About
Gruhesh Sri Sai Karthik Kurra
AI and machine learning engineer. I write the notes I wish existed when I was learning this stuff: full derivations, real numbers, and code that actually runs.
What this blog is
Every post here comes out of building something. When I worked through reverse-mode autograd, I wrote the autograd post. When I rebuilt GPT-2, I wrote that one. The pattern is always the same: derive the math by hand, write the naive version, break it, fix it, then check it against a reference implementation.
That means the posts are longer than most. They keep the derivations in, they keep the parameter-count tables in, and they use the actual hyperparameters from the actual config rather than round numbers. If you want a five-minute summary, these are the wrong notes. If you want to be able to rebuild the thing, they should be enough.
Background
Incoming MSc Computing (AI & ML) at Imperial College London (from Sep 2026). Before that, AI integration work (LLM systems, retrieval, and the plumbing that makes models usable in production), plus research at IIIT Hyderabad.
Interests, roughly in order: language model internals, training dynamics, numerical methods, and how much of “modern architecture” is genuinely necessary versus inherited.
Where to start
- AI from Scratch: the whole thing in order, linear algebra through a working GPT-2. Start at part one.
- Topics: if you already know what you’re looking for.
- Library: books, courses, and papers I actually used, no affiliate links.
Elsewhere
- Portfolio: gruheshkurra.com
- GitHub: GruheshKurra
- Hugging Face: karthik-2905
- LinkedIn: gruheshkurra
- X: @Karthik__kurra
Get in touch
Corrections are welcome and genuinely wanted. If a derivation is wrong or a number is off, tell me. Email gruheshkurra2@gmail.com.
If a post saved you an afternoon, you can buy me a coffee.