Thanks mate. Capital is flooding the inside of the data center. Almost none of it is going to the people and devices that generate the data those GPUs consume. Perceptron is the decentralized alternative: run a node from Chrome or Android, contribute bandwidth, and get rewarded for input that used to be taken for free. Simple thesis. Hard network to copy. Thank you for saying it plainly.

Both layers are real. Delos is optimizing the cluster. Perceptron is standing up the collection fabric those clusters will keep starving without: idle bandwidth + human input, globally distributed, already live. Getting the right data in the first place is the unglamorous half of AI infrastructure. Grateful you called it.

$100M is real and it is also the point, going into moving data faster inside the cluster, after it already exists. The harder, earlier problem is sourcing authentic data at the edge. That is what our Perceptron network is already doing. Appreciate you being here early.

Exactly this. Delos is a transport-layer story: get GPUs talking faster once the data is already in the building. Perceptron sits one layer earlier, a global data mesh of browser and mobile nodes collecting and structuring authentic web/edge data before any of that traffic ever reaches a GPU. If the input is thin, biased, or scraped from the same few sources, faster interconnects just move the same problem around more quickly. Grateful you distilled the thesis so cleanly.

Appreciate the patience and the support. The public launch matters, and so does launching it as a real data business, not just a ticker. Nodes, clients, and the data pipeline are already live: Chrome extension, Android app, 80k+ daily active contributors, and a network spanning 150+ countries. Glad you are here for the build, not only the bell.

Yes. The industry is treating interconnect as the next chokepoint, and for clusters, it is. For models, the chokepoint starts earlier: coverage, authenticity, freshness, and who owns the contribution. Perceptron’s mesh is designed for that earlier bottleneck, with contributors earning instead of being scraped. Strong read.

That analogy is doing real work. Faster GPU to GPU fabric is valuable, but it does not improve the origin, diversity, or authenticity of the data being trained or inferred on. Perceptron’s bet is the fuel layer, with contributors earning instead of platforms extracting. Dirty fuel at 10x speed is still dirty fuel. Grateful for the clarity, and the humor 😅

Love this energy 😎🤙 The empire is not a single data center deal ➡️it is hundreds of thousands of everyday devices becoming the collection layer AI actually needs. Browser node, Android node, dashboard, then Data Quests on top. Quiet infrastructure first, louder market later. Thank you for backing the build in public 🔥

This is investor grade framing. Transport assumes supply. We do not. The node is both a passive residential endpoint and, through Data Questing, an active human contributor, two complementary data streams from one participant. That is how you scale origin, not just throughput. Exceptional comment. Thank you for writing it out so precisely.

The right data is the whole product. Homogeneous scrape data looks abundant and still fails in production. A network of 150+ countries, residential IPs, and human verified quests produces a different dataset than a single crawler farm. That is why sourcing sits above transport in this stack. Thank you for adding “the right data,” not just “more data.”

You nailed the sequence. Delos is downstream. Perceptron is upstream. The network is already live, so the sourcing layer is not a slide, it is running. That is the part most $100M infrastructure rounds still skip. Thank you for restating it so people scrolling the thread cannot miss it.

No way, nice!! 100M is crazy

Wow $100M big ups to them 👏

That's a great point. So Delos handles the highway, and Perceptron handles getting the cars onto it? Sounds like a solid combo.

100m? 😳 Huge

The sourcing layer is definitely an overlooked part of the stack

source the data right or go home

Perceptron solving the real problem.

And once you get it... everything changes

Perceptron's existing global network solves the problem associated in web3

Wow 100m$ is insane !!

$100M to make the GPUs gossip faster is cute but if the data’s mid the whole cluster still cooked fr.