The Real Cost Of AGI—According To OpenAI

This week on In The Loop, I’m breaking down OpenAI’s staggering financial projections and what they reveal about the true cost of pursuing AGI. With spending expected to soar to $115 billion by 2029, the question is: where is all this money actually going—and can it really deliver the future OpenAI is betting on?

In this episode, I follow the money trail to uncover the massive investments in data centers, chips, and infrastructure that power AI. From the scale of Project Stargate to the risks of building custom hardware, I explore the economics, the environmental impact, and the high-stakes race among tech giants. By the end, you’ll have a clear picture of just how enormous—and risky—this journey to AGI really is.

⏭️ Episode Highlights

(00:40) - Why compute and training costs are driving massive investments

(06:20) - The cost of poser: The rising demand for energy and the environmental toll of AI infrastructure

(09:20) - The cost of training data: How copyright settlements could add billions to training costs

(10:40) - Historical parallels: railway mania, the dot-com bubble, and today’s AI boom

(11:45) - Closing thoughts: Will AI infrastructure spending outpace actual demand?

🔗 Links & Resources

Episode transcript with more resources on the Mindset AI blog

EP28 - Is The AI Bubble About To Burst?

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Jack Houghton

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