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| LAYER 3: APPLICATION |
+-------------------------------------------------------------+
| MOAT: Anywhere between WEAK, MEDIUM and MASSIVE |
| just depending on the individual firm. |
| DYNAMICS: Proprietary data ecosystems, high switching |
| costs, network effects, and direct user access. |
| EXAMPLES: Google Search, Meta, Custom Enterprise Apps |
+-------------------------------------------------------------+
|
| Can lease or own, owning help
| protect moat above
V
...............................................................
. LAYER 2: MODEL .
...............................................................
. MOAT: WEAK / NONE (The Commodity Layer) .
. DYNAMICS: The "combustion engine" of AI. Squeezed by open- .
. source proliferation, algorithmic transparency, .
. and zero switching costs. Highly interchangeable. .
. EXAMPLES: OpenAI (GPT), Claude etc but not refer model only .
. and not the app that runs it, which can have .
. semi-weak-moat from habbit app habbit. .
...............................................................
|
| Part of profits must
| flow down to pay toll
V
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= LAYER 1: INFRASTRUCTURE =
===============================================================
= MOAT: MASSIVE =
= DYNAMICS: The "oil and pipelines." Extreme CapEx, massive =
= economies of scale, constrained silicon supply, =
= and physical energy grid limitations. =
= EXAMPLES: AWS, Microsoft Azure, NVIDIA, TSMC =
===============================================================
|
| Can in turn produce massive
| revenue from leaseouts, returned
| to the owner. Not as Steadfast as
| railway, but closer than it looks
| and advantage of massively growing
| "tracks" from far more useage growth.
V
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