What’s New in AI: AI Chips with Evan Sparks

Join host George Anadiotis and guest Evan Sparks, chief product officer of AI at Hewlett Packard Enterprise, who’ll discuss the AI chips and new AI hardware that will enable the latest AI-powered systems to run more efficiently and effectively. AI chips provide an advantage over general-purpose processors for AI systems that require exponentially larger volumes of data and computational power. Generative AI and new models like ChatGPT, GPT-4, and others have migrated beyond the AI field into the general public. At the same time, the creators of AI chips, which enable practitioners to train and deploy these models, are equally engaged in a somewhat lesser-known effort: the race to produce the best hardware to support these powerful AI systems. Join George and Evan to discuss how AI chips are becoming the backbone of new AI systems, and hear their thoughts on the state of AI chips today and the developments to look for in the near future.

What’s New in AI gives you a chance to hear from leading minds in the field on topics such as generative AI, large language models, responsible AI, AI hardware, and other developments as they appear. Host George Anadiotis, founder of Linked Data Orchestration, and members of O’Reilly’s community of experts help you make sense of the bigger picture in AI and leverage emerging AI technologies to solve your organization’s most challenging problems.

• Understand the advantages of these new hardware technologies and the types of applications and systems they can power
• Learn about different AI chip architectures and what each brings to the tableExplore how to evaluate the options
• Discuss the role of software stacks in abstracting different AI chips or integrating them tightly in your applications
• Learn about the changing terrain of AI hardware vendors and service providers

• You’re a data scientist, machine learning engineer, machine learning architect, leader, or practitioner who designs, develops, and deploys machine learning systems.
• You want to keep up-to-date on the latest developments and breakthroughs in the field of AI.

Prerequisites

• A basic understanding of machine learning systems

Recommended follow-up:

• Read “Infrastructure and Tooling for MLOps” (chapter 10 in Designing Machine Learning Systems)
• Watch “Energy-Efficient AI and High-Performance Computing Data Centers” (event segment video)
• Watch Fast and Lean Data Science with TPUs (video)