Podflow AI by Virtuals (POD)

ai inference x crypto is perfect

we have a solid, organic project with $pod, sitting relatively low

all in a category led by $vvv, which rly isn’t more than an artificialyl spoofed VC scam. @ErikVoorhees is a con artist and would hit prison time in any trad market

observe.

$POD 👀

For those who compare $POD and $VVV remember they’re closely related but operate at completely different layers of the stack.

Venice: End user experience layer focused on privacy, ease of use, and creative tools

POD: Infra layer focused on scalable, permissionless inference compute and open model development

They are synergistic partners rather than direct competitors. See I f you break the AI value chain in layers👇

1. Frontier training (hyperscaler-dominated)
2. Model weights & fine tunes (increasingly open and commoditizing)
3. Inference delivery & orchestration (the battleground)
4. Application/agent layer (exploding surface area)

@dphnAI sits squarely in layer 3 but bleeds upward into model curation and downward into hardware incentives. It is…

- Orthogonal to hyperscalers (they win on peak frontier scale and enterprise SLAs)
- Complementary to gen purpose GPU DePINs
- Also synergistic with privacy first frontends like Venice

I personally see it as the clearest expression yet of a parallel AI infra stack optimized for the properties that centralized systems structurally cannot optimize for i.e user-defined alignment, permissionless participation and direct usage to value feedback.