@QuantumTransf: I have to say some people are filled with a mysterious self-confidence. The contemporary computer science titan Knuth once said, "Computer science is a branch of mathematics." I used magic to counter-attack, and they actually don't think computer science is mathematics, proving that their understanding is stuck at the general undergraduate level, at least they haven't read TAOCP or done any academic research in computer science. Of course, nowadays computer science has become a broad term encompassing many things, including parts of Software Engineering. Seriously, I suggest you take a look at discrete mathematics; it is a very important component of computer science, and many algorithms and ideas originate from there.

X AI KOLs Timeline News

Summary

An academic debate on whether computer science belongs to mathematics, citing a quote from computer science giant Knuth, involving discussions on discrete mathematics and the essence of algorithms.

I have to say some people are filled with a mysterious self-confidence. The contemporary computer science titan Knuth once said, "Computer science is a branch of mathematics." I used magic to counter-attack, and they actually don't think computer science is mathematics, proving that their understanding is stuck at the general undergraduate level, at least they haven't read TAOCP or done any academic research in computer science. Of course, nowadays computer science has become a broad term encompassing many things, including parts of Software Engineering. Seriously, I suggest you take a look at discrete mathematics; it is a very important component of computer science, and many algorithms and ideas originate from there.
Original Article
View Cached Full Text

Cached at: 07/03/26, 10:34 AM

I have to say, some people are filled with a mysterious sense of confidence. The contemporary computer science giant Knuth once said, “Computer science is a branch of mathematics.” I would counter that with some “magic”—how can someone deny that computer science is part of mathematics? This proves that person’s understanding is at the typical undergraduate level; at the very least, they haven’t read TAOCP, nor have they done any academic research in computer science. Of course, nowadays computer science has been generalized into an all-encompassing term, which actually includes parts of Software Engineering. Seriously, I suggest you take a look at discrete mathematics—it’s a very important component of computer science, and many algorithms and ideas originate from it.

lidang (The first person to persuade people to sell houses / study CS / buy S&P500 / Nasdaq100 / OpenAI / Anthrop) (@lidangzzz): Actually believing that dynamic programming, DFS, graphs, etc., are mathematics,

Proves that this person’s math level is basically stuck at high school; at least they never properly learned calculus and linear algebra, and have never touched any real introductory math like analysis, algebra, geometry, or combinatorics.

This is a typical ideology of greasy middle-aged uncles—their own skills are trash, they have low intelligence, and low education; seeing a math formula or proof…

Similar Articles

@Xudong07452910: After AI starts doing math, a more dangerous thought may emerge: if machines can prove theorems, are human mathematicians less important? This essay "Automation Without Understanding" discusses this issue. The author's core point is straightforward: Mathematics...

X AI KOLs Timeline

AI systems have made breakthroughs in mathematics, helping to overturn Erdős's long-standing conjecture about unit distances in the plane. But an essay warns: the stronger the automation, the more important human ability to understand and audit machine reasoning becomes, while the U.S. mathematics talent pipeline is degrading due to budget cuts.

@berryxia: Honestly, only truly brilliant people dare to say such things! An undergraduate student can handle the math training of LLMs! In a recent interview, Terence Tao laid out the core mystery of LLMs directly. The Fields Medal winner, the highest honor in mathematics — often called the Nobel Prize of math — and one of the most top contemporary…

X AI KOLs Timeline

Terence Tao pointed out that the math behind current LLMs is actually very simple, but the real puzzle lies in the intermediate zone of natural language data, which leads to unpredictable model behavior.

@Phoenixyin13: Recently, I finally realized that continuous calculus might just be an engineering compromise produced by human intelligence. The origin was a book sent to me by my Swiss classmate — a 1200-page magnum opus titled A New Kind of Science (NKS). The author of this book is the genius scholar I have been following, Ste…

X AI KOLs Timeline

The author shares his reflections on Stephen Wolfram's A New Kind of Science, arguing that continuous calculus is only an engineering compromise made for a discrete universe in an era of scarce computing power, and discusses how computational irreducibility challenges the traditional paradigm of prediction.

@snowboat84: To add a supplementary note, regarding the phenomena emerging from AI—scaling laws, emergence, double descent, representation geometry—the papers discussing them are already numerous. But there is a big problem: they are all thinking in the way of computer scientists, not physicists. What is a computer sci…

X AI KOLs Timeline

The author comments that current AI research overuses the thinking style of computer science and lacks a physics-based approach, proposing the need to establish an ideal system like 'Cyber Space' to lay a theoretical foundation.

@snowboat84: Today, let's discuss something hardcore. One question: what level of mathematics does AI use? From the perspective of tools and models themselves, the mathematics used by AI has an average age of 150 years, with most being from before the mid-19th century: matrix multiplication, gradient descent, chain rule, Fourier transform, inner product, probability — mostly content from the first two years of undergraduate studies. But some phenomena emerging from AI...

X AI KOLs Timeline

Discusses that the mathematics used by AI is mainly linear algebra, calculus, etc., from before the 19th century, but emerging phenomena such as Scaling Law, emergent abilities, double descent, in-context learning, and representation geometry lack mathematical explanation. Analogizes to the clouds in physics in 1900, suggesting it may drive the development of 21st-century mathematics.