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SpaceX Delays Mars Plans to Focus on Moon

https://www.wsj.com/science/space-astronomy/spacex-delays-mars-plans-to-focus-on-moon-66d5c542
1•BostonFern•20s ago•0 comments

Jeremy Wade's Mighty Rivers

https://www.youtube.com/playlist?list=PLyOro6vMGsP_xkW6FXxsaeHUkD5e-9AUa
1•saikatsg•43s ago•0 comments

Show HN: MCP App to play backgammon with your LLM

https://github.com/sam-mfb/backgammon-mcp
1•sam256•2m ago•0 comments

AI Command and Staff–Operational Evidence and Insights from Wargaming

https://www.militarystrategymagazine.com/article/ai-command-and-staff-operational-evidence-and-in...
1•tomwphillips•2m ago•0 comments

Show HN: CCBot – Control Claude Code from Telegram via tmux

https://github.com/six-ddc/ccbot
1•sixddc•4m ago•1 comments

Ask HN: Is the CoCo 3 the best 8 bit computer ever made?

1•amichail•6m ago•0 comments

Show HN: Convert your articles into videos in one click

https://vidinie.com/
1•kositheastro•8m ago•0 comments

Red Queen's Race

https://en.wikipedia.org/wiki/Red_Queen%27s_race
2•rzk•9m ago•0 comments

The Anthropic Hive Mind

https://steve-yegge.medium.com/the-anthropic-hive-mind-d01f768f3d7b
2•gozzoo•11m ago•0 comments

A Horrible Conclusion

https://addisoncrump.info/research/a-horrible-conclusion/
1•todsacerdoti•11m ago•0 comments

I spent $10k to automate my research at OpenAI with Codex

https://twitter.com/KarelDoostrlnck/status/2019477361557926281
2•tosh•12m ago•0 comments

From Zero to Hero: A Spring Boot Deep Dive

https://jcob-sikorski.github.io/me/
1•jjcob_sikorski•13m ago•0 comments

Show HN: Solving NP-Complete Structures via Information Noise Subtraction (P=NP)

https://zenodo.org/records/18395618
1•alemonti06•18m ago•1 comments

Cook New Emojis

https://emoji.supply/kitchen/
1•vasanthv•21m ago•0 comments

Show HN: LoKey Typer – A calm typing practice app with ambient soundscapes

https://mcp-tool-shop-org.github.io/LoKey-Typer/
1•mikeyfrilot•24m ago•0 comments

Long-Sought Proof Tames Some of Math's Unruliest Equations

https://www.quantamagazine.org/long-sought-proof-tames-some-of-maths-unruliest-equations-20260206/
1•asplake•24m ago•0 comments

Hacking the last Z80 computer – FOSDEM 2026 [video]

https://fosdem.org/2026/schedule/event/FEHLHY-hacking_the_last_z80_computer_ever_made/
2•michalpleban•25m ago•0 comments

Browser-use for Node.js v0.2.0: TS AI browser automation parity with PY v0.5.11

https://github.com/webllm/browser-use
1•unadlib•26m ago•0 comments

Michael Pollan Says Humanity Is About to Undergo a Revolutionary Change

https://www.nytimes.com/2026/02/07/magazine/michael-pollan-interview.html
2•mitchbob•26m ago•1 comments

Software Engineering Is Back

https://blog.alaindichiappari.dev/p/software-engineering-is-back
2•alainrk•27m ago•0 comments

Storyship: Turn Screen Recordings into Professional Demos

https://storyship.app/
1•JohnsonZou6523•27m ago•0 comments

Reputation Scores for GitHub Accounts

https://shkspr.mobi/blog/2026/02/reputation-scores-for-github-accounts/
2•edent•31m ago•0 comments

A BSOD for All Seasons – Send Bad News via a Kernel Panic

https://bsod-fas.pages.dev/
1•keepamovin•34m ago•0 comments

Show HN: I got tired of copy-pasting between Claude windows, so I built Orcha

https://orcha.nl
1•buildingwdavid•34m ago•0 comments

Omarchy First Impressions

https://brianlovin.com/writing/omarchy-first-impressions-CEEstJk
2•tosh•40m ago•1 comments

Reinforcement Learning from Human Feedback

https://arxiv.org/abs/2504.12501
7•onurkanbkrc•40m ago•0 comments

Show HN: Versor – The "Unbending" Paradigm for Geometric Deep Learning

https://github.com/Concode0/Versor
1•concode0•41m ago•1 comments

Show HN: HypothesisHub – An open API where AI agents collaborate on medical res

https://medresearch-ai.org/hypotheses-hub/
1•panossk•44m ago•0 comments

Big Tech vs. OpenClaw

https://www.jakequist.com/thoughts/big-tech-vs-openclaw/
1•headalgorithm•47m ago•0 comments

Anofox Forecast

https://anofox.com/docs/forecast/
1•marklit•47m ago•0 comments
Open in hackernews

Discrete Fourier Transform

https://nima101.github.io/dft
92•pykello•4mo ago

Comments

tverbeure•4mo ago
I almost always prefer text over video, but this video on the same subject is fantastic: https://www.youtube.com/watch?v=h7apO7q16V0. I watch it at least once every year.

Also, the title of the blog post (and by extension this HN post) is IMO not really correct: it's not about the DFT but specifically about the FFT.

majorchord•4mo ago
Not going to lie, I have always been fascinated by the fourier transform, but I had to stop this video after less than 2 minutes in because it went way over my head... "a context you are all familiar with: polynomial multiplication"... um no, I have zero clue what that is, sorry. Also the speaker seems to have some sort of speech pathology that unfortunately bothers me.
lomase•4mo ago
I like this 3Blue1Brown video about what he calls the almost-fuerier transform:

www.youtube.com/watch?v=spUNpyF58BY

tverbeure•3mo ago
Polynomial multiplication is something I learned in 8th grade?
aeve890•4mo ago
>I’ve worked on ads at Meta, Snap, and Nextdoor. I also consult companies on building ads. If you are building your ad stack, feel free to reach out — let’s chat!

Hmmm

IMTDb•4mo ago
Not sure I get your point here
lispisok•4mo ago
Do we really need yet another blog post about Fourier transforms that's really just self-promotion on HN?
tverbeure•4mo ago
What self-promotion? This was posted to HN by someone who had a long history of posting lots of links, with no obvious connection to the writer of the blog post.

As for yet another Fourier related post, shall we talk about AI instead?

lomase•4mo ago
After careful consideration I think the point of aeve890 is that the advertisment industry sucks big time.
aeve890•4mo ago
Is this not the stereotypical big tech employee everyone love to bash here when the topic of advertising comes out? I've read thousand of comments about the morality of people working in that industry. Well, here's one.

I hope it helps.

dvfjsdhgfv•3mo ago
And actually, you can observe the values in action here:

https://nima101.github.io/adsopt

lomase•4mo ago
Feels like an article wrote from somebody who knows a lot about the FFT for people who already knows a lot about the FFT.
dkjaudyeqooe•4mo ago
All mathematic exposition feels that way.
amirhirsch•4mo ago
If you are doing polynomial multiplication and want exact integer convolution then you can’t leave the precision of your FFT up to chance so the alternative to an FFT over complex roots of unity is to use something called a Number Theoretic Transform (NTT) that relies on nth roots of unity in finite integer rings
DecentShoes•4mo ago
From what I've read about it all in the past, I feel like my intelligence level sits precisely between DCT and DFT. I seem to be able to mostly get Discrete Cosine Transform, but when confronted with Discrete Fourier Transform my brain simply shuts off and melts.
throw_away_8080•4mo ago
If you wanted to multiply two polynomials f and g of degree n, you could do distribution and the do n squared multiplications. Instead, evaluate the two separate polynomials at 2n special points, multiply the results pointwise, and then interpolate. The magical part is there are some specific points which speed up the evaluation and interpolation steps using a divide and conquer type algorithm.
e-khadem•4mo ago
I first learned about FFT in highschool to solve competitive programming problems, and it was, let's say, useful for that. But then I started studying EE, and after learning more about the different types of Fourier transform, I started respecting the humble DFT matrix much more. I believe there is big gap of understanding between considering FFT as a cool algorithm for multiplying polynomials (or doing a circular convolution), and considering the transform as obtaining an eigenvalue representation of linear systems. The latter might not be as fruitful in the software engineering per se, but is the backbone of understanding the Fourier Transform for EE.
dkjaudyeqooe•4mo ago
Somewhat off topic rant, but am I the only one who find mathematical notation unnecessarily obtuse?

The bit that gets me is defining degree as n-1. For someone without a mathematical background, it takes a bit of pondering to figure out that you have to define n as one more than the actual degree, the opposite of what seems natrual. My mind at least just wants to think about n as the degree, and use n+1 as the last index. To me it seems aggressively unintuitive.

I guess you want to align the coefficient numbers but would it be a sin to define another index c = n-1 for that purpose?

But I'm a mathematical lightweight and maybe mathematical thinking is all about this. Perhaps some greater talent can correct my thinking.

notrealyme123•4mo ago
By giving it a quick read I saw that the have n data points where a polynomial of n-1 degrees provides a useful fit in the sense of this blog post.

Every field has its own language to speak. And shouting into the field from "outside" that they should change is not polite.

E.g * if you redefine c = n-1 the connection between number of points and dimension is lost. * c ist very often used as a constant Skalar. E.g as the speed of light. Using it as a dimension of a problem is quite unintuitive.

defrost•4mo ago
Fence post and rail is "off by one", two fence posts are joined by one rail, N fence posts are joined by N-1 rails, and this polynomial order and defining coefficients discussion has that in common.

Two points define a line, a polynomial of degree 1. A polynomial with 2 coefficients, ax + b.

Three points give us a quadratic, a polynomial of degree 2 with three coefficients, ax^2 + bx + c.

N points gives us a polynomial of degree N-1 with N coefficients.

Indexing coefficients by their associated power of X seems natural to some.

A(N-1).X^(N-1) + ... A(1).X^1 + A(0).X^0 (where X^0 == 1)

are the N indexed coefficients of a generic polynomial of order N-1.

pixelpoet•4mo ago
TeX tip: it's \log, not log (ditto sin, cos, etc)
raluk•4mo ago
How much is fft used for AI? Seems that attention and convolution could benefit from this.
KISHNUVADAM•4mo ago
There are architectures, such as FNO, that utilize FFTs within them. These are particularly popular in deep learning weather prediction problems.
teo_zero•4mo ago
While I do understand that O(n²) complexitity is frowned upon, I wonder how big should n be before n² multiplications are worse than nlogn loops which include several complex multiplications, complex exp, and various array reshapes...