Generative AI, spearheaded by large language models, marks a transformative era in computing, poised to reshape human-computer interaction. This webinar explores the capabilities of this cutting-edge technology and shows how it can enhance your business operations.

Amanda Saunders, Sr. Manager, Enterprise AI Product Marketing, NVIDIA
Jeremy Krinitt, Senior Developer Relations Manager, NVIDIA

In this webinar, we explore the essential knowledge that AI teams should possess regarding generative AI, covering topics ranging from data acquisition and curation to model customization and deployment.

Amanda Saunders, Sr. Manager, Enterprise AI Product Marketing, NVIDIA
Donald Chouinard, Product Marketing Manager, NVIDIA

In today's competitive landscape, innovation and efficiency are imperative for success. The integration of artificial intelligence is now essential rather than optional, with large language models facing challenges in understanding domain-specific topics and occurrences of hallucinations. However, retrieval-augmented generation (RAG) offers a revolutionary advancement in AI, enabling businesses to harness domain-specific, real-time data like never before, as explored in this webinar focusing on building highly customized AI chatbots accessing, processing, and presenting data from current, trusted sources.

Amanda Saunders, Sr. Manager, Enterprise AI Product Marketing, NVIDIA
Jacob Liberman, Product Manager, NVIDIA

Generative AI stands as a cornerstone of enterprise transformation, offering innovative avenues while presenting challenges in developing and deploying end-to-end AI pipelines. Embracing a full-stack approach enables enterprises to surmount technical hurdles, enhance model performance, and expedite time-to-value, as explored in our webinar, which guides you through constructing an end-to-end generative AI workflow incorporating retrieval augmented generation, expediting training, fine-tuning, and deployment of large language models, and leveraging enterprise-grade runtimes for generative AI applications.

Anne Hecht, Senior Director, Product Marketing, NVIDIA
Tony Paikeday, Senior Director, Artificial Intelligence Systems, NVIDIA

As organizations shift from experimenting with generative AI to deploying and scaling these applications in production, the focus on secure and efficient AI inference is becoming critical. This webinar explores key strategies for optimizing AI inference at scale, while ensuring data security, compliance, and innovation agility through real-world enterprise case studies.

Bethann Noble, Product Marketing Manager, NVIDIA
Neal Vaidya, Developer Advocate, NVIDIA