Viewing profile — b89kim

I had no failure mode in 3.6 9B thinking with llama.cpp. After release, there were updates for both model and llama.cpp.

If you're using depth, you're better off starting with a diffusion policy (DP). We benchmarked ACT, DP, pi0,pi05 on the same task, ACT underperformed in most cases. There is alread…

Adding a depth channel rarely yields a massive performance gain, likely due to data scarcity and the fact that modern VLAs are good at guessing distance directly from RGB. I have u…

- A single arm is sufficient for validating basic Pick/Place tasks, but more complex scenarios require Bi-arm - Calibration is not required for VLA models. - RGB or Stereo RGB inpu…

I could confirm 50-100 demonstrations are enough for fine-tuning pi0/pi05. I did research with aloha and humanoid. It works from 20~40ep(5~10min) but success rate would be 70~80%. …

The Raspberry Pi is a single-board computer with native support for UART, SPI, I2C, CSI, and more. There's a large ecosystem of HATs, sensors, and peripherals built specifically fo…

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ChatGPT's Canvas uses Pyodide for sandboxing, but it's not designed for coding agents. Node.js environment is usually better for agents. Pyodide restricts server-side functionality…

I’ve been testing these on other tasks—IK, Kalman filters, and UI/DB boilerplate. Qwen3.5 is multimodal and specialized for js/webdev or agentic coding. It’s not surprising MoE mod…

I’ve been benchmarking GGUF quants for Python tasks under some hardware configs. - 4090 : 27b-q4_k_m - A100: 27b-q6_k - 3*A100: 122b-a10b-q6_k_L Using the Qwen team's "thinking" pr…