Why not simply have both? This does not have to be an either-or decision. Have a default repository with vetted extensions, but leave the option to install from other sources open.
For seekable gzip indexes in zip, there SOZip: https://github.com/sozip/sozip-spec . However, it stores the indexes as files succeeding the actual file entry. To hide these index files and avoid extraction, they are not listed in the central directory, but a linear scan of the local headers, which some wrongly-behaved ZIP tools do, or which might be necessary for recovering broken ZIP files, would find those hidden indexes.
> 10. Code is cheap, but maintenance, support, and security aren’t.
I also keep circling around this point. So many software repositories in the AI space seem to follow a publish and forget pattern. If you simply can show that you have the patience to maintain a project, ideally with manual intervention instead of a fully autonomous AI, then you already have an outstanding project.
These are not errors. They are simply warnings about extended attributes being ignored when extracting files, which seems completely fine to me, and creating the tar without those extended attributes has exactly the same outcome, but throws away the metadata at archive time instead of extraction time.
Furthermore, this is not an Apple/macOS issue. The tool used is bsdtar, so it would also affect all BSD-variants that default to bsdtar/libarchive, and those systems also have extended attributes, e.g., for SELinux, which would get added to the TAR.
Note, however, that this can only seek to frames, and zstd still only creates files containing a single frame by default. pzstd did create multi-frame files, but it is not being developed anymore. Other alternatives for creating seekable zstd files are: zeekstd, t2sz, and zstd-seekable-format-go.
Exactly. And often this state is either highly compressible or non-compressible but only sparsely used. The latter can then be made compressible by replacing the unused bytes with zeros.
Ratarmount uses indexed_gzip, and when parallelization makes sense, it also uses rapidgzip. Rapidgzip implements the sparsity analysis to increase compressibility and then simply uses the gztool index format, i.e., compresses each 32 KiB using gzip itself, with unused bytes replaced with zeros where possible.
indexed_gzip, gztool, and rapidgzip all support seeking in gzip streams, but all have some trade-offs, e.g., rapidgzip is parallelized but will have much higher memory usage because of that than indexed_gzip or gztool. It might be possible to compile either of these to WebAssembly if there is demand.
I like the idea of bubblewrap, but my pain point is that it is work to set it up correctly with bind mounts and forwarding necessary environment variables to make the program actually work usefully. Could you share your pip bwrap configuration? It sounds useful.
> The obvious one outside of KV caches as mentioned above is vector databases. Any RAG pipeline that stores embedding vectors for retrieval benefits from the same compression. TurboQuant reduces indexing time to “virtually zero” on vector search tasks and outperforms product quantisation and RabbiQ on recall benchmarks using GloVe vectors.
This part sounds especially cool. I did not think about this application when reading the other articles about TurboQuant. It would be cool to have access to this performance optimization for local RAG.
After 2 minutes at 150 kHashes on mobile, I finally see the first pixel of the progress bar filling up. Seems like it will take hours or a day to finish. Some estimate would have been nice.
I never understood why the recommended replacement for ß is ss. It is a ligature of sz (similar to & being a ligature of et) and is even pronounced ess-zet. The only logical replacement would have been sz, and it would have avoided the clash of Masse (mass) and Maße (measurements). Then again, it only affects whether the vowel before it is pronounced short or long, and there are better ways to encode that in written language in the first place.