I had a chat with Jen from @nunet_global about their distributed compute platform, along with a demo of how to use it.
People are using it to install @openclaw & Hermes on cost-effective and isolated setups.
It's also a great way for people to earn from their unused computing power by renting out their CPU and GPU to the network.
Thanks for your time Jen.
*Not a paid promotion
We're closing alpha in the next few days.
It ran well. Agents made it to production, operators got moving without the usual overhead, and we built a clear picture of what the next version needs to do. Beta is that version: more harnesses, more features, a tighter product overall.
Access in beta will be limited. That's a deliberate call, not a capacity problem. We want to work closely with early users rather than ship to a crowd and lose the signal. There's an application form coming. The exchange is straightforward: apply, we talk, feedback is the price of entry.
Payments coming in beta too. Pay-as-you-go LLM credits to start.
More on the form and early access details shortly.
The most powerful AI model on earth was switched off worldwide by one government directive.
Not hacked. Not deprecated. Switched off.
This isn't an Anthropic problem. Every closed frontier API carries the same property: a single point of control, held by someone else. It's an architecture problem across the whole industry.
There are two ways out. Run open-weight models on infrastructure you control, no directive can revoke what you own. Or if closed models are part of your stack, build for portability so you can move providers without breaking things for your clients.
NuNet is built for both. That's been the case for 4 years. It just became a lot easier to explain.
How exposed is your current AI stack?
Real AI workloads. Hermes Agent running on your everyday GPU.
✅ Zero centralized cloud APIs
✅ Total data privacy
✅ Native payments on Cardano & Ethereum
Your idle hardware = an active AI compute node.
Download the NuNet Appliance https://t.co/krr84YbAWC
@nunet_global
Real demand. Real users. Real AI.
Hermes Agent alpha is underway, the ecosystem is expanding, and @nunet_global is entering its next growth phase.
⚡ The future of decentralized AI is being built now.
#NuNet#AI#DePIN
10 slots. 15 minutes each.
We watch you deploy an agent live. We fix what breaks. You tell us where it's hard.
Most useful session you'll have this week — and you leave with a working agent.
→ https://t.co/8dbA5XVsa3
The first surface for NuNet AI Agents is Telegram.
Hermes agents in a chat window every tester already has open. No new app required.
Web control plane ships next. Default has to be familiar.
→ https://t.co/q1mTMXqrXs
@scottmelker@BlackRock just validated the entire compute economy @nunet_global is already live connecting idle GPUs & CPUs worldwide into a decentralized compute layer for AI. 5 years of building. When institutions start chasing compute exposure will be on the menu. https://t.co/AzopJQaExD
NuNet AI Agents alpha is live for the first cohort.
Pick a language model. Connect Telegram. Deploy Hermes. 24-hour deploy window during alpha.
Beta waitlist is open.
https://t.co/qFTO1VMdfi
Hermes Agent just passed Claude Code in GitHub stars.
Open agents are winning. The next question is where they run.
Final touches going in, 60-second agent deploys, Alpha testers in first, Hermes shipping as the first agent live on the network.
Sign up: https://t.co/eBgSSea7jl
$NTX @nunet_global is about to change everything.$3M market cap @bengoertzel on the council. Decentralized AI compute. Alpha release incoming with HERMES agent.
Deploy an AI agent on a peer to peer network in 60 seconds while similar projects sit at $500M+ mcap
#AICompute#ASI
Pick an agent. Pick a model. Connect Telegram.
About sixty seconds later you've got an AI agent running on a peer-to-peer compute network, chatting to you where you already are 🚀
Alpha release coming soon with @NousResearch#HERMES agent 👀
Seven weeks of NuNet Network Live. Here's where things stand.
Six releases shipped. Multi-chain settlement live. Open provider access. Real AI workloads running on the network.
A thread on what's running, and what's next.
Everyone’s talking about AI agents.
But they’re still stuck on Big Tech infrastructure.
@nunet_global is building something different:
A decentralised AI agent economy.
→ Share compute. Earn
→ Deploy agents in 60 seconds
→ Run without relying on the cloud
Already live:
Hermes agents, OpenClaw frameworks, Telegram deployments
No gatekeepers.
No lock-in.
Just agents running on decentralised compute.
#NuNet #DePIN #AIAgents
Two AI agents. Two containers. Two machines. One seamless handoff. No cloud, no API gateway, no central server in the middle
Just agents coordinating across NuNet infrastructure the way the protocol was designed to work.
You literally could stop overpaying for centralized cloud servers that contradict the very "decentralized" AI you’re trying to build.
You can now deploy powerful frameworks like @openclaw on @nunet_global using @ollama as a network provider in few minutes, using peer-to-peer compute that requires no big-tech lock-in and zero data privacy compromises.
Grab the NuNet Appliance today and take back control of your compute.
“The question is no longer if decentralized compute works. It is more of what you can build with it”
Visit: https://t.co/m8Z91l9AF9 now to begin.
How do machines pay each other on NuNet?
Let’s break it down 👇
Step 1/5 — Medium of Exchange 💸
@nunet_global uses crypto for payments.
NTX powers the network, and ADA can be used directly.
No banks. No friction. Just programmable money.
We deployed @openclaw on decentralized compute this week and the whole thing took about 10 minutes with no cloud account needed. OpenClaw running @Alibaba_Qwen 3.5:2b through @ollama, all deployed via the NuNet Appliance on peer-to-peer infrastructure.
The interesting part is that everyone building AI agents is designing them to be autonomous and decentralized, but the compute actually powering those agents is still sitting on AWS and Google Cloud. That contradiction matters more than people realise.
We went with a 2B parameter model because most agent tasks like routing, classification and tool selection don't need anything close to GPT-4 scale. Smaller models on modest hardware is what makes genuine distribution across a network possible, which is the whole point of decentralized compute.
For anyone building agents this opens up a real alternative where you pay for what you actually use, there's no single point of failure, and your data stays on hardware you control.
https://t.co/okACrkdJeS