Sunil Kumar Pradhan

126 posts

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Sunil Kumar Pradhan

Sunil Kumar Pradhan

@SunilINTJ

Python Developer INTJ-A | I go to gym , I like to code (ofc with AI assistance) , I love Photography / Robotics .

Hyderabad Katılım Ocak 2024
181 Takip Edilen30 Takipçiler
Sunil Kumar Pradhan
Sunil Kumar Pradhan@SunilINTJ·
If your strength is not increasing… It’s rarely your training program. It’s usually: • Low total protein • Poor distribution • Long gaps without feeding
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Sunil Kumar Pradhan
Sunil Kumar Pradhan@SunilINTJ·
What works better: 25g post workout : Dope !! 25g mid morning : Dope !! 25–30g lunch : Dope !! 20–25g evening/dinner : Dope !! 4–5 protein spikes = 4–5 growth signals. Better MPS
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Sunil Kumar Pradhan
Sunil Kumar Pradhan@SunilINTJ·
Most people think muscle growth is about total daily protein. It’s not. It’s about protein distribution. You don’t build muscle by dumping 100g at night. You build it by triggering growth multiple times a day. Checkout the thread : 🧵
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Sunil Kumar Pradhan
Sunil Kumar Pradhan@SunilINTJ·
Broadcasting is the mechanism that allows element-wise operations on arrays of different shapes by "stretching" the smaller array to match the larger one. #ML #NumPy Refer this :
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Firebase
Firebase@Firebase·
Meet Firebase Studio: A cloud-based, agentic dev environment powered by Gemini ✨💻✨ Find everything you need to prototype, build, and run production-quality full-stack AI apps quickly and safely. Learn more about building AI apps with Firebase → goo.gle/4j3MS9v #GoogleCloudNext
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dr. jack morris
dr. jack morris@jxmnop·
this guy invented VLLM. he's basically the john wick of CUDA kernels
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Marko Denic
Marko Denic@denicmarko·
Quickly and easily create a CSS Grid layout for your website!
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Marcel
Marcel@marcelkargul·
Reply with your website and I'll rate it.
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hal
hal@HAL09999·
∭ 𝘢(𝘵) ∝ eᴴᵗ
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Bilawal Sidhu
Bilawal Sidhu@bilawalsidhu·
Wow. Recreating the Shawshank Redemption prison in 3D from a single video, in real time (!) Just read the MASt3R-SLAM paper and it's pretty neat. These folks basically built a real-time dense SLAM system on top of MASt3R, which is a transformer-based neural network that can do 3d reconstruction and localization from uncalibrated image pairs. The cool part is they don't need a fixed camera model -- it just works with arbitrary cameras -- think different focal lengths, sensor sizes, even handling zooming in video (FMV drone video anyone?!). If you've done photogrammetry or played with NeRFs you know that is a HUGE deal. They've solved some tricky problems like efficient point matching and tracking, plus they've figured out how to fuse point clouds and handle loop closures in real-time. Their system runs at about 15 FPS on a 4090 and produces both camera poses and dense geometry. When they know the camera calibration, they get SOTA results across several benchmarks, but even without calibration, they still perform well. What's interesting is the approach -- most recent SLAM work has built on DROID-SLAM's architecture, but these folks went a different direction by leveraging a strong 3D reconstruction prior. Seems to give them more coherent geometry, which makes sense since that's what MASt3R was designed for. For anyone who cares about monocular SLAM and 3D reconstruction, this feels like a significant step toward plug-and-play dense SLAM without calibration headaches -- perfect for drones, robots, AR/VR -- the works!
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Tom Dörr
Tom Dörr@tom_doerr·
Network IP scanner with web interface
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GitHub Projects Community
GitHub Projects Community@GithubProjects·
Open-source push notifications system across devices
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