AI’s next phase hinges on a paradox: falling costs could threaten today’s winners while unlocking far greater demand.

Steve Hou, head of research at Silicon Data and former Bloomberg strategist, joins us to examine the changing economics of AI compute.

We discuss token efficiency, model routing, GPU pricing, memory bottlenecks, and when enterprise adoption may finally deliver measurable returns. Enjoy!

TIMESTAMPS:

00:00 Intro

01:01 Why AI Compute Needs Hedging

06:55 What The Token Index Really Shows

14:04 Token Maxing Meets Efficiency

18:35 Who Captures AI’s Value?

22:12 Old GPUs Reveal Surging Demand

27:10 GPU Markets Keep Tightening

32:03 The Memory Bottleneck

37:07 AI’s Next Phase

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EVENTS

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DISCLAIMER

Nothing said on Forward Guidance is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only. Any views expressed are opinions, not financial advice. Hosts and guests may hold positions in the companies, funds, or projects discussed.