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yu3zhou4
searching PlanetScale…
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3 ms
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What Are Sheaves? (2024)
(quantamagazine.org)
2 points
by
yu3zhou4
7d ago
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0 comments
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yu3zhou4
7d ago
Michał Zalewski (the author of this book) is goated. His book Silence on the Wire was very inspiring to me and the techniques he described often come to my mind years after reading the book
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A CPU Backdoor (2025)
(phrack.org)
4 points
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yu3zhou4
8d ago
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0 comments
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yu3zhou4
12d ago
I study stats and probability
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yu3zhou4
23d ago
I found that in LLMs the self-reference defined as "referring in generated text to itself" (so a bit different than in Scott's blog) comes largely from the chat template https://openreview.net/pdf?id=3O2A23MhN
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Offpunk Manifesto
(blog.ayom.media)
3 points
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yu3zhou4
24d ago
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yu3zhou4
1mo ago
Also PageRank as a Markov chain [0] https://math.libretexts.org/Bookshelves/Linear_Algebra/Under...
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The Hacker's Renaissance (2025)
(phrack.org)
125 points
by
yu3zhou4
2mo ago
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103 comments
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yu3zhou4
2mo ago
I’m happy it helps you!
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yu3zhou4
2mo ago
If you prefer C++ and CUDA, then there's also tiny-vllm of mine [0] - recently we broke 1k gh stars [0] https://github.com/jmaczan/tiny-vllm
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yu3zhou4
2mo ago
My fav zine
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yu3zhou4
2mo ago
It's a very useful guide, I used it when working on torch-webgpu some time ago. Elie also published few packages that help with using some WebGPU related things, I don't remember exactly what was that but I recall it saved me lots
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yu3zhou4
3mo ago
Print ondemand can be ordered for less than $5 per zine in Lulu, since 2022 or so. I guess Zach doesn’t make a cut from it since this $5 probably barely covers the cost of print and Lulu fee :(
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Exapunks (2018)
(zachtronics.com)
333 points
by
yu3zhou4
3mo ago
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123 comments
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William Thurston: On Proof and Progress in Mathematics (1994) [pdf]
(ams.org)
1 points
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yu3zhou4
3mo ago
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AMD contributes their GPU support to tiny-vLLM
(github.com)
2 points
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yu3zhou4
3mo ago
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yu3zhou4
3mo ago
PyTorch?
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The Cypherpunk Library
(cypherpunkbooks.com)
378 points
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yu3zhou4
4mo ago
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97 comments
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yu3zhou4
4mo ago
README is in my opinion (author here) the most interesting - I wrote it to help others build useful mental model to be able to recreate the project yourself, without need to even read my code
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Show HN: Tiny-vLLM – high performance LLM inference engine in C++ and CUDA
(github.com)
205 points
by
yu3zhou4
4mo ago
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18 comments
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yu3zhou4
5mo ago
There was onivim that was a bit hyped a few years ago but unfortunately it died
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yu3zhou4
5mo ago
Just learning math and trying myself in ml research
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yu3zhou4
5mo ago
Laughed hard about Collegium Tumanum
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yu3zhou4
5mo ago
Poland was sort of occupied until 1989
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yu3zhou4
5mo ago
Good idea, too! Why do you see my explanation as cynical, though?
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yu3zhou4
5mo ago
Maybe it’s in order to have an external provider to blame for failures and shift the blame/responsibility?
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yu3zhou4
5mo ago
Adding a support for new hardware to PyTorch is actually quite convenient. I did that with WebGPU using the same PrivateUse1 mechanism TorchTPU used. Every hardware has its own slot and identifier, and when you want to add a support for a n
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yu3zhou4
5mo ago
They write that they use PrivateUse1, so it’s a custom out-of-tree backend
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TorchWebGPU: Running PyTorch Natively on WebGPU
(github.com)
2 points
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yu3zhou4
5mo ago
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0 comments
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yu3zhou4
5mo ago
The system like iOS is still closed. Once Apple ends support for a device, being able to swap a battery won’t help much
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