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The Next AI Platform
May 9 @ 10:00 am - 7:30 pm
The Next AI Platform will feature live in-depth interviews with those are the forefront on both the technology creation and end user sides of the AI infrastructure spectrum with a focus on investments up and down the AI infrastructure stack–from chips and accelerators to storage, networking, memory, and beyond.
More coming on the agenda but for now, here is a sneak peek at just a fraction of the day’s content…
Your hosts for the wide range of in-depth, technical interviewers: Nicole Hemsoth, Co-Founder, Co-Editor, The Next Platform; Timothy Prickett Morgan, Co-Founder, Co-Editor, The Next Platform. More interviews will be conducted by contributing editor, Stacey Higginbotham and analyst/contributing author, Paul Teich.
From Large-Scale ML Infrastructure at Twitter to the Future of Training
This live interview with Clement Farabet will chart the shifting hardware requirements for deep learning at Twitter scale over time and bring us to the present where both training and inference requirements are pushing server infrastructure in new directions. This conversation will focus on the shifting needs of AI hardware infrastructure and look ahead to a future with larger, more complex training sets and models (GANs, etc) and efficient inference.
AI Chip Startup Ecosystem: In-Depth Interview Series Followed by Panel
We will sit down with the leaders behind some of the most noteworthy AI chip architectures, including Nigel Toon, co-founder and CEO of Graphcore and Jin Kim, VP and Chief Data Scientist at Wave Computing for individual interviews followed by a panel where they will be joined by other architecture startup founders, including Mike Henry, co-founder and CEO of AI chip startup Mythic for a view into how inference-specific chips fit into this evolving ecosystem.
VC Panel: Future Concepts & Directions for AI Hardware Investments
This interview will feature Vijay Reddy of Intel Capital and Michael Stewart from Applied Ventures, Rob Chira, as well as other VCs as we discuss the balance (and lack thereof) in hardware investments in AI chips, software, and other elements of the stack, including storage and networking. We will talk about how and where the market might drive the industry and how that meshes with real (and perceived) demand. In other words, we’ll be focused on asking what is real in this space and what might not stand the test of time.