrastructure management, and will highlight best practices for scaling large models efficiently. You’ll also see real-world examples with Adobe Firefly Foundry and NVIDIA NeMo integration that demonstrate how teams are applying these techniques to production-grade AI systems.
Speaker: Ely Greenfield | CTO | Adobe
Key Takeaways:
Data Preparation: Discover how customer images, video, and 3D assets are analyzed using vision language models to extract unique world context and specific visual style.
Fine-Tuning: Learn how very large generative AI models are fine-tuned at scale. enabling distributed training across tens of thousands of customer assets, using NVIDIA's technology stack (including CUDA and NCCL).
Infrastructure Management: Understand how AI infrastructure is built to serve large and varied customer bases, each with dozens of personalized models deployed concurrently, while maintaining secure isolation, performance efficiency, and production reliability.
Industry: Media & Entertainment
Topic: Agentic AI / Generative AI - Video Generation
Technical Level: Technical - Intermediate
Intended Audience: Developer / Engineer
NVIDIA Technology: Cloud / Data Center GPU, NeMo, NVIDIA AI Enterprise
#NVIDIAGTC
