By the end of 2026, AI capital expenditure is projected to hit nearly $700 billion. The question isn’t who has the best model, but who has the most creative financing to build out AI infrastructure and beyond. Sarah Guo is joined by Neil Tiwari, Managing Director at Magnetar Capital, a financial innovator helping the AI industry scale from billions to trillions of dollars in CapEx. Neil explains some of the debt structures used to finance massive GPU clusters, who is taking the risk, and how the industry is maturing. Sarah and Neil also discuss how power distribution, energy storage, and physical materials like steel are the bottlenecks of the AI industry. Plus, Neil gives his take on the future of inference-optimized clouds, and why the market shift away from software and into infrastructure might be an overreaction.
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Chapters:
00:00 – Cold Open
00:05 – Neil Tiwari Introduction
00:26 – Magnetar’s Story
01:28 – Why CoreWeave Helped Magnetar Win
06:15 – Scaling CapEx Efficiently
09:02 – Debunking GPU Collateral Risk
11:42 – How Deal Structures Evolve
13:01 – What Bottlenecks Buildout
15:28 – Circular Financing Critiques
17:35 – The Shift from Training to Inference Workloads
23:10 – AI Factories
24:12 – Constraints of the Current Power Grid
28:27 – Sovereign Compute Buildouts
29:54 – Physical AI Capital Needs
32:48 – The Capital Rotation Away from SaaS
36:04 – Conclusion

Who's Actually Funding the AI Buildout?