arnaucube
@arnaucube
Cryptography engineering.
arnaucube.com
Love to study cryptography and mathematics.
prev. @0xPARC @AragonProject @vocdoni @identhree
arnaucube.com
Love to study cryptography and mathematics.
prev. @0xPARC @AragonProject @vocdoni @identhree
507 Following 1.1K Followers 524 Posts
Latest posts 5
If you're in Barcelona next Thursday, this will be fun!
Will go over some of the math behind lattices and how they are used to build post-quantum cryptography.
Will go over some of the math behind lattices and how they are used to build post-quantum cryptography.
📡Save the date, new Ethereum Engineering Barcelona meetup luma.com/i95pdcdc Sep 17th at @AKASHAworldBCNView quoted post on X
⊢ Quantum computing by Albert Solana (@qilimanjaro, builders of quantum computers)
⊢ Intro to Lattices by @arnaucube
⊢ A post-quantum ethereum by @adria0
These past days I've been reading this pdf, and it is really interesting (I had no prior idea on LLMs).
Really recommended. Don't ask an LLM for an overview, read it through, it's only 16 pages. Afterwards you can do a quick impl to see the compnnts in action,really interesting!
Really recommended. Don't ask an LLM for an overview, read it through, it's only 16 pages. Afterwards you can do a quick impl to see the compnnts in action,really interesting!
"The Simple Mathematics of Large Language Models" is a concise free paper if you want to understand the mathematics behind modern LLMs and systems such as ChatGPT and Claude.
I have shared several resources in the past that explain the mathematics behind these systems in detail, but they are often quite long. This paper is only about 20 pages, so I think it is a useful resource if you want a compact introduction without starting from a much larger textbook.
It covers token representations, context, attention as learned weighted averaging, projections and bilinear forms, multi-head attention, normalization, positional information, softmax, maximum likelihood, cross-entropy, and gradient descent. Together, these topics give a concise mathematical picture of how a language model works.
Save it to your bookmarks. It can be useful as a quick reference.
crc.business-school.ed.ac.uk/sites/crc/file…View quoted post on X
I was curious on how (post-quantum) lattice-based SNARKs work. I've been reading the LaBRADOR paper.
This post tries to explain the intuition and steps not explicitly shown in the paper, which helped me understanding it.
arnaucube.com/blog/labrador.…
This post tries to explain the intuition and steps not explicitly shown in the paper, which helped me understanding it.
arnaucube.com/blog/labrador.…
