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N8 Programs

@N8Programs9,863 subscribers

Studying Applied Mathematics and Statistics at @JohnsHopkins. Studying In-Context Learning at The Intelligence Amplification Lab.

Shorts

10,000 rigidbodies at 15-60FPS in Three.js (faster than Unity/Godot). How? Babylon.js's new physics system: havok - it works w/ any frontend, so below is a video of Babylon's havok powering physics in a three scene. Kudos to the whole Babylon team! #threejs #webgl #babylonjs

10,000 rigidbodies at 15-60FPS in Three.js (faster than Unity/Godot). How? Babylon.js's new physics system: havok - it works w/ any frontend, so below is a video of Babylon's havok powering physics in a three scene. Kudos to the whole Babylon team! #threejs #webgl #babylonjs

87,815 views

everyone's been sharing this 'bouncing ball visualization' and having AIs recreate it - so for a fun challenge, I recreated it without *any* AI assistance. ill break down the math behind the visualization - and what makes it challenging for AI - in this thread:

everyone's been sharing this 'bouncing ball visualization' and having AIs recreate it - so for a fun challenge, I recreated it without *any* AI assistance. ill break down the math behind the visualization - and what makes it challenging for AI - in this thread:

26,695 views

I am proud to announce that N8AO 1.7 is out - uses three.js r158, has transparency and stencil support, and more intuitive parameters for AO behavior (when updating, set your *distanceFalloff* to 1) Link: Github: #threejs #webgl #n8ao

I am proud to announce that N8AO 1.7 is out - uses three.js r158, has transparency and stencil support, and more intuitive parameters for AO behavior (when updating, set your *distanceFalloff* to 1) Link: Github: #threejs #webgl #n8ao

18,598 views

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