Demand for deep learning training and inference is accelerating with the growing recognition across nearly every industry category of the positive impacts that AI/deep learning computer vision, natural language processing and multi-modal models can make on business and organizational applications. For this reason, Habana and Equus have teamed up to drive success and ease of implementation with these AI technologies for customers across a wide array of industries.
Join Equus and Habana Labs to learn how Equus’ Lab-as-a-Service can help you plan, build and deploy your advanced computing infrastructure with Habana® Gaudi®2 hardware and software optimized for deep learning workloads. In this 30-minute live webinar, they will discuss how the Gaudi®2 is designed to maximize training and inference throughput and efficiency, while providing developers with optimized software and tools that scale to many workloads and systems. With Equus you can save time, resources, and money with end-to-end customized solutions for your deep learning workloads. We will conclude with a live Q&A.
Agenda
- Equus and Habana overview
- Cloud and datacenter solutions powered by Gaudi processors
- Application of Gaudi2 for Deep Learning/Generative AI/ Large Language Models
- Live demo
- Q&A
Featured Speakers
Sree Ganesan
Software Product Management at Habana Labs
Sree Ganesan leads Software Product Management at Habana Labs, working alongside a diverse global team to deliver state-of-the-art deep learning capabilities of the Habana SynapseAI® software suite to the market.
Previously, she was Engineering Director in Intel’s AI Products Group, where she was responsible for AI software strategy and deep learning framework integration for Nervana NNP AI accelerators.
Kevin McKelligon
Business Development Manager at Equus
Kevin McKelligon is Business Development Manager with 25+ years of account management experience. He is passionate about learning new technologies and helping customers address business challenges and achieve their desired outcomes.