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NATIX Network

@NATIXNetwork · joined 20 Apr 2022

The world’s largest camera infrastructure for mapping, autonomous driving, and physical AI. Powered by @Solana.

136 968Followers
122Following
3 405Posts total
57KViews on collected posts

Postingan terbaru

Hand-built simulations teach a vehicle how to drive according to pre-written laws. World Models teach autonomous driving how to analyze, anticipate, and react. This is how autonomy scales 📈 https://t.co/gpHLsNDbxK
4.3K views · 39 likes · 8 reposts · 0 replies Open on X →
@NATIXNetwork Nice work! Are we working on listings as well? 45 views · 0 likes · 0 reposts · 0 replies Open on X →
@NATIXNetwork How many tokens did we burn 65 views · 0 likes · 0 reposts · 0 replies Open on X →
August Progress Update is here: 📹>196K Hours of Multi-Camera Footage 💹>8.4B $NATIX Staked 🤖How autonomous driving data helps robotics 🔄The difference between a dataset and a data engine Full recap👇 https://t.co/TIHcHXPAOl https://t.co/otZoSAMtFZ
4.9K views · 56 likes · 14 reposts · 2 replies Open on X →
@NATIXNetwork @Valeo_Group I’m curious how VATIX performs in real driving scenarios 57 views · 2 likes · 0 reposts · 0 replies Open on X →
9/ 5,500 hours of community-collected driving data helped push open-source driving video generation to new heights. This is what Decentralized Physical AI can make possible. 💪 Explore VATIX and the results 👇 https://t.co/eMABLMGjvr https://t.co/ioVVsqXtzL
309 views · 7 likes · 3 reposts · 0 replies Open on X →
8/ VATIX 9B is the largest open-source video diffusion model trained from scratch on driving data. It sets a new open-source benchmark for driving video generation. ⚡️ This is the first result from our broader work with Valeo, with a wider multi-camera WFM still ahead. 315 views · 6 likes · 0 reposts · 1 replies Open on X →
6/ The final model, VATIX 9B, learned its entire understanding of driving from NATIX footage. 🚗 And how did it do? It smashed the competition! VATIX 9B delivered over 60% better image quality and nearly 70% better video-consistency scores than its open-source competitors. https
153 views · 8 likes · 0 reposts · 1 replies Open on X →
7/ The biggest surprise? The NATIX dataset still had more to give. Even after 200+ experiments, performance kept improving as more footage was used. No clear plateau was reached. 5,500 hours pushed the open state of the art, but the ceiling is higher. 🌎 136 views · 5 likes · 0 reposts · 1 replies Open on X →
5/ Those scaling laws were then used to predict how a 9B-parameter model would perform before training it. The prediction landed within 3.6% of the final result, showing that large models can be planned far more efficiently. 🎯 That means less wasted funding and compute. 159 views · 6 likes · 0 reposts · 1 replies Open on X →
3/ Most driving world models are adapted from models already trained on web videos. Often, these models fail the reality check and break down after a couple of seconds. ❌ With 5,500 hours of driving footage provided by the NATIX Network, Valeo took a different approach. 286 views · 11 likes · 0 reposts · 1 replies Open on X →
4/ Valeo trained its world model, VATIX, from scratch using NATIX's driving data. They trained 200+ models to measure how data, model size, and compute affect performance. 📈 The results provided a breakthrough: predictable rules for how to build better driving world models. htt
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191 views · 8 likes · 0 reposts · 1 replies Open on X →
2/ What if AI could watch a few seconds of driving, then imagine what happens next? That's the promise of World Models. Video goes in. A simulated version of reality comes out. That's how autonomy scales. But it's a little more complicated than that. https://t.co/lj9ntdADw6
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521 views · 11 likes · 0 reposts · 1 replies Open on X →
How far can 5,500 hours of real-world driving data take you? All the way to VATIX, a new open-source, state-of-the-art world model for driving video generation. 🚗 The first major result from the NATIX × @Valeo_Group collaboration is here! https://t.co/gKldF0yg72
1:45
36K views · 209 likes · 19 reposts · 67 replies Open on X →
Most open-source data available for Physical AI teams is front-facing video footage. In reality, things come from all sides, not just from the front. That's what front-facing footage misses. ❌ NATIX datasets include multi-camera views, so autonomy can see everything🔄 https://t.
4.7K views · 50 likes · 8 reposts · 2 replies Open on X →
Data is a magic word that is used a lot, as if it can solve all the problems in the world. But data gets old, and the datasets that come with it are often out of date. A data engine keeps the data fresh and constantly updated. That's the NATIX way 💪 https://t.co/vgHLKTejbg
4.8K views · 43 likes · 12 reposts · 5 replies Open on X →

Dibandingkan akun berukuran sama

16 postingan dari 90 hari terakhir, dibandingkan dengan rentang 100K–1M pengikut. menjangkau lebih sedikit orang, tetapi melibatkan mereka jauh lebih kuat.

Median tayangan298akun ini6 277median untuk 100K–1M
Jangkauan, %0.22%akun ini1.78%median untuk 100K–1M
Interaksi, %2.26%akun ini1.12%median untuk 100K–1M
MetrikAkun iniMedian untuk 100K–1MRasio
Median tayangan per postingan2986 2770.05×
Jangkauan (tayangan ÷ pengikut)0.22%1.78%0.12×
Tingkat interaksi2.26%1.12%2.01×

Akun lain pada rentang ini →   Bandingkan dengan akun lain →   Bagaimana tolok ukur ini disusun →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

36K10 Sep
521
191
286
159
136
153
315
309
57
4.9K11 Sep
65
45
4.3K12 Sep

Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.82%10 Sep
2.30%
4.71%
4.20%
4.40%
4.41%
5.88%
2.22%
3.24%
3.51%
1.47%11 Sep
0.00%
0.00%
1.09%12 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.12%.

What the audience does

Likes75.0%461 in total
Reposts10.4%64 in total
Replies13.5%83 in total
Bookmarks1.1%7 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

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