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No physics libraries? No raycasts? That's right! The track is a spline that lets us easily figure out the normals and tangents at any given point on the curve. This makes collision and twisting tracks simple and super performant. Reply if you want an in-depth break down 😃

Daniel Beauchamp

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39,683 views • 1 year ago •via X (Twitter)

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At any point on a curve, there's one circle that fits the curve better than any other. It touches the curve at that point, leans in the same direction, and bends by the same amount. It tells you how sharply the curve is bending at that exact spot, and which way it's leaning. If the curve is bending sharply, the circle is small. If the curve is nearly straight, the circle is huge. The osculating circle of the curve.

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China just dropped an open source model that turns any phone into a 3D scanner you point it at a room and walk through it the whole space builds itself into a 3D point cloud in real time as the camera moves, no LiDAR and no depth sensor anywhere it held a full 13 minute walkthrough at 25,000 frames without the map drifting or collapsing > ~20 fps on a single GPU > works indoors and outdoors from plain footage > the scan normally needs a $50,000 rig and a technician > Apache 2.0 and runs fully offline on your machine repo in the reply

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In 2022, Carlos Alcaraz hit an unreturned serve out wide on match point to claim the US Open title and the world No.1 ranking. In 2025, Carlos Alcaraz hit an unreturned serve out wide on match point to reclaim the US Open title and the world No.1 ranking.

In 2022, Carlos Alcaraz hit an unreturned serve out wide on match point to claim the US Open title and the world No.1 ranking. In 2025, Carlos Alcaraz hit an unreturned serve out wide on match point to reclaim the US Open title and the world No.1 ranking.

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Steal this idea: An app that lets you chat with the owners of any other vehicle out there. Someone is not giving you side and driving in an overtaking lane? You can simple enter his car number in the app and ping the driver small pre designed sentences like - hatt ja bhai.

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Chirag Barjatya

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I'll always root for a team that open-sources its best work, and Robbyant just did it properly. Robbyant, Ant Group's embodied-AI company, released LingBot-Vision, a vision foundation model for robots, and the part I love is the data. They trained it on 161M images, filtered down from 2B raw ones and mostly pulled straight from the open web, with no human labels, no edge detectors, no depth sensors anywhere in the loop. It learns the exact edges of objects from raw pixels. That's roughly a tenth of the data DINOv3 saw, and under a third of the training. And it shows in the results. On depth, working out how far away things are, the 1B model edges out a 7B on NYU-Depth. It also powers LingBot-Depth 2.0, which reads the surfaces cameras usually choke on, glass and mirrors, and halves indoor depth error. LingBot-Vision is fully open. Weights from the 1.1B flagship down to a tiny 21M version, code, and the paper. This is the timeline I want more of. Robbyant

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The Fondant Custom Normals Blender addon is being tested, and we're aiming for a 1.0 release next week! The first feature is the Weighted Normals + Laplacian Smoothing Geometry Nodes modifier. This let's you calculate Normals that are as clean as a nice quad mesh even if your topology is a mess and triangulated! We'll be following up with more tools to support creating high quality Normals for 3D anime and vtuber characters. We have an optimized adjustable Face Normal Transfer proxy mesh nearly ready to go. Check out the Docs to see more about the Addon's features and workflow (link in the reply.)

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"Mr. Simpson, look at this lineup and tell us if any of these are the aliens you saw..." "Yo!" "No, I'm sorry." "Oh, this makes me very angry!"

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starting to roll out this little gesture on threads that lets you hold down on a subject anywhere in an image to segment it and attach it to your reply (powered by sam!)

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