Four short links: 6 August 2018
GPU Notebooks, Reproducible Experiments, History of Fears, and Debloating Code
- Kernels — Kaggle hosting Jupyter Notebooks with GPUs.
- Speedrun — A no-strings-attached toolkit to help you deploy and manage your machine learning experiments. The idea is to equip you with the tools you need to have well-documented and reproducible experiments going, but without getting in your way.
- Ancient Dreams of Intelligent Machines (Nature) — the extraordinary history of cultural responses to automata.
- Trimmer — an application specialization tool that leverages user-provided configuration data to specialize an application to its deployment context. The specialization process attempts to eliminate the application functionality that is unused in the user-defined context. Our evaluation demonstrates Trimmer can effectively reduce code bloat. For 13 applications spanning various domains, we observe a mean binary size reduction of 21% and a maximum reduction of 75%. Description of how it works, but no source, alas.
