This session from theCUBE and NYSE Wired Robotics and artificial intelligence
Infrastructure Leaders Series, the third annual infrastructure leaders event,
features Max Kan of SemiAnalysis. The discussion examines infrastructure topics
such as tokenomics, inference hardware, model distillation, agentic workloads
and the evolving dynamics between frontier and open source model development.
Kan examines token economics and AI infrastructure dynamics, focusing on agentic
workloads, token volume growth, model distillation, inference hardware
trade-offs and accelerator architecture segmentation. They emphasize that
accelerating global token production driven by multi-turn agentic workloads
requires monitoring frontier-model token share to forecast market shifts. They
note that low switching costs make model quality the principal competitive
factor and that hardware segmentation channels most volume to general-purpose
chips while premium accelerators such as Groq and Cerebras serve
latency-sensitive high-price niches. theCUBE Research frames the conversation
with hosts John Furrier and Gabe Valladares and explores implications for
developers, cloud providers and AI labs during the ongoing infrastructure
buildout. Key insights include: - Global token production accelerates as
multi-turn agentic workloads expand, making frontier-model token share a
critical forecasting metric. - Low switching costs elevate model quality as the
primary determinant of adoption. - Hardware segmentation directs volume to
general-purpose chips while premium accelerators such as Groq and Cerebras
address latency-sensitive high-price niches.
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In this interview from theCUBE + NYSE Wired: Robotics & AI Infra Leaders 2026, Max Kan, tokenomics technical lead at SemiAnalysis, joins theCUBE's John Furrier to discuss the economics powering the AI infrastructure buildout. Kan explains how his team sits atop SemiAnalysis' full-stack coverage, tracking token production and pricing across hyperscalers and AI labs. He unpacks the fierce open-source-versus-closed-source debate reignited by Kimi K2 and NVIDIA's public comments, framing much of the discourse as companies "talking their book" rather than pure phi...Read more
