I am working with a bunch of fellows to make scalable teaching/training tools. Most of it will be open source, some will be free to access (since we have to use platforms like youtube).
The current project in that direction is a timeline-maker targeting research labs. Imagine joining a research lab (for MS/PhD) and getting a timeline of key papers in their field. This will set a baseline for "literature survey". Some of my professors from my college have already shown interest.
It is nothing fancy though. A python script that take YAML input and produce an HTML output. Now producing that YAML input with all the data from 100+ papers is the tedious task. I am currently doing it for my field - speech recognition.
I think they are referring to their server logs and other logs required to prevent site attack or misuse. Our access gets logged even before we can interact with their website. I could be wrong.
This one uses a simple, command based speech recognition system running on the browser - thanks to webassembly!
The model is trained using Kaldi and PyTorch.
[[In a “meta” issue in the GitHub tracker, Van Rossum outlined the three main pieces of the plan for 3.11. They all revolve around the idea of speeding up the bytecode interpreter through speculative specialization, which adapts the VM to run faster on some code because the object being operated on is of a known and expected type (or has some other attribute that can be determined with a simple test).]]
I thought adding type hints would improve the execution speed. If not now, at some point. Apparently they are not even considering it. They consider speculative specialization, which is likely more work than specialization based on known type hints. Still great to see that 'speed' is not ignored by the developers.
One day there will come an editor which has alternating line color theme by default - I hope.
Never mind that. I hope they won't forget to add 'read from stdin'.
The current project in that direction is a timeline-maker targeting research labs. Imagine joining a research lab (for MS/PhD) and getting a timeline of key papers in their field. This will set a baseline for "literature survey". Some of my professors from my college have already shown interest.
It is nothing fancy though. A python script that take YAML input and produce an HTML output. Now producing that YAML input with all the data from 100+ papers is the tedious task. I am currently doing it for my field - speech recognition.