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NVIDIA Omniverse

@nvidiaomniverse · joined 31 Oct 2020

The official handle for #NVIDIAOmniverse. The platform for developing #OpenUSD applications for industrial digitalization and generative physical #AI.

26 423Followers
315Following
4 267Posts total
18.4KViews on collected posts

Latest posts

Your #NVIDIAGTC Berlin agenda could use some work. 👀 Don't worry, we have recommended hands-on trainings for you. Explore our lineup to build physical AI skills across NVIDIA Cosmos, visual AI agents, humanoid robot policies, and more. 👉 https://t.co/ql96IlaABe https://t.co/qH
0:16
940 views · 8 likes · 3 reposts · 4 replies Open on X →
@nvidiaomniverse @OpenAI The useful part isn’t the pretty scene. It’s that the scene is inspectable, editable, and runnable. That’s a digital world you can work in, not just look at. 63 views · 1 likes · 0 reposts · 0 replies Open on X →
NVIDIA developer Chirag Majithia turned stereo RGB captures into an editable USD scene. 👀 Using Astra, NVIDIA’s Omniverse, and Isaac libraries, he connected 3D reconstruction, scene authoring and Isaac Sim testing so developers can inspect, refine and test the scene. 🔗 https://
0:14
525 views · 13 likes · 2 reposts · 1 replies Open on X →
NVIDIA's Nic Johns brought the International Space Station into the browser. 🛰️ He used Astra to assemble 555 exterior meshes and seven interior modules from @NASA into an OpenUSD model connected to live telemetry. 🔗 https://t.co/r2zMd5OB64 https://t.co/YUpas9Px1x
434 views · 7 likes · 0 reposts · 0 replies Open on X →
What happens when you put Frontier AI agents to work with NVIDIA Omniverse libraries? Developers are using @OpenAI GPT-6 Astra to turn existing assets, captured spaces, and simple prompts into interactive, simulation-ready 3D experiences. 🔗 https://t.co/voBiQv0gkN Here’s what 6.5K views · 95 likes · 16 reposts · 16 replies Open on X →
@nvidiaomniverse Codex|OpenClaw|Hermes 14 views · 0 likes · 0 reposts · 0 replies Open on X →
@nvidiaomniverse The Blender-to-Isaac path is compelling. What catches a bad asset before simulation: physics checks, semantic labels, or the SimReady validation? 8 views · 0 likes · 0 reposts · 0 replies Open on X →
@nvidiaomniverse The durable pattern is model orchestration over simulation primitives: agents plan, while semantic labels, physics, sensors, and validation make the result executable and testable. 71 views · 0 likes · 0 reposts · 0 replies Open on X →
From Blender to Isaac Sim, fully agent-driven. 🦾 Codex orchestrates. NVIDIA NemoClaw coordinates. NVIDIA Omniverse Libraries do the work: semantic labels, physics, sensors, preflight renders, and SimReady validation. Read how we built it: https://t.co/DmssN9IXgN https://t.co/xB
5.3K views · 70 likes · 14 reposts · 4 replies Open on X →
Got a physical AI question? Skip the search bar. 👀 Connect one on one with NVIDIA experts at #NVIDIAGTC Berlin and get guidance on the technology behind your next build. Pick your next conversation: https://t.co/iUhvQ3X8FR https://t.co/MhlhkXEbXE
1.4K views · 34 likes · 4 reposts · 3 replies Open on X →
Build OpenUSD Worlds Using CAD and GPT-6 Astra https://t.co/nZmI5y3D7a 3.1K views · 55 likes · 10 reposts · 2 replies Open on X →

Against accounts of the same size

11 posts from the last 90 days, next to the 10K–100K follower range. reaches fewer people than peers of the same size.

Median views525this account1 015median for 10K–100K
Reach, %1.99%this account3.95%median for 10K–100K
Engagement, %1.68%this account1.54%median for 10K–100K
MetricThis accountMedian for 10K–100KRatio
Median views per post5251 0150.52×
Reach (views ÷ followers)1.99%3.95%0.50×
Engagement rate1.68%1.54%1.09×

Others in this range →   Compare with another account →   How these benchmarks are built →

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

3.1K16 Sep
1.4K
5.3K17 Sep
71
8
14
6.5K18 Sep
434
525
6319 Sep
94022 Sep

Last 11 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

2.16%16 Sep
2.94%
1.68%17 Sep
0.00%
0.00%
0.00%
1.97%18 Sep
1.84%
3.05%
1.59%19 Sep
1.60%22 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.54%.

What the audience does

Likes59.8%283 in total
Reposts10.4%49 in total
Replies6.3%30 in total
Quotes1.1%5 in total
Bookmarks22.4%106 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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