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NEW AI CUSTOMER BUYS 3,000 HOURS OF NATIX DRIVING DATA 🚗
We've signed a six-figure deal with an AI lab pioneering general world models. Real demand for DePIN on @solana.
Not a research collab. Not a free dataset. A paying customer.
We've signed a six-figure deal with an AI lab pioneering general world models. Real demand for DePIN on @solana.
Not a research collab. Not a free dataset. A paying customer.
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Tesla's new robotaxi safety page counts 3.1M autonomous miles 🚕
The split says more than the total: 862K after dark, 113K in rain, 575K in rush hour.
Miles only count for the conditions they cover. Night, rain and traffic are where driving data earns its keep 🌧️
The split says more than the total: 862K after dark, 113K in rain, 575K in rush hour.
Miles only count for the conditions they cover. Night, rain and traffic are where driving data earns its keep 🌧️
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KITTI came out in 2012 and gave self-driving research its first shared benchmark 🏁
BDD100K, nuScenes and Waymo Open followed. Today's world models need more than they were built for: recent multi-camera video from many places.
What they taught us 👇
natix.network/blog/open-driv…
BDD100K, nuScenes and Waymo Open followed. Today's world models need more than they were built for: recent multi-camera video from many places.
What they taught us 👇
natix.network/blog/open-driv…
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DePIN taught crypto to crowdsource maps, WiFi and compute.
DePAI points the same idea at physical AI: everyday people collect the real-world data robots and self-driving cars learn from, and get rewarded for it.
NATIX drivers do it with the cameras built into their Teslas.
DePAI points the same idea at physical AI: everyday people collect the real-world data robots and self-driving cars learn from, and get rewarded for it.
NATIX drivers do it with the cameras built into their Teslas.
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Goldman Sachs puts general-purpose robots about where self-driving was in 2017 or 2018 🦾
Its estimate: they’ll need around 10 million hours of high-quality physical interaction data.
Self-driving learned this first. The models got good once the real-world data caught up.
Its estimate: they’ll need around 10 million hours of high-quality physical interaction data.
Self-driving learned this first. The models got good once the real-world data caught up.
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October was the month demand showed up 📈
A 3,000 hours data sale to a world model lab, over 931M $NATIX burned in total, and the VX360 Desktop App open beta live in the U.S.
Our October recap is here 👇
natix.network/blog/progress-…
A 3,000 hours data sale to a world model lab, over 931M $NATIX burned in total, and the VX360 Desktop App open beta live in the U.S.
Our October recap is here 👇
natix.network/blog/progress-…
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The real line between ADAS and L4 is not capability. It is who catches the mistake when the model is wrong.
Answer that and the training data question mostly answers itself.
Full breakdown on coverage, labels and edge cases 👇
natix.network/blog/adas-data…
Answer that and the training data question mostly answers itself.
Full breakdown on coverage, labels and edge cases 👇
natix.network/blog/adas-data…
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More world models, more demand for real driving data 📈
This week Rivian bought Third Dimension to turn real footage into 3D worlds, and Baidu is about to reveal its own world model.
Whoever builds the model needs the footage. NATIX has over 200,000 hours of it.
This week Rivian bought Third Dimension to turn real footage into 3D worlds, and Baidu is about to reveal its own world model.
Whoever builds the model needs the footage. NATIX has over 200,000 hours of it.
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Autonomous driving shouldn’t be locked inside a few companies 🔓
The Autoware Foundation builds open-source self-driving software, backed by members like AMD, AWS and Arm.
As a Premium member, NATIX supplies multi-camera data for Autoware’s open-source end-to-end model 🤝
The Autoware Foundation builds open-source self-driving software, backed by members like AMD, AWS and Arm.
As a Premium member, NATIX supplies multi-camera data for Autoware’s open-source end-to-end model 🤝
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Over 200,000 hours of driving footage, and none of it came from a test fleet 🚗
It was recorded by drivers in the NATIX network, on their everyday routes.
That’s the network behind every dataset, partnership and world model NATIX powers 🌍
It was recorded by drivers in the NATIX network, on their everyday routes.
That’s the network behind every dataset, partnership and world model NATIX powers 🌍
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Video shows what happened. Telemetry shows what the driver did.
Our Safety-Critical Driving Events Dataset has both: GPS, wheel angle, pedals and brake state, 45 events in ten U.S. states 🛑
Working on ADAS or world models? It’s on Hugging Face.
huggingface.co/datasets/natix…
Our Safety-Critical Driving Events Dataset has both: GPS, wheel angle, pedals and brake state, 45 events in ten U.S. states 🛑
Working on ADAS or world models? It’s on Hugging Face.
huggingface.co/datasets/natix…
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More data from the same city won't teach a model how another city drives.
Two quick headlight flashes mean thanks in Hungary and a warning in Italy. Same signal, opposite meaning 💡
Why validation data has to come from roads a model has never seen 👇
natix.network/blog/autonomou…
Two quick headlight flashes mean thanks in Hungary and a warning in Italy. Same signal, opposite meaning 💡
Why validation data has to come from roads a model has never seen 👇
natix.network/blog/autonomou…
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Driving video is just storage cost until you can find the moment you need.
With VLMs, NATIX can search its multi-camera data in plain language: describe a scene and get the matching clips.
Hours of manual review become a query that takes seconds 🔍
With VLMs, NATIX can search its multi-camera data in plain language: describe a scene and get the matching clips.
Hours of manual review become a query that takes seconds 🔍
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World Foundation Models learn the world from video 🌎
But if the footage only looks forward, the model only understands what’s ahead.
Autonomous systems need the full scene. That’s why NATIX builds on real-world multi-camera footage, not just a front view 👀
But if the footage only looks forward, the model only understands what’s ahead.
Autonomous systems need the full scene. That’s why NATIX builds on real-world multi-camera footage, not just a front view 👀
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Models are getting cheaper. Compute is getting easier to buy.
Real-world data is still the bottleneck 🔍
Robots and autonomous systems need the long tail of real roads, seen from every angle. NATIX captures it at scale with multi-camera footage from drivers worldwide 🚗🌎
Real-world data is still the bottleneck 🔍
Robots and autonomous systems need the long tail of real roads, seen from every angle. NATIX captures it at scale with multi-camera footage from drivers worldwide 🚗🌎
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Physical AI labs are paying for the one thing they can’t generate: real-world data 🌎
That’s what NATIX has been building, one car camera at a time 🚗
And as @AlirezaGhods2 hinted, something is cooking 👀
That’s what NATIX has been building, one car camera at a time 🚗
And as @AlirezaGhods2 hinted, something is cooking 👀
crypto data businesses might be one of the biggest opportunities right now.
microagi just went from 0 to $100M ARR in 6 months, the fastest revenue ramp on this entire chart, beating OpenAI, Cursor, Higgsfield and everyone else.
interestingly the engine behind this was Shift, ecting real world data to train robots and physical AI.
let that sink in for a second.
the demand for high quality real world data is so insane right now that a data business can outscale the fastest growing AI frontier and the fastest scaling software companies in history.
this is exactly why I keep saying the most overlooked opportunities in crypto are the former DePINs that quietly turned into exactly these kinds of data businesses.
@silencioNetwork, @NATIXNetwork and @OVRtheReality are sitting in the exact same category, sitting at ridiculous valuations given that no one is paying attention to them.
massive opportunity in there for those who are connecting the dots.
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A better model alone won’t get autonomy to scale 🚗
It also needs rare road cases to learn from, every camera angle to see the full scene, and real-world footage to test and validate against.
That’s the golden trio. NATIX’s multi-camera data covers all three 🔍
It also needs rare road cases to learn from, every camera angle to see the full scene, and real-world footage to test and validate against.
That’s the golden trio. NATIX’s multi-camera data covers all three 🔍
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Real data. Real revenue. Real burns 🔥
Drivers collect multi-camera footage, AI teams buy it, and every sale becomes protocol revenue that buys back $NATIX and burns it.
The more Physical AI needs real-world data, the more this loop runs 🌎
Drivers collect multi-camera footage, AI teams buy it, and every sale becomes protocol revenue that buys back $NATIX and burns it.
The more Physical AI needs real-world data, the more this loop runs 🌎
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World Models simulate reality, but if you feed them nothing but internet data, how much reality are you actually capturing?
Real-world multi-camera driving data is the key to unlocking the next generation of autonomous systems. 🗝️
That's how autonomy scales 📈
Real-world multi-camera driving data is the key to unlocking the next generation of autonomous systems. 🗝️
That's how autonomy scales 📈
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Most World Models today are built on front-facing driving videos. ➡️
But reality comes at us from all sides. That's why multi-camera video data is extremely valuable for autonomous driving simulations. 🔁
That's the data NATIX offers 📹
But reality comes at us from all sides. That's why multi-camera video data is extremely valuable for autonomous driving simulations. 🔁
That's the data NATIX offers 📹
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Missed our latest token burn? We've got you covered 😉
224,971,878 $NATIX burned across Q2 and Q3 🔥
Our drivers collect data. Companies pay for it.
Real demand = Value accrual to the token.
Over 931M tokens were already permanently removed from the supply in total 💪
224,971,878 $NATIX burned across Q2 and Q3 🔥
Our drivers collect data. Companies pay for it.
Real demand = Value accrual to the token.
Over 931M tokens were already permanently removed from the supply in total 💪
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