📢 New website is live with full GPU access available for new users! We’re excited to announce that Fluence Console is now open for instant access to GPU Containers, Virtual Machines, and Bare Metal deployments. 👉 console.fluence.network/auth… 👈 🌎 Get easy access to 1400 GPUs across 32 regions and 71 data centers now: 1️⃣ Sign up via GitHub, Google, or Email. 2️⃣ Top up your balance. 3️⃣ Deploy your first workload! Key features 👇

I don't know why everyone is complaining about a shortage supply of B200's and H100's... @fluence_project was giving them out for free at @superai_conf.

at @superai_conf with @fluence_project with <3 from @ionet

Look what we’ve got at our booth at @superai_conf! 🍫 The sweetest GPU cluster deals on the market. Hurry up — they’re melting fast! 📍 PB47, Level 5

Fluence team just landed in Singapore 🛬 🇸🇬 We’re excited to meet you all at @superai_conf very soon! Stop by our booth on Level 5, near the Main Stage to learn about our global network of GPU clusters, explore available locations, and learn more about our new GPU Auction Platform. 📍 Booth #PB47, Marina Bay Sands Who’s already on the ground? 👋

AI infra is entering a $5T buildout. But reserved GPU clusters are still bought through intros, private quotes, hidden inventory, and weeks of negotiation. No order book. No clearing price. That’s not a market. It’s a maze. We’re about to change that. More soon.

The $FLT Grid League on Gate with @fluence_project Grab your spot: app.origami.tech/competition… Trade FLT-USDT, generate volume, take your share of 3,000 USDC in rewards. Start: 12:00 UTC, May 15 End: 12:00 UTC, Jun 12 New to Grid Leagues? Setup takes under 5 minutes: x.com/origamitech_/status/20…

you probably noticed… as AI keeps scaling, the demand for compute and data is growing way faster than the current supply. and right now, most of that supply is still expensive and heavily centralized. DePIN is starting to position itself as the alternative layer, offering infrastructure at ~50–80% lower cost while redistributing supply across decentralized networks. instead of focusing on obvious large caps, I’ve been looking at smaller projects where the asymmetry between risk and potential upside is more meaningful. 1. @grass - $GRASS - one of the clearer DePIN data plays right now, already showing real usage with millions of devices contributing bandwidth for AI data scraping. - the “data for AI” narrative is getting stronger, and Grass sits directly in that flow with actual adoption and revenue backing it. → this is one of the few cases where usage isn’t just theoretical, it’s already happening at scale. 2. @cysic_xyz - $CYS - positioned at the intersection of ZK and AI, focusing on verifiable compute, which is becoming increasingly relevant as AI systems scale. - backed by strong names and already pushing toward mainnet, with early integrations and agent-based use cases starting to form. → if ZK AI becomes a real convergence narrative, this is one of the more direct ways to get exposure. 3. @AethirCloud - $ATH - building a decentralized GPU cloud targeting AI and gaming, with real demand already coming from rendering and compute-heavy workloads. - this is less about theory and more about capturing existing demand for GPU rental in a more flexible way. → with an expanding ecosystem and enterprise angle, it’s one of the more “business-like” models in the space. 4. @PhalaNetwork - $PHA - focused on confidential compute using TEE, which becomes increasingly important as AI starts handling sensitive data. - this sits in a quieter part of the market, but the use case is clear once privacy becomes a real constraint for AI adoption. → longer-term, this kind of infrastructure tends to matter more than people expect early on. 5. @fluence_project - $FLT - one of the more solid plays from a product standpoint, already showing real revenue and targeting enterprise compute demand. - competing primarily on cost efficiency, offering significantly cheaper infrastructure compared to traditional cloud providers. → as more AI startups look for cost optimization, models like this start to make more sense. => ngl,I think the core point is simple. AI demand is already real and accelerating, but whether these networks can scale supply fast enough and actually capture value at the token level is still an open question. not all of them will survive as the cycle evolves, that’s just how this space works. but if DePIN x AI shifts from narrative into sustained usage, a few projects here could outperform as real demand, early infrastructure, and speculation start to overlap. this is just a perspective based on current data, nfa,,.