My job involves a lot of staring at large numbers, mostly latencies in nanoseconds, and picking out magnitudes like microseconds. I noticed myself constantly...
Functional Programmers need to take a look at Zig.
I’ve been tinkering around with Zig to explore what’s possible with comptime. Whenever I evaluate a new language I use three axes:
Kill Math
The power to understand and predict the quantities of the world should not be restricted to those with a freakish knack for manipulating abstract symbols.
Mathematicians still don’t know the fastest way to multiply numbers
A 23-year-old student overturned an ancient conjecture about one of math’s simplest operations
esoteric.codes
esolangs, esoplatforms, esosystems, and all that break from the norms of computing
A faster way to calculate the day-of-the-week
A range of fast modulus techniques that beat compiler output
Faster double-to-string conversion
There comes a time in every software engineer’s life when they come up with a new binary-to-decimal floating-point conversion method. I guess my time has come. I just wrote one, mostly over a weekend: https://github.com/vitaut/zmij.
Ten advances in mathematics and theoretical computer science
OpenAI shares new results on long-standing open problems in mathematics and theoretical computer science, including advances in geometry, cryptography, and complexity.
Using spaced repetition systems to see through a piece of mathematics
By Michael Nielsen, January 2019
Why Can’t Powerful LLMs Learn Multiplication?
These days, large language models (LLMs) can handle increasingly complex tasks, writing complex code and engaging in sophisticated reasoning. But when it comes to 4-digit multiplication, a task taught in elementary school, even state-of-the-art systems fail. Why? A new paper by Computer Science PhD student Xiaoyan Bai and Faculty Co-Director of the Data Science Institute’s …
Write You a Haskell ( Stephen Diehl )
The End of Mathematics — Daniel Litt
I'm currently returning to Toronto from a summit on the future of mathematics, at OpenAI. Sebastian Bubeck asked me to talk a bit about the future we'd all like to avoid, where humans are mathematically disempowered. Jacob Tsimerman advised us to try to prioritize detail over correctness, and I have no doubt that I succeeded in deprioritizing correctness.
ggtime: A Grammar of Temporal Graphics
Visualizing changes over time is fundamental to learning from the past and anticipating the future. However, temporal semantics can be complicated, and existing visualization tools often struggle to accurately represent these complexities. It is common to use bespoke plot helper functions designed to produce specific graphics, due to the absence of flexible general tools that respect temporal semantics. We address this problem by proposing a grammar of temporal graphics, and an associated software implementation, 'ggtime', that encodes temporal semantics into a declarative grammar for visualizing temporal data. The grammar introduces new composable elements that support visualization across linear, cyclical, quasi-cyclical, and other granularities; standardization of irregular durations; and alignment of time points across different granularities and time zones. It is designed for interoperability with other semantic variables, allowing navigation across the space of visualizations while preserving temporal semantics.
Another absolutely bonkers math result from a frontier LLM (announced in a tweet, no less): reddit.com/r/math/comments/1v1aix1/the_j…
From the math community on Reddit: The Jacobian Conjecture is False Per Anthropic (Link in Description)
www.reddit.com