# Training now works on distributed, heterogeneous networks

- **Speaker:** Greg Osuri
- **Attribution:** attributed
- **Said:** 2026-07-29
- **Theme:** Decentralized AI — https://www.gregosuri.com/predictions/decentralized-ai/
- **Source:** AI Data Centers Are Eating the Grid. Is There Another Way? (The People's AI: The Decentralized AI Podcast)
- **Watch at:** 00:39:02 — https://www.buzzsprout.com/2440361/episodes/19568316-ai-data-centers-are-eating-the-grid-is-there-another-way
- **Canonical:** https://www.gregosuri.com/predictions/decentralized-ai/2026-07-29-training-now-works-on-distributed-heterogeneous-ne-k4hj/
- **Cite as:** Greg Osuri, "Training now works on distributed, heterogeneous networks," AI Data Centers Are Eating the Grid. Is There Another Way? (The People's AI: The Decentralized AI Podcast), 29 Jul 2026, 00:39:02. https://www.buzzsprout.com/2440361/episodes/19568316-ai-data-centers-are-eating-the-grid-is-there-another-way

## Quote — verbatim

> Today, training workloads are evolving to a point that can work on distributed networks, heterogeneous networks, highly fault tolerant. We're seeing companies like Pluralis, for example, training fairly large or usable models on fully decentralized networks.

## Context — site annotation, not spoken

Adds that algorithms "can communicate less frequently in bigger batches," and that Razer (the gaming hardware company) ran a successful April 1st image-generation campaign on Akash home nodes — proof home nodes work at scale for a publicly traded company [00:39:02].