bbr blynk @TeBlynk
Joined August 2023-
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bbr blynk retweeted
Raspberry Pi AI Kit。姿勢推定でもパフォーマンスがすごい。
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bbr blynk retweeted
久しぶりに動かしたけど、剛性の高い部品をいかに作るかが本当に課題。歩行ロボットに限ってはハードウェアの方に結構性能が依存する気がする。
bbr blynk retweeted
結線・プログラム完了 1st動作。。。
bbr blynk retweeted
障害物を克服し、起伏の多い地形を移動できる小型四脚ロボットの製作 youtu.be/KD4VsgM374M #mobile #robot #quadruped #wheeled #servos #LightRobotics
bbr blynk retweeted
学生たちが知恵と工夫、機械工学を駆使して作り上げた「綱渡りロボット」たち。中には生き物の動作を参考したものもある。(※若干古めの動画) youtu.be/pgtKwCLNf2Y #mechanical #science #engineering #robot #robotics #BioRob #biomimicry #バイオミミクリー #生物模倣 #IllinoisMechSE
bbr blynk retweeted
Working on some performance improvements for the phone. Running the simulation on a web worker so main thread & gpu can do the tracking.
bbr blynk retweeted
RX1 Humanoid: - Opensource full human scale dual arm robot - <$1,000 - Teleoperation and pick & place objects @_buildspace @_nightsweekends
bbr blynk retweeted
スケート 動作が怪しかったサーボを取り換え。 明日の展示も頑張るぞー。 @名古屋栄ナディアパーク
bbr blynk retweeted
💪RAG Me Up RAG Me Up is a generic framework (server + UIs) that enables you do to RAG on your own dataset easily. Its essence is a small and lightweight server and a couple of ways to run UIs to communicate with the server (or write your own). github.com/AI-Commandos/R…
bbr blynk retweeted
I just created a notebook using Llama 3.1 70B to generate a synthetic data for preference finetuning / aligning LLMs: github.com/rasbt/LLMs-fro… (The updated Llama license now allows using Llama 3.1 to improve other models, yay!). You can probably guess what comes next... 😊
bbr blynk retweeted
[Dot Product] by Hand ✍️ ~ I created a series of workbooks to help beginners learn the basic math of deep learning by hand. This is the first workbook in the series. Checkout the tutorial video made by Mohsena, my PhD student: by-hand.ai/v/w1 Download the PDF of the…
bbr blynk retweeted
ge-gnss-visibility GNSS satellite visibility simulation from Google Earth github.com/taroz/ge-gnss-…
bbr blynk retweeted
Want to run Llama 3.1 on a small number of chips, forget using up to 8 H100s or 512 LPUs, you just need a single Raspberry Pi 😁
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