# 992: Tokenmaxxing vs AI Hardware Bottlenecks

Page: https://stenobird.com/podcast/super-data-science/992-tokenmaxxing-vs-ai-hardware-bottlenecks
Text version: https://stenobird.com/podcast/super-data-science/992-tokenmaxxing-vs-ai-hardware-bottlenecks.md
Podcast: [Super Data Science: ML & AI Podcast with Jon Krohn](https://stenobird.com/podcast/super-data-science)
Published: 2026-05-15T11:00:00+00:00
Episode link: https://www.podtrac.com/pts/redirect.mp3/chrt.fm/track/E581B9/arttrk.com/p/VI4CS/pscrb.fm/rss/p/traffic.megaphone.fm/SUPERDATASCIENCEPTYLTD2200836202.mp3
Audio file: https://www.podtrac.com/pts/redirect.mp3/chrt.fm/track/E581B9/arttrk.com/p/VI4CS/pscrb.fm/rss/p/traffic.megaphone.fm/SUPERDATASCIENCEPTYLTD2200836202.mp3
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JSON: https://stenobird.com/v1/public/podcasts/super-data-science/episodes/992-tokenmaxxing-vs-ai-hardware-bottlenecks
Duration seconds: 872

## Resource

While “tokenmaxxing”, the social media trend of maximizing AI token consumption as a vanity metric, takes off online, the physical infrastructure behind AI is slamming into serious bottlenecks. In this Five-Minute Friday, Jon Krohn maps out the four overlapping supply-chain constraints choking AI compute: GPUs (with NVIDIA Blackwell sold out through mid-2026), high-bandwidth memory (quintupled demand since 2023, only three manufacturers worldwide), CPUs (agentic AI requires 12x more CPUs per GPU than chatbots), and electricity (Gartner projects power shortages will restrict 40% of AI data centres by 2027). Find out why the five biggest hyperscalers are on track to spend $725 billion on AI infrastructure in 2026, where the reasons for optimism lie, and why Jon says you should definitely not tokenmaxx. Additional materials:⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/992⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

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## Transcript

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