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
› Join us at Digital Asset Summit 2026 Asia October 7th & Digital Asset 2026 London November 10-11th
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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.
