you could also use "mps" (Apple), "xpu" (Intel), "hip" (AMD) GPUs and "xla" for TPUs. But yeah, those are less mature.
@rasbt
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AI/ML Engineering Career Development Strategy
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I think that would go a long way for an AI/ML engineering career
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LitGPT Pre-training Implementation and OLMo 2 Recommendation
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We implemented pre-training in LitGPT (e.g., it was used to train TinyLlama back then): https://
github.com/Lightning-AI/l
itgpt/blob/main/litgpt/pretrain.py
…
I would strongly recommend looking at OLMo 2 otherwise: https://
github.com/allenai/OLMo/b
lob/main/olmo/train.py
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Teaching Decision Trees as First ML Method in Statistics
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Agreed. Btw decision trees were the first ML/AI method I taught in my Stat 451 classes back then:
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NVIDIA’s 10-Year Lead in CUDA and Scientific Computing
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"NVIDIA has a ~10 year lead with their general purpose compute language CUDA" Yes, this!!
I was in a research lab 14 years ago where we used CUDA (and Nvidia-sponsored GPUs) for molecular dynamics simulations. Nividia has a big head start in scientific computing. -
Applied Math and Programming Skills: Yann LeCun’s Educational Advice
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Applied math and problem-solving skills. There's a famous @ylecun quote "If you are an undergrad, take as many math and physics courses as you can, and learn to program." (
https://
reddit.com/r/MachineLearn
ing/comments/25lnbt/ama_yann_lecun/
…) -
Future ML with PyTorch project plans and timeline
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The ML with PyTorch one? Agreed. I hope to get to it in the next 1-2 years!
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AI degree programs from reputable institutions raise concerns
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I don't want to name any, but there are lots of them. I often get emails from either former students listing AI degree options from pretty reputable places and asking for advice.
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AI Degree Advice: Foundation in Math, Stats, Physics Instead
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Maybe a hot take, but what about the following advice to the next gen: Don't get an AI degree; the curriculum will be outdated before you graduate. Instead, study math, stats, or physics as your foundation, and stay current with AI through code-focused books, blogs, and papers.
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GQA Implementation Guide for Llama Model Conversion
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Nice work! In case you get stuck, I've implemented GQA as part of the GPT -> Llama conversion guides: https://
github.com/rasbt/LLMs-fro
m-scratch/tree/main/ch05/07_gpt_to_llama
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But since you already implemented MQA, GQA should be pretty smooth sailing 🙂