One centralized data pipeline can't cover the world. 🔍
NATIX does it differently: Decentralized collection, global scale, every road, every market, every edge case.
Because the gap between AV demos and AV deployment is a data gap.
NATIX Network
3,351 posts
NATIX Network
@NATIXNetwork
The world’s largest camera infrastructure for mapping, autonomous driving, and physical AI. Join 260k+ drivers and earn rewards. Powered by @Solana.
Joined April 2022
- NATIX is at the center of some BIG moves in the autonomous driving world 🚗 From World Models to VLMs and End-to-End models, data is the key that binds them together. It's only a matter of time before Physical AI takes over, and the ones building it are using NATIX data 💪
00:00 - The city-by-city playbook made sense in 2016. ⚡️ It doesn't anymore. Autonomous systems need edge cases from all over the world, not just one city at a time.
- The data collected for Physical AI training is important, but is it also important who collects that data?
- Our May Progress Update dropped: 📹>176K Hours of Multi-Camera Footage 💹>6.78B $NATIX Staked 💎VX360 HODL Clubs launched 📺How video turns into intelligence 🌐Physical AI's geography problem Full recap👇 natix.network/blog/natix-net…
- Raw footage is only the starting point. NATIX turns real-world visual data into structured spatial intelligence by extracting road signs, lane markings, road geometry, and infrastructure assets at scale. This is how roads become machine-readable. 🌎
00:00 - If an AV can drive in New York, it doesn't necessarily know how to drive in Tokyo. Different roads mean different driving behaviors. 🛣️ The only way to bridge that gap before sending autonomous cars into the real world is to have enough training data.
- Heads up Drive& users, June 30th is coming fast 👀 That's your last day to withdraw and qualify for the staking campaign. Stake your $NATIX and earn up to 15% bonus on top of standard APY. Make sure not to miss it 👇
- One view is never the full scene. VX360 captures the road from multiple angles at once. More context means stronger real-world data for Physical AI. 👀
- Replying to @NATIXNetwork4/ This is where NATIX comes in. Our decentralized camera network captures real-world driving data across countries, climates, and driving cultures. That is how Physical AI gets the geographic coverage it needs to scale. 🌎
- Replying to @NATIXNetwork3/ Nowadays, AV systems are deployed city-by-city, but this kind of autonomy does not scale. Every new market means new roads, edge cases, maps, and tuning. 🚗 The future needs a data layer that can teach a vehicle how to drive in a different geography before it gets there.
- Replying to @NATIXNetwork2/ A model that feels confident in Phoenix may struggle in Mumbai, Bangkok, or Berlin. The long tail is local, and safety depends on seeing what actually happens there. 👀 That's what makes data diversity the key to unlocking new regions for autonomous driving. 🔑
- Autonomous driving is not just an algorithm race. It is a geography problem. 🌎 Roads, signs, weather, and driving culture change everywhere. That is why global data coverage matters 👇
