vismit2000

32 ms·

751.
by vismit2000 2y ago
Related: The Potential for AI in Science and Mathematics - Terence Tao https://www.youtube.com/watch?v=_sTDSO74D8Q
752.
by vismit2000 2y ago
Chapter level detailed summary for quick overview of main ideas from the book: https://www.booksummary.pro/Never_Split_the_Difference_summa...
753.
12 Coins in Verse: Genius solution of twelve balls and a scale problem(cut-the-knot.org)
31 points by vismit2000 2y ago|5 comments
754.
by vismit2000 2y ago
Related: https://cpu.land/
755.
by vismit2000 2y ago
Mathologer video on the same: https://www.youtube.com/watch?v=4AuV93LOPcE
756.
by vismit2000 2y ago
This has been an absolute game changer: https://github.com/pytries/marisa-trie (succinct trie with fast lookup and minimal RAM) Use case and more details in the wonderful book by Ian and Micha: High Performance Python
757.
by vismit2000 2y ago
https://www.edwardtufte.com/bboard/q-and-a-fetch-msg?msg_id=...
758.
by vismit2000 2y ago
How about water computer? https://youtu.be/IxXaizglscw
759.
by vismit2000 2y ago
This is covered in section 9.3 in CLRS book - Medians and Order Statistics
760.
by vismit2000 2y ago
Stanford CS25: V4 I Hyung Won Chung of OpenAI - https://youtu.be/orDKvo8h71o
761.
by vismit2000 2y ago
I wonder when she grows up and starts spending all day on HN like us, she would be really glad to see this post and the appreciative comments here :)
762.
by vismit2000 2y ago
https://xkcd.com/927/
763.
by vismit2000 2y ago
π seconds is a nanocentury: 1 year = 3.155 × 10^7 seconds (Programming Pearls by Jon Bentley)
764.
by vismit2000 2y ago
Also check out the detailed chapter level summary here: https://www.booksummary.pro/Why_We_Sleep_summary.html
765.
by vismit2000 2y ago
https://pyscript.com/
766.
by vismit2000 2y ago
ptpython: https://github.com/prompt-toolkit/ptpython
767.
by vismit2000 2y ago
Nothing beats ISLR: https://www.statlearning.com/
768.
by vismit2000 2y ago
Great article! Agree with everything mentioned. Good to share with all tech people who don't work in the AI space and "hallucinate" about working of LLMs. Having said that, although LLMs don't directly learn from what we
769.
by vismit2000 2y ago
It's there in form of chain: from itertools import chain flatten = chain.from_iterable Ref: pytudes - https://github.com/norvig/pytudes/blob/main/ipynb/Advent-202...
770.
by vismit2000 2y ago
Lessons after a Half-billion GPT Tokens: https://news.ycombinator.com/item?id=40015185 Goes well with the first observation in the shared article: "Lesson 1: When it comes to prompts, less is more"
771.
by vismit2000 2y ago
I have been taking notes in VS code for more than three years now in plain text. I use this extension for colors and syntax highlights: https://marketplace.visualstudio.com/items?itemName=canadadu...
772.
by vismit2000 3y ago
Karpathy also writes beautiful python code and his GPT lecture series contains some of the finest python code to learn from. https://github.com/karpathy/nn-zero-to-hero
773.
by vismit2000 3y ago
Just FYI, it was possible to solve Advent of Code 2023 - Day 25 using a cool Linear Algebra trick as well. "Fiedler vector"[1] - Algebraic connectivity (without networkx): https://www.reddit.com/r/adventofcode
774.
by vismit2000 3y ago
Advanced Python Mastery: https://news.ycombinator.com/item?id=36785005 Book: High Performance Python
775.
by vismit2000 4y ago
Stanford Lecture: Don Knuth—"Dancing Links" (2018): https://youtu.be/_cR9zDlvP88