Been mapping out a few narratives lately, and one that keeps repeating is how compute is quietly becoming the backbone of Web3 especially with AI demand in the mix.
@Fluence $FLT its neatly into this. It’s not trying to be another generalized chain it’s focused on decentralized compute, where developers can access distributed resources instead of relying on centralized cloud providers. As AI demand grows, this kind of verifiable and flexible compute layer starts to make more sense.
What’s interesting is how this connects with other projects moving in parallel:
• @io.net $IO → decentralized GPU networks focused on AI workloads
• @Nosana $NOS → community-powered compute for running AI inference
• @Golem Network $GLM → one of the earlier peer-to-peer compute marketplaces, now aligning more with modern AI use cases
Different stages, different models but all circling the same problem: how to source and scale compute without central bottlenecks.
Feels like the narrative is becoming more grounded. Less about abstract decentralization, more about who provides the infrastructure behind AI and data processing.
Fluence doesn’t feel like the loudest in the room, but it sits right at that intersection which is probably why it keeps coming up in research.