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NuNet
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NuNet provides globally distributed computing power & storage for decentralized networks #DePin 🔗http://nunet.io/links 🚨 Get NTX - https://bit.ly/3RmoHrG
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NuNet
03-20
The AI industry talks about orchestration constantly. But it's conflating two different things. Software orchestration: coordinating agent logic. Which agent handles which task. How they pass information. When to escalate. LangGraph, CrewAI, AutoGen; all software orchestration. Compute orchestration: coordinating the physical resources agents run on. Which hardware runs which workload. How resources are allocated dynamically. What happens when a machine fails. You need both. Most people only think about the first one. Software orchestration without compute orchestration is like writing a symphony without an orchestra. The composition exists. Nobody can play it. NuNet operates at the compute orchestration layer. The protocol discovers available resources across any hardware; edge devices, GPUs, servers, data centers. Matches workloads dynamically. Recovers from failures. Settles payment. The software layer decides what agents do. The compute layer makes sure they can actually do it. Both layers need to be orchestrated. Only one is getting built.
NTX
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NuNet
03-12
The autonomous AI agent market hits $8.5 billion this year. $35 billion by 2030. But here's what Deloitte also found: organizations with mature orchestration capture 2-3x more value from their AI investments. The problem is 50% of enterprise AI agents are still operating in silos. Disconnected workflows, redundant automations, no coordination between systems. The industry spent years building intelligence and basically forgot to build the infrastructure underneath it The industry built intelligence. It forgot to build coordination. Orchestration isn't a feature. It's the entire infrastructure layer that makes multi-agent AI actually work. At the compute level, orchestration means: discover resources, match workloads, deploy dynamically, recover from failures, settle payments. Automatically. That's what NuNet does. Not at the software layer. At the compute layer underneath everything. When AI agents need to coordinate across devices, owners, and environments, the compute layer has to be orchestrated too. The model race is over. The orchestration race is starting 🏎️
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NuNet
03-06
Reinforcement learning, motion diffusion models, onboard perception, all running across different compute environments. Training these policies runs on GPU clusters. But the character itself runs inference on embedded hardware in real time, navigating guests and generating motion autonomously That edge-to-cloud coordination, simulation and training in the data center, real-time inference on the robot, data flowing between both, is the compute orchestration challenge that scales with every character you deploy. It's the problem #NuNet is solving: a protocol that coordinates workloads across heterogeneous infrastructure, from cloud GPUs to edge devices. The next wave of physical AI isn't bottlenecked by GPU power. It's bottlenecked by the infrastructure layer that ties it all together.
NVIDIA Robotics
@NVIDIARobotics
03-06
Ever wondered how Disney's characters make it from the screen to reality? 🎬 Behind the magic is physical AI: • Newton & Kamino: Leveraging the open-source, GPU-accelerated Newton framework and Disney’s Kamino solver for artist-centric reinforcement learning. • Expressive
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