sesame/csm-1b
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Saurav Panda
sauravpanda
AI & ML interests
Small models and edge runtime!
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sesame/csm-1b
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sauravpanda's activity
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Post
1901
LLM Challenge with Petabytes of Data to Prove Famous Number Theory Conjecture https://mltblog.com/3F3Y9Yd
In my recent article “Piercing the Deepest Mathematical Mystery”, I paved the way to proving a famous multi-century old conjecture: are the digits of major mathematical constant such as π, e, log 2, or √2 evenly distributed? No one before ever managed to prove even the most basic trivialities, such as whether the proportion of ‘0’ or ‘1’ exists in the binary expansions of any of these constants, or if it oscillates indefinitely between 0% and 100%.
Here I provide an overview of the new framework built to uncover deep results about the digit distribution of Euler’s number e, discuss the latest developments, share a 10x faster version of the code, and feature new potential research areas in LLMs, AI, quantum dynamics, high performance computing, cryptography, dynamical systems, number theory and more, arising from my discovery. Perhaps the most interesting part is testing LLMs and other AI tools to assess their reasoning capabilities on a fascinating math problem with no solution posted anywhere.
➡️ Read about the challenge at https://mltblog.com/3F3Y9Yd
In my recent article “Piercing the Deepest Mathematical Mystery”, I paved the way to proving a famous multi-century old conjecture: are the digits of major mathematical constant such as π, e, log 2, or √2 evenly distributed? No one before ever managed to prove even the most basic trivialities, such as whether the proportion of ‘0’ or ‘1’ exists in the binary expansions of any of these constants, or if it oscillates indefinitely between 0% and 100%.
Here I provide an overview of the new framework built to uncover deep results about the digit distribution of Euler’s number e, discuss the latest developments, share a 10x faster version of the code, and feature new potential research areas in LLMs, AI, quantum dynamics, high performance computing, cryptography, dynamical systems, number theory and more, arising from my discovery. Perhaps the most interesting part is testing LLMs and other AI tools to assess their reasoning capabilities on a fascinating math problem with no solution posted anywhere.
➡️ Read about the challenge at https://mltblog.com/3F3Y9Yd
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I am currently developing a library aimed at enabling llms inside the browser. It's essentially a wrapper for MLC and transformer.js right now but plan to add more agentic stuff like RAG etc.
To integrate transformer.js with Next.js, I had to convert it to TypeScript. I want to ensure that I properly credit you and your work, and you can check it out here: https://github.com/sauravpanda/BrowserAI.
Additionally, I noticed that the license in transformer.js appears to be incomplete and contains default values. I wanted to bring this to your attention.
I hope this is okay with you, and I truly admire all of your work!
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