You can disagree, but the product builders I respect keep coming to the same conclusion:
In-app ads will fund a large share of AI inference.
For
@thinkinstant, the path is clear.
Phase one: serve 1–2 models with a clear advantage in inference speed and performance.
Phase two: bring that inference into products people already use, while building our own application.
Better products earn distribution. Give users a better experience, faster, at a lower cost, and you give them a reason to switch.
Here’s what excites me most.
We can build revenue beyond the inference API. Applications built on our subnet can direct 100% of their revenue to buybacks and burns, helping us scale burns beyond miner emissions.
The goal is a deflationary alpha token: more tokens burned than emitted.
We see two paths: sell premium inference at 2.5x what we pay miners, or build additional revenue streams on top of the subnet to fund a total of 2.5x miner burns.
Inference can cover miners while our additional endeavors funded by owner emissions can cover itself and stakers.
Emissions from the Bittensor network will ideally be used to increase our price floor aka mcap:LP ratio.
But first, we have to launch and prove the foundation works.
That means verifying inference without a trusted execution environment (TEE). Removing that requirement can give miners more hardware flexibility and developers a better cost and speed profile.
Niki is finishing the final tests of the miner code. I’m focused on growth.
Prove the inference. Earn the usage. Scale the revenue.
Accelerate. ⚡️🧠