> AI by Hand is the research publication of By Hand Research, founded by Prof. Tom Yeh. By Hand Research studies model interpretability and explainability at the math and algorithm level. Subscribers receive free new articles and join live seminars. Members get access to our full research library.
Yes. Convince me why your site is worth my attention, don't try to force it through a dark pattern and then try to justify why I should waste my time figuring it out.
i created something similar a while back. Inspired by micrograd for showing the connection between math/calculus and code, then building along the way to a full NumPy deep learning library that I pretrained GPT-2 124M model with it. One way to learn is to trace through the PRs merged to the repo in chronological order.
- half the posts are locked
- other half have no visualizations whatsoever
- i have posted far better resources than this in the past collecting everything HN has over a 10 yr period on these subjects https://news.ycombinator.com/item?id=49183198
This is also recommended reading if you want to learn more about building LLMs from scratch: See:
Train your own LLM - https://github.com/angelos-p/llm-from-scratch
HN Discussion - https://news.ycombinator.com/item?id=48017948
https://www.byhand.ai/p/library
> AI by Hand is the research publication of By Hand Research, founded by Prof. Tom Yeh. By Hand Research studies model interpretability and explainability at the math and algorithm level. Subscribers receive free new articles and join live seminars. Members get access to our full research library.
I'm not sure what this is. Click past the subscribe page to get a bunch of links to descriptions of articles I could read if I was a subscriber?
Scroll all the way down and there's a video, it's a course he's making for deep-dive into how Qwen 3.6 works internally
Click "Later->" to bypass subscribe.
I clicked "Back" to leave the user-hostile website.
Yes. Convince me why your site is worth my attention, don't try to force it through a dark pattern and then try to justify why I should waste my time figuring it out.
dont see later
Eventually, none of us do.
I found Deep Learning by No Starch Press to be an excellent primer the foundation of AI:
https://nostarch.com/deep-learning-visual-approach
There's also The Little Learner: https://www.thelittlelearner.com/
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i created something similar a while back. Inspired by micrograd for showing the connection between math/calculus and code, then building along the way to a full NumPy deep learning library that I pretrained GPT-2 124M model with it. One way to learn is to trace through the PRs merged to the repo in chronological order.
The philosophy is the same: "What I cannot create, I do not understand." https://github.com/workofart/ml-by-hand
wow this is nice work. i am diving into this world and was hoping to this exact thing. i am going to look to see how you did it. ty for sharing.
My professor used this "by hand" technique when teaching quantum computation algorithms, so I have a soft spot for it.
Nice! Is that also accessible online?
No :(
I’d say bad UX design. It may or may not be something good behind the door. But why do I enter?
See also:
0 - https://arxiv.org/pdf/2501.09223v2this is sick!
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