Tokenomics: The Economy Of AI Part 1

    Tokenomics: The Economy Of AI Part 1
    • As I start deep diving on memory chip stocks and whether they represent a potentially amazing multi-year investment opportunity I came across something amazing...Tokenomics!
    • Tokenomics is the fundamental economics of AI and understanding this is critical to understanding whether the current boom is headed for a bust, or years (or decades) of incredible growth.
    • Headlines about falling token prices make it seem like the Frontier labs who are driving 185% growth in compute backlog are in trouble, it's the opposite.
    • Blackwell GPU systems that came out last year are just NOW starting to be fully integrated into datacenters. Blackwell is able to generate tokens 35X cheaper than Hopper.
    • The rate of token creation is 65X faster meaning the supply and cost of tokens is going to crash...that's true...and that's WONDERFUL NEWS! Not just for Nvidia, but for AI frontier labs.
    • When OpenAI cut prices 100X over 18 months revenue went up 4.55X because demand soured 455X. When Anthropic cut prices 100X demand rose 330X and revenue more than tripled.
    • This is called Jevon's Paradox (specifically the Khazzoom-Brookes Postulate) which says that as efficiency rises this lowers cost and leads to MORE usage than before.
    • This fundamental law of economics (and technology specifically) means that falling prices open up more use cases and grow the market...This is great news for Nvidia and thus the world😉😂
    Adam Galas
    Jun 16, 20268:49 PM3320

    This is the start of a multi-part series about memory chip stocks…but just like the SpaceX series began as a single article, and then evolved into a grand epic journey into the entirety of the human condition😉😂, well part 1 of this report became a delightful and very insightful deep dive into Tokenomics!

    Update On the AI Boom: Don’t Forget Sagan’s Law😉

    Here is what I mean.

    RPO (remaining performance obligations) is the proxy for how much demand the hyperscalers have (contracted revenue) for AI datacenters.

    Source: FactSet

    Note the growth rate the company is reporting…363% in the last quarter, and even the slowest growth period back in 2025 was “just” 41%. Now compare that to the consensus of 13% CAGR growth through 2029. Estimates keep rising because analysts are

    Ok, so let me show you something really exciting.

    Let Me Explain A Simple But Powerful Model For Understanding the AI Boom

    Do you remember when DeepSeek came out in January of 2025 with R1, and we had “DeepSeek Monday”?

    Remember DeepSeek Monday? Jan 27th, 2025?😉

    Remember how the AI boom was over because of DeepSeek's cheap model?😂

    Jevon's Paradox is real...and Tech CEOs said so on DeepSeek Monday. They were right.

    DeepSeek claimed to have trained R1 on about $5 million BUT they didn’t include any costs other than the single training run.

    In other words, they distilled US models to create a training model, then set up an optimized training run for the final model, and THAT and only THAT run cost $5 million.

    The idea that a startup in China pulled a “Apple in a garage” and suddenly blew up the business models of Amazon, Google, and Microsoft, who were building AI datacenters to handle the data…(not training models themselves other than Gemini).

    Not to mention Jevon’s Paradox…which Satya Nadella (CEO of Microsoft) explained that very day.

    Jevon’s Paradox: The Heart Of How Technology Has Always Worked

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