The cost comparison between local RTX 3090 and cloud A100 clusters is useful, but I wonder if the author accounted for hidden overhead—like data transfer time for large datasets or the time spent debugging CUDA compatibility issues on local hardware.
The cost comparison between local RTX 3090 and cloud A100 clusters is useful, but I wonder if the author accounted for hidden overhead—like data transfer time for large datasets or the time spent debugging CUDA compatibility issues on local hardware.
It's based on a book https://www.manning.com/books/build-a-large-language-model-f..., is it a good book?
Here's part 1 [1]. Since his archive goes by date, it makes it a bit easier to guestimate which part is made in which month.
[1] https://www.gilesthomas.com/2024/12/llm-from-scratch-1
Nice, this is a recipe for making an evil AI which will destroy humanity.