Skild AI ✓
@SkildAI · USA · joined 01 Jun 2023
Building general purpose robotic intelligence.
22 914Followers
0Following
279Posts total
8.2MViews on collected posts
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กำลังค้นหาโพสต์ใหม่…
@SkildAI Apparently the robot is more robust than I am now.😂 btw this still hurts @hellokillian https://t.co/CzUTZLMxMx
10.9K views · 39 likes
· 1 reposts · 2 replies
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0:07
AlphaGo taught us that self-play can lead to emergent, superhuman behavior.
We're bringing it to the physical world: https://t.co/3Vpn5Fqjj8
121.3K views · 219 likes
· 46 reposts · 0 replies
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Once it was ready, we brought it to life. https://t.co/aqviMtabFv
111.8K views · 218 likes
· 46 reposts · 2 replies
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0:38
It was born in a physics simulation.
For 140 years, our model played against increasingly tough opponents, each one a previous version of itself. https://t.co/nmn3B46L3J
120.3K views · 316 likes
· 51 reposts · 13 replies
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0:15
We trained a robot to play football.
How? Self-play for 140 years in a virtual World Cup.
Meet the #Messinator: https://t.co/WJNkb2mfoI
1.6M views · 1.9K likes
· 417 reposts · 207 replies
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0:52
@SkildAI this is kind of unreal, a robotics foundation model hitting $100M ARR in 10 months.
Physical AI is is coming in a big way.
3.6K views · 25 likes
· 0 reposts · 1 replies
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Why it matters:
https://t.co/aWxcUO786o
249.5K views · 585 likes
· 56 reposts · 3 replies
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@SkildAI Ofc I would try a food robot that learns a new dish from one video. I just wouldn't put it on a line until the same plate comes out the same way all week.
36 views · 0 likes
· 0 reposts · 0 replies
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@SkildAI Not only I loved the video (I wished more launches will have this type of vibe)…the learning tasks never seen during pretraining is so cool
6.7K views · 42 likes
· 1 reposts · 1 replies
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Last year, we showed in-context learning for the first time for mobility.
Locoformer can control any robot, and adapt to disturbances like disabled legs, locked wheels and more.
S1 expands that capability to general manipulation.
https://t.co/wdpmi8gXYE
319.7K views · 277 likes
· 22 reposts · 3 replies
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We're excited to deploy S1 with our limited industrial partners today, rolling out to more customers over the next few months.
S1 is the first light on a new path towards general intelligence grounded in the physical world.
Technical blog: https://t.co/tx5ohKimhQ
324.1K views · 306 likes
· 30 reposts · 7 replies
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We found that to match the accuracy that S1 can achieve with just one example of prompting, current VLA models would need to be post-trained with 50-100 hours of data collection followed by fine-tuning! https://t.co/W8wGv63ssD
295.8K views · 282 likes
· 23 reposts · 1 replies
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0:21
S1 does not blindly replay the video demonstration.
Instead, it displays common-sense understanding that goes beyond the video prompt:
- can withstand perturbations
- improvise upon mistakes, even if the human didn’t
- at times execute with more precision than the human in the
300.2K views · 308 likes
· 25 reposts · 2 replies
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0:53
Compared to conventional VLAs, S1 is a step-change improvement.
For known tasks, S1 can match the performance of language-prompted VLAs.
For novel tasks, S1 exponentially outperforms any existing language-prompted VLAs as we scale the pre-training.
We believe this is a https:/
302.6K views · 313 likes
· 26 reposts · 3 replies
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0:27
S1 learns new tasks like a language model.
You prompt it with a video demonstration, and it outputs robot actions to complete the task in any environment and in any embodiment. https://t.co/8ACELwodeA
308.9K views · 330 likes
· 29 reposts · 2 replies
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0:28
The first time S1 flipped a pancake, we assumed pancake flipping must have been in its pre-training data.
We searched our whole pre-training data and found no examples of flipping.
S1 inferred the out-of-distribution task from one video prompt. https://t.co/lPELYWmEFC
315.3K views · 408 likes
· 34 reposts · 4 replies
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0:33
It can be taught extremely long-horizon tasks, over 10 minutes long.
By composing skills learned in pretraining or creating new ones, it can make coffee, pot a plant, fry pancakes, and more – tasks never seen during pretraining. https://t.co/DhoqsJb33G
333.5K views · 469 likes
· 37 reposts · 3 replies
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0:40
Exciting news! 🎉 Our CEO & Co-founder, Deepak Pathak (@deepakpathak), received the PAMI Young Researcher Award at #CVPR2026 this week.
Among the highest honors in computer vision for early-career researchers, the award recognizes groundbreaking contributions that have a lasting
64.7K views · 203 likes
· 6 reposts · 10 replies
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We have acquired Zebra Technologies’ robotics arm (formerly Fetch Robotics).
This is what happens when orchestration meets intelligence -- a major step toward fully autonomous warehouses.
More robots. More environments. One unified brain. https://t.co/16DgX6T0ic
83.8K views · 317 likes
· 47 reposts · 9 replies
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Nearly every system today, from energy to chips to food, is bottlenecked by scarce human capital.
We are changing that by building AI-powered industries of the future.
Check out Skild Brain robustly assembling GPU racks, a highly precise task, live at #NvidiaGTC. https://t.co/
285.4K views · 308 likes
· 65 reposts · 24 replies
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Robotics is a data problem.
Today, we’re partnering with @ABBRobotics, @Universal_Robot, and @NVIDIARobotics to deploy the Skild Brain across real-world industries from manufacturing to factory lines.
This will help us build the world’s biggest data flywheel for physical AI. ht
258.1K views · 723 likes
· 87 reposts · 19 replies
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@SkildAI Ok these robot torture videos are going a little far
11.1K views · 414 likes
· 1 reposts · 4 replies
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Blog → https://t.co/NtTeCvUCJ7
Careers → https://t.co/ZonwGiy23L
Follow @SkildAI for updates.
https://t.co/wdpmi8gXYE
31.5K views · 98 likes
· 1 reposts · 2 replies
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Imagine Mars rovers that can adapt to broken wheels.
Submersibles that can finish critical repairs with faulty thrusters.
A rescue robot with crushed legs that can keep saving lives. https://t.co/BDen243bxE
30.6K views · 285 likes
· 10 reposts · 4 replies
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With its extremely long memory, the Brain can learn from failure.
This has far-reaching implications for robotics and beyond— https://t.co/YyOaL4CRa8
23.8K views · 203 likes
· 7 reposts · 5 replies
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The Skild Brain has an extraordinary memory.
Most robot control policies have a few hundred milliseconds of memory, specialized for only one robot.
Our context window is over 100x longer. https://t.co/2ZbiELKwde
30.1K views · 183 likes
· 4 reposts · 2 replies
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What makes it so resilient? It's "omni-bodied".
The Skild Brain spent 1,000 years walking 100,000 different bodies across simulated worlds.
In our world, the Brain treats a broken robot as just another body. https://t.co/xmYyEeF255
68.5K views · 496 likes
· 32 reposts · 11 replies
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Chainsaw vs. Robot. https://t.co/UJy709wxRH
45.9K views · 206 likes
· 9 reposts · 9 replies
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The Skild Brain can control any machine that walks or rolls.
Watch it inhabit a robot dog that's stood up on two legs.
Being zero-shot, it thinks it's in a humanoid body, so it walks like one: https://t.co/PopIonVcqA
43.8K views · 296 likes
· 8 reposts · 5 replies
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We built a robot brain that nothing can stop.
Shattered limbs? Jammed motors? If the bot can move, the Brain will move it— even if it’s an entirely new robot body.
Meet the omni-bodied Skild Brain: https://t.co/DkFXhq3ZbF
2.4M views · 6.7K likes
· 856 reposts · 502 replies
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1:33
เทียบกับบัญชีขนาดเดียวกัน
17 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง 10K–100K ผู้ติดตาม แสดงในวงกว้าง แต่มีผู้ชมตอบสนองน้อย.
ยอดดูมัธยฐาน295 819บัญชีนี้924ค่ามัธยฐานของ 10K–100K
การเข้าถึง, %1291.00%บัญชีนี้3.62%ค่ามัธยฐานของ 10K–100K
การมีส่วนร่วม, %0.15%บัญชีนี้1.52%ค่ามัธยฐานของ 10K–100K
| ตัวชี้วัด | บัญชีนี้ | ค่ามัธยฐานของ 10K–100K | อัตราส่วน |
|---|---|---|---|
| ยอดดูมัธยฐานต่อโพสต์ | 295 819 | 924 | 320× |
| การเข้าถึง (ยอดดู ÷ ผู้ติดตาม) | 12.9× audience | 3.62% | 357× |
| อัตราการมีส่วนร่วม | 0.15% | 1.52% | 0.10× |
บัญชีอื่นในช่วงนี้ → เปรียบเทียบกับบัญชีอื่น → ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →
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
302.6K25 Aug
300.2K
295.8K
324.1K
319.7K
6.7K
3626 Aug
249.5K10 Sep
3.6K
1.6M23 Sep
120.3K
111.8K
121.3K
10.9K
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
0.11%25 Aug
0.11%
0.10%
0.11%
0.09%
0.66%
0.00%26 Aug
0.26%10 Sep
0.72%
0.17%23 Sep
0.32%
0.24%
0.22%
0.40%
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes59.9%16 455 in total
Reposts7.2%1 977 in total
Replies3.1%860 in total
Quotes5.1%1 389 in total
Bookmarks24.8%6 812 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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