The narrative that we need more data centers is a lie.
The world is not short on computing power. It is drowning in misallocated computing power. The raw capacity needed to run AI, the metaverse, and the next generation of AAA gaming already exists. Most of it is sitting turned off in people’s homes.
YOM is not building a better data center. We are building the layer that makes the data center optional.
The sleeping giant: 50-75% latent capacity
At any given second, 50% to 75% of the world’s consumer GPU power sits idle.
Millions of RTX 3090s, 4080s, and high-end gaming rigs are running browser tabs or nothing at all. This is the single largest reservoir of compute on the planet, and centralized cloud providers treat it as if it does not exist. We treat it as the supply side.
Activating that hardware does not add capacity. It unlocks a resource that is already manufactured, already distributed, and already paid for.
And consumer GPUs are not the only supply side. Carrier-tower-sited GPUs through a Tier-1 telecom operator partner (scoped 200 towers near-term, scaling to 19,000 masts) add deterministic edge coverage where it matters. Hybrid topology, not a single-source marketplace.
The economic floor centralized cloud cannot cross
To scale, a hyperscaler has to spend. Doubling capacity means pouring billions into silicon, concrete, land, and cooling, and that mortgage sets a hard floor under their pricing. They cannot charge below roughly $2.00 per hour because someone has to pay for the building.
YOM has no building.
We do not buy hardware. We do not pour concrete. We orchestrate a protocol across hardware that already exists, which puts our blended cost near $0.13 per hour, about 15x below the centralized floor. That is not a discount. It is a different cost structure, and it is mathematically out of reach for anyone carrying datacenter capex.
Defeating the speed of light
Centralized cloud is also fighting physics, and losing.
You cannot optimize the speed of light. If the server is a thousand kilometers away, the latency is baked in, and no amount of fiber fixes the fact that the box is simply too far from the player. YOM solves latency by ignoring geography: every gaming PC on the network is a potential edge node, which moves the compute into the user’s own neighborhood. Signal travels down the street instead of across the country, and the network holds sub-10ms median latency with nodes inside ~50km of the player.
That is local-console responsiveness, achieved through proximity rather than brute force.
What stays scarce when everything else goes to zero
The deeper shift is that software itself is collapsing in value. Anyone with a frontier model can generate their own app in a weekend. When everything can be generated, intelligence becomes abundant and software gets cheap. What stays scarce are the things you cannot prompt into existence: latency, locality, energy, hardware, and physical presence.
That is the ground YOM is built on. Owning information matters less when generation is cheap; operating low-latency systems close to the player matters more. The economy that follows rewards real contributors in real places, not distant monopolies. Miners, retail operators, and telcos contribute on the same open substrate. The network is permissionless.
The shift is structural
We are watching the transition from rent-seeking platforms to participatory networks.
- Old world: you pay a corporation to rent a computer far away. The corporation keeps the margin; the planet pays for new manufacturing.
- New world: you pay a peer for a computer nearby. The contributor keeps the reward; nothing new has to be built.
YOM is the infrastructure for that transition. We start with cloud gaming because gaming is the hardest real-time streaming problem there is: ultra-low latency, AAA fidelity, millions of concurrent sessions. Solve gaming and the same mesh serves AI inference, autonomous compute, and digital twins by inheritance.
And consumer cards reach further than the marketing assumes. Recent research on algorithmic communication packing has shown that the hyperscaler interconnect moat can be broken from the math side, not the hardware side. With matching software primitives in the stack, consumer GPUs can serve frontier-class training and large-model inference, not just inference at the edge.
Step one is gaming. Step two is everything else.