nigma
Joined 15 years ago
Joined 15 years ago
First of all the project is based on llama.cpp[1], which does the heavy work of loading and running multi-GB model files on GPU/CPU and the inference speed is not limited by the wrapper choice (there are other wrappers in Go, Python, Node, Rust, etc. or one can use llama.cpp directly). The size of the binary is also not that important when common quantized model files are often in the range of 5GB-40GB and require a beefy GPU or a MB with 16-64GB of RAM.
The best part about C64 was it immediately booted into a Basic prompt that invited you to experiment with the hardware, like typing these magic POKE commands to set screen and text colors.
I'm not actively involved in the package development anymore but it is still maintained [3] and there is a great chance that you have it already in your Python environment as a dependency of scikit-image/scikit-learn. Just give it a try, it's very simple:
>>> import pywt
>>> cA, cD = pywt.dwt([1, 2, 3, 4], 'db1')
[1] https://en.wikipedia.org/wiki/JPEG_2000
[2] https://pywavelets.readthedocs.io/
[3] https://github.com/PyWavelets/pywtSQLite is primarily embedded/local database and cannot be easily separated and shared over network [1] between multiple disposable backend/worker instances.
Also many ad-blockers that could filter app traffic were nuked from the App Store. I wish there was a way to firewall network traffic in the same way it is possible on other systems.
In other words if I buy a phone with 2y warranty (a standard duration in many European countries) it would be reasonable to expect that any security updates (device fixes) will be provided in a reasonable time within that period starting from the purchase date.
AWS product basically consists of open remote sensing datasets uploaded to S3. This is convenient if you deploy on AWS (transfer costs) but still have to develop all the data processing.
There are some sites that require JS to render, but the great thing is that majority of pages I visit work just fine as plain html/css. In general I feel less distraction from popups, overlays, ads, etc.
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https://github.com/nigma/