NATIX Network

World Foundation Models (WFM) are the future of Physical AI, and we believe this future should be open-sourced. We are partnering with @Valeo_Group to build one of the largest open-source, multi-camera WFMs — redefining how Physical AI interacts with the real world.

The long tail is where autonomy is won or lost. 👀 Most AV datasets are built on clean, common driving. But rare events, edge cases, and unexpected behavior are what actually define safety. That is the data NATIX is built to find. 🔍

► TAO's Subnets For The Robotics Era everyone on CT is talking about $TAO but almost nobody is paying attention to the part of the TAO eco that actually touches the physical world. that's the TAO subnets shipping the robotics era. I've named them here 👇🏻 1/ @kinitroai | SN26: generalist robot policy training researchers compete to submit policies evaluated across arm manipulation and Unitree G1 humanoid locomotion. only policies that generalize across all environments earn emissions, specialists get penalized. 2/ @SwarmSubnet | SN124: autonomous drone flight miners submit RL policies, validators test in physics simulator. completed first autonomous mountain drone flight 100 days post-launch. goal: 10,000 drones deployed. 3/ @NATIXNetwork | SN72: real-world perception data for physical AI. ingests street imagery from smartphones + dashcams, miners train detection models, best models feed back into NATIX's live edge network. backed by Yuma (DCG). 4/ @Loosh_ai | SN78: cognitive layer for robots persistent memory, ethical judgment, emotional intelligence. EEG model hitting ~70% accuracy on emotional state prediction. Yuma Subnet Accelerator incubatee. 5/ @nepher_robotics | SN49: decentralized robotics-tournament subnet. Miners upload policies; validators run them in NVIDIA Isaac Lab sims. Winner-takes-all weight split. --- Subnets that supporting the #Robotic stack: 6/ @404gen_ | SN17: text-to-3D generation. 21.5M open-source 3D models on Hugging Face. feeds robot simulation + digital twin pipelines. 7/ ChipForge @TatsuEcosystem | SN84: decentralized chip design. building Edge AI accelerators + NPUs - the silicon profile robots actually need. most people sleep on this because robotics feels abstract and far away, but as I said, robotics is the next after #AI rally! the market hasn't priced this in yet.

NATIX Edge Case Spotlight 🛑 Physical AI doesn't just need to move. It needs to know when to wait. A vehicle blocking the lane. No special signal, just context. Extracted from our network via an advanced VLM. This is what the long tail is all about.

Collecting edge cases at scale is a 3-tiered problem. 💎Rarity: You can't schedule rare events. 📰Context: Front-facing video misses the full story. 🔍Discovery: Rare moments buried in hours of footage you can't manually review. NATIX's multi-camera network is the answer.

We use VLMs to extract real-world scenarios from video, focusing on edge cases and long tails ⚡ We turn them into structured formats that simulation tools can read and test 🧪 By capturing objects and trajectories, we recreate reality for training physical AI 🌍

Vision-Language-Action (VLA) models enable AI to interpret visual data, language and make informed decisions 🧠 They translate complex visual information into purposeful physical responses 💡 NATIX fuels VLAs with unparalleled real-world data for robust DePAI development 🌐

This February report shows that raw collection metrics have cooled, but the use-case layer is warming up. Our partnership with @NomadicML = multi-camera footage is processed for video data analysis at scale. That's how we make DePAI the perfect Physical AI infrastructure. 🌐

1/ @Solana DePIN protocols generated $2.4M in Feb 2026. Wireless protocols data offloading hit a new ATH at 37k TB, up 12% from Jan. @helium_mobile held revenue > $2M for a second straight month. @XNET_Mobile surpassed 100TB of offload for the first time. Full breakdown 🧵👇

If you think we haven't achieved full autonomy because we need to build better models, you’re missing the real bottleneck. Edge cases and the long tail are what separate demos from real-world reliability. In this piece, CEO @AlirezaGhods2 breaks it down 👇

Real-world AI is not limited by data alone but by the lack of true perspective 🌍 NATIX captures multi-camera, multi-angle data, creating a richer view of the physical world 🧠 That kind of capability is what made this collaboration a natural fit for MaprGo 🚀

Which Physical AI breakthrough are you most excited to see NATIX power? 🤖🌐

Multi-camera video data is transforming how Physical AI systems understand the real world 🌐 Dive into this AI-generated podcast to find out what makes video data, via VLMs, WFMs, VLAs, and End-to-End driving systems, push autonomous driving to a brighter future 🚗

Traditional AI is limited by centralized data silos lacking real world diversity 🌐 NATIX is changing that with DePAI, where users contribute to AI training 🧠 Result: smarter systems trained on diverse, real-time data from the ground up 🛣️

⌛️We're starting our special broadcast with MaprGo in 3 hours!!⌛️ Make sure not to miss it ⬇️

What do NATIX and Pokémon Go have in common? The power of DePIN Pokémon Go was really ahead of its time, but can it be considered the father of all DePINs?

Tesla drivers in Switzerland 🇨🇭 Help build the future of autonomous driving. Free VX360 + earn while you drive. Limited spots! Comment below if you’re in or DM me.

Imagine driving once, and every street sign, stop light, and lane marking turns into valuable intelligence. This is not a dream. Spatial AI tools do exactly that with our multi-camera footage! 🎥 This level of detail supports autonomy development and Physical AI research. 🚗

Great news! 🎆 In this special broadcast, CEO @AlirezaGhods2 will be joined by @MaprGo CEO @NareshShetty46🙌 📅March 19 | 4:30 PM CET 📅 You don't want to miss this one 👇 x.com/i/broadcasts/1…

📢IMPORTANT UPDATE 📢 The special broadcast event scheduled for today is postponed to a later date, as we have a special surprise for it. More information will be shared soon 🙌

Physical AI development currently faces a major bottleneck due to data scarcity 📉 VX360 leverages Tesla's cameras and DePIN to crowdsource critical 360° imagery 🚗 This approach provides the essential, continuously updated datasets Physical AI needs ✨