- llm
- inference
- on-device-ai
- reinforcement-learning
- robotics
- kernel
- ml
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The AI Coding Paradox: When Faster Code Makes Projects Slower
Why AI-generated code accelerates some teams and slows others — coding velocity vs. delivery velocity, the rise of AI slop, and a short field guide for using AI without losing the plot.
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Understanding Kernel Design from a Mathematical Perspective
Relating mathematical concepts — index notation, associative mergeable summaries — to GPU kernel design for ML inference, with case studies on fused operators and FlashAttention.
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Gated Delta Networks: Improving Mamba2 with the Delta Rule
A reading note on Yang et al., 2024 — how combining Mamba2's decay gate with DeltaNet's selective memory update yields a flexible recurrent model, and why its parallel training algorithm requires a matrix inverse.
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Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots
A reading note on Chi et al., 2024 — how a handheld gripper with a fisheye camera and mirrors enables hardware-agnostic demonstration collection anywhere, and what retargeting steps bridge the gap to a real robot.
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Diffusion Policy: Visuomotor Policy Learning via Action Diffusion
A reading note on Chi et al., 2023 — how DDPM-style denoising is applied to robot action generation, why it handles multimodal demonstrations better than explicit policies, and what the inference cost looks like in practice.