
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 FOLLOW STEVE › X/Twitter – https://x.com/stevehou › Silicon Data – https://www.silicondata.com/ FOLLOW THE SHOW › Forward Guidance – https://x.com/ForwardGuidance › Felix – https://x.com/fejau_inc › Telegram – https://t.me/+CAoZQpC-i6BjYTEx › Blockworks – https://x.com/Blockworks EVENTS › Join us at Digital Asset Summit 2026 Asia October 7th & Digital Asset 2026 London November 10-11th https://blockworks.com/events 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.
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