@xizhao_fanclub: ✨ Hong Kong Concert Exclusive Every heartbeat captured, every embrace shared, these are the moments that stay with us forever. A special Hong Kong exclusive is on its way, bringing a little extra warmth before the 361 Heart Flutter Concert. We can't wait to see it in person! 🧡💛 #XiZhao #HeChangxi #HeYanzhao

XiZhao Official Fan Club
XiZhao Official Fan Club
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Region: US
Saturday 04 July 2026 11:39:59 GMT
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ace.0032
Ace032 :
The tension between this two is really something, they don't need to kiss just being physical touch and eye contact im already losing my shit. Their chemistry is off the chart
2026-07-04 11:59:58
25
hwyee0805
Wyee :
OMG !!!!!OMG!!!!!!!!! OMG!!!!!!
2026-07-04 11:47:57
12
reniutari6
🔮🍀 :
Mereka udah ada fm belum ya?
2026-07-05 05:30:55
0
screamzack
ชื่อ กิ๊ฟ นะคับ :
เริดเลยละ....🥰🥰
2026-07-04 12:33:55
2
perempuan1999
perempuan :
2026-07-04 17:13:30
2
puputpraba3
Sakura 🌸 :
Gak mungkin klo blm nikah ini mah😭 ini after party photo bgt 😭
2026-07-04 12:36:42
6
lostinskies96
Lostinskies :
That was my reaction cause I was not ready for it but I love it
2026-07-04 17:04:55
2
nguyt.thanh987
Nguyệt Thanh :
2026-07-04 12:04:27
1
xiao_alin.72
xiao alin :
Wao
2026-07-04 11:49:23
1
zarakmojoi3
bint e hawa :
omg what is this😂♥️♥️
2026-07-04 12:13:46
2
nekochaniee
narangiie :
😭😭😭😭 jirrrr udah gua ulang² 10kali
2026-07-04 22:23:05
0
tiarendom_
tiarendom :
wow
2026-07-04 11:50:49
0
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Other Videos

Why does a standard AI think an upside-down coffee mug is a completely new object? ☕️🙃
 
 Because standard neural networks don't understand physics. They just memorize raw (x, y, z) coordinates. And the second you move the camera, every single coordinate changes. 
 
 To fix this, engineers don't just feed the AI more data. They hardcode the mathematical laws of 3D space directly into the model's architecture. This is the foundation of **Geometric Deep Learning**.
 
 Swipe through the carousel to see how we translate the physical rules of reality into pure algebra using the Special Euclidean Group, SE(3). 👉
 
 🧠 **QUICK-WIN MNEMONIC:**
 Need a shortcut to remember the group theory of 3D space? Just remember **
Why does a standard AI think an upside-down coffee mug is a completely new object? ☕️🙃 Because standard neural networks don't understand physics. They just memorize raw (x, y, z) coordinates. And the second you move the camera, every single coordinate changes. To fix this, engineers don't just feed the AI more data. They hardcode the mathematical laws of 3D space directly into the model's architecture. This is the foundation of **Geometric Deep Learning**. Swipe through the carousel to see how we translate the physical rules of reality into pure algebra using the Special Euclidean Group, SE(3). 👉 🧠 **QUICK-WIN MNEMONIC:** Need a shortcut to remember the group theory of 3D space? Just remember **"The Spin and The Step"**: • **SO(3) = Just the Spin.** (Rotation only. The math guarantees no stretching and no mirror-reflections). • **SE(3) = The Spin + The Step.** (Rotation + Translation. But remember the physical twist: the Spin always acts upon the Step!). 📚 **THE DEEP DIVE:** The carousel gives you the visual intuition, but if you want to master the rigorous math—like the exact step-by-step proof of why $R^T R = I$ preserves inner products, or how computer graphics engines actually code the semidirect product ($\ltimes$) using $4 \times 4$ matrices—read today’s Substack article. 🔗 Link in bio! 👇 **QUESTION FOR YOU:** When you visualize a 3D scene, do you naturally think in "Active" transformations (the object physically moves) or "Passive" transformations (the object is still, but your camera moves)? Let me know in the comments! #GeometricDeepLearning #ComputerVision #LinearAlgebra #MachineLearning #MathNotes

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