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Start all of your commands with a comma

https://rhodesmill.org/brandon/2009/commands-with-comma/
140•theblazehen•2d ago•41 comments

OpenCiv3: Open-source, cross-platform reimagining of Civilization III

https://openciv3.org/
667•klaussilveira•14h ago•202 comments

The Waymo World Model

https://waymo.com/blog/2026/02/the-waymo-world-model-a-new-frontier-for-autonomous-driving-simula...
949•xnx•19h ago•551 comments

How we made geo joins 400× faster with H3 indexes

https://floedb.ai/blog/how-we-made-geo-joins-400-faster-with-h3-indexes
122•matheusalmeida•2d ago•32 comments

Unseen Footage of Atari Battlezone Arcade Cabinet Production

https://arcadeblogger.com/2026/02/02/unseen-footage-of-atari-battlezone-cabinet-production/
53•videotopia•4d ago•2 comments

Show HN: Look Ma, No Linux: Shell, App Installer, Vi, Cc on ESP32-S3 / BreezyBox

https://github.com/valdanylchuk/breezydemo
229•isitcontent•14h ago•25 comments

Jeffrey Snover: "Welcome to the Room"

https://www.jsnover.com/blog/2026/02/01/welcome-to-the-room/
16•kaonwarb•3d ago•19 comments

Monty: A minimal, secure Python interpreter written in Rust for use by AI

https://github.com/pydantic/monty
222•dmpetrov•14h ago•117 comments

Vocal Guide – belt sing without killing yourself

https://jesperordrup.github.io/vocal-guide/
26•jesperordrup•4h ago•16 comments

Show HN: I spent 4 years building a UI design tool with only the features I use

https://vecti.com
330•vecti•16h ago•143 comments

Hackers (1995) Animated Experience

https://hackers-1995.vercel.app/
493•todsacerdoti•22h ago•243 comments

Sheldon Brown's Bicycle Technical Info

https://www.sheldonbrown.com/
381•ostacke•20h ago•95 comments

Microsoft open-sources LiteBox, a security-focused library OS

https://github.com/microsoft/litebox
359•aktau•20h ago•181 comments

Show HN: If you lose your memory, how to regain access to your computer?

https://eljojo.github.io/rememory/
288•eljojo•17h ago•169 comments

An Update on Heroku

https://www.heroku.com/blog/an-update-on-heroku/
412•lstoll•20h ago•278 comments

Was Benoit Mandelbrot a hedgehog or a fox?

https://arxiv.org/abs/2602.01122
19•bikenaga•3d ago•4 comments

PC Floppy Copy Protection: Vault Prolok

https://martypc.blogspot.com/2024/09/pc-floppy-copy-protection-vault-prolok.html
63•kmm•5d ago•6 comments

Dark Alley Mathematics

https://blog.szczepan.org/blog/three-points/
90•quibono•4d ago•21 comments

How to effectively write quality code with AI

https://heidenstedt.org/posts/2026/how-to-effectively-write-quality-code-with-ai/
256•i5heu•17h ago•196 comments

Delimited Continuations vs. Lwt for Threads

https://mirageos.org/blog/delimcc-vs-lwt
32•romes•4d ago•3 comments

What Is Ruliology?

https://writings.stephenwolfram.com/2026/01/what-is-ruliology/
43•helloplanets•4d ago•41 comments

Where did all the starships go?

https://www.datawrapper.de/blog/science-fiction-decline
12•speckx•3d ago•4 comments

Introducing the Developer Knowledge API and MCP Server

https://developers.googleblog.com/introducing-the-developer-knowledge-api-and-mcp-server/
59•gfortaine•12h ago•25 comments

Female Asian Elephant Calf Born at the Smithsonian National Zoo

https://www.si.edu/newsdesk/releases/female-asian-elephant-calf-born-smithsonians-national-zoo-an...
33•gmays•9h ago•12 comments

I now assume that all ads on Apple news are scams

https://kirkville.com/i-now-assume-that-all-ads-on-apple-news-are-scams/
1066•cdrnsf•23h ago•446 comments

I spent 5 years in DevOps – Solutions engineering gave me what I was missing

https://infisical.com/blog/devops-to-solutions-engineering
150•vmatsiiako•19h ago•67 comments

Why I Joined OpenAI

https://www.brendangregg.com/blog/2026-02-07/why-i-joined-openai.html
149•SerCe•10h ago•138 comments

Understanding Neural Network, Visually

https://visualrambling.space/neural-network/
287•surprisetalk•3d ago•43 comments

Learning from context is harder than we thought

https://hy.tencent.com/research/100025?langVersion=en
182•limoce•3d ago•98 comments

Show HN: R3forth, a ColorForth-inspired language with a tiny VM

https://github.com/phreda4/r3
73•phreda4•13h ago•14 comments
Open in hackernews

What Comes After Science?

https://www.science.org/doi/10.1126/science.aec7650
33•porteclefs•2mo ago

Comments

tech_ken•2mo ago
> With the emergence of AI in science, we are witnessing the prelude to a curious inversion – our human ability to instrumentally control nature is beginning to outpace human understanding of nature, and in some instances, appears possible without understanding at all.

A while ago I read "Against Method" by Paul Feyerabend and there's a section that really stuck with me, where he talks about the "myth" of Galileo. His point is that Galileo serves as sort of the mythological prototype of a scientist, and that by picking at the loose ends of the myth one can identify some contradictory elements of the popular conception of "scientific method". One of his main points of contention is Galileo's faith in the telescope, his novel implementation of bleeding edge optics technology. Feyerebend argues that Galileo invented the telescope as primarily a military invention, it revolutionized the capabilities of artillery guns (and specifically naval artillary). Having secured his finances with some wealthy patrons, he then began to hunt for nobler uses of his new tool, and landed on astronomy.

Feyerabend's point (and what I'm slowly working up to) is that applying this new (and untested) military tool to what was a very ancient and venerable domain of inquiry was actually kind of scandalous. Up until that point all human knowledge of astronomy had been generated by direct observation of the phenomenon; by introducing this new tool between the human and the stars Galileo was creating a layer of separation which had never been there before, and this was the source of much of the contemporary controversy that led to his original censure. It was one thing to base your cosmology on what could be detected by the human eye, but it seemed very "wrong" (especially to the church) to insert an unfeeling lump of metal and glass into what had before been a very "pure" interaction, which was totally comprehensible to the typical educated human.

I feel like this article is expressing a very similar fear, and I furthermore think that it's kind of "missing the point" in the same way. Human comprehension is frequently augmented by technologly; no human can truly "understand" a gravitational wave experientially. At best we understand the n-th order 'signs' that the phenomenon imprints on the tools we construct. I'd argue that LLMs play a similar role in their application in math, for example. It's about widening our sensor array, more than it is delegating the knowledge work to a robot apprentice.

mjamesaustin•2mo ago
Fascinating point, and one I think can definitely apply here.

Though there is a key difference – Galileo could see through his telescope the same way, every time. He also understood what the telescope did to deliver his increased knowledge.

Compare this with LLMs, which provide different answers every time, and whose internal mechanisms are poorly understood. It presents another level of uncertainty which further reduces our agency.

spongebobstoes•2mo ago
LLMs can be deterministic machines, you just need to control the random seeds and run it on the same hardware to avoid numerics differences.

Gradient descent is not a total black box, although it works so well as to be unintuitive. There is ongoing "interpretability" research too, with several key results already.

nahuel0x•2mo ago
Deterministic doesn't necessarily mean that can be understood by an human mind. You can think about a process entirely deterministic but so complex and with so many moving parts (and probably chaotic) that a humble human cannot comprehend.
tech_ken•2mo ago
> Though there is a key difference – Galileo could see through his telescope the same way, every time.

Actually this is a really critical error- a core point of contention at the time was that he didn't see the same thing every time. Small variations in the lens quality, weather conditions, and user error all contributed to the discovery of what we now call "instrument noise" (not to mention natural variation in the astronomical system which we just couldn't detect with the naked eye, for example the rings of Saturn). Indeed this point was so critical that it led to the invention of least-squares curve fitting (which, ironically, is how we got to where we are today). OLS allowed us to "tame" the parts of the system that we couldn't comprehend, but it was emphatically not a given that telescopes had inter-measurement reliability when they first debuted.

graemep•2mo ago
I have been meaning to read Feyerband for a while but never did. I think Against Method sounds like a good starting point.

Did Feyerband also not argue that Galileo's claim that Copernicus's theory was proved was false given it was not the best supported hypothesis by the evidence available at the time.

I very much agree with your last paragraph. Telescopes are comprehensible.

tech_ken•2mo ago
> Did Feyerband also not argue that Galileo's claim that Copernicus's theory was proved was false

My reading of AM was that it's less about what's "true" or "false" and more about how the actual structure of the scientific argument compares to what's claimed about it. The (rough) point (as I understand it) is that Galileo's scientific "findings" were motivated by human desires for wealth and success (what we might call historically contingent or "poltical" factors) as much as they were by "following the hard evidence".

> Telescopes are comprehensible.

"Comprehensible" is a relative measure, I think. Incomprehensible things become comprehensible with time and familiarity.

pnathan•2mo ago
There was an attitude at a University about 20 years ago when I was an undergrad, around, hmm, stochastic learning algorithms. And the attitude was, "we don't care why or how it works - we want to make the outcome happen".

I found it intellectually reprehensible then, and now.

timoth3y•2mo ago
> "we don't care why or how it works - we want to make the outcome happen".

That's the primary difference between science and engineering.

In science, understating how it works is critical, and doing something with that understanding is optional. In engineering getting the desired outcome is critical, and understanding why it works is optional.

Razengan•2mo ago
Blindness?
nancyminusone•2mo ago
To be pedantic, engineering.
amelius•2mo ago
Philosophy
gmuslera•2mo ago
By some perspective, what made us unique was our ability to have a hint on the future, pattern recognition, superstition, religion and then science gave us a grasp of the outcome of what happens in a future, usually after an action by ourselves. Things are of bad luck, or a sin, or should not be done because some negative outcome. So, following that line of thinking, what will come next are better predictive capabilities, taking more out of guessing or "this is random" and more deterministic. Think in psichohistory telling what will happen with cultures and civilizations for centuries giving the current state of things.

Anyway, the "we have AI, so will be soon no more things to discover" is similar to what was thought at the end of the XIX century that everything was discovered and only increasing precision was left. At the very least, we have a lot of learning about ourselves and how we understand reality, in the light of what AI could uncover with different methods than the traditional ones.

MangoToupe•2mo ago
> So, following that line of thinking, what will come next are better predictive capabilities

You can also view science as a rejection of the ability to be able to predict (arbitrary) things. Any illusion otherwise is simply seemingly reliable knowledge of the past and present. The rise of eg disinformation and misinformation, siloed communication, the replication crisis could presage a future where confidence is generally lower than the past, and predictive power is more limited.

I caution heavily against the idea that what you perceive as "progress" is inevitable or will follow past trends

gmuslera•2mo ago
Reality is complicated. The future may be unknowable from a strict point of view. But educated guesses are better than just random. Not for lotto numbers, but to take better decisions. Deciding that everything is potentially false, biased, or unreliable and so doing whatever your guts (that are also biased) tell you may have a worse outcome.
quickening•2mo ago
> XIX century

I’m curious. Why did you write it this way vs. “19th”? People from 400 AD to 1400 AD used to write it that way. I’m assuming you’re either very old or a history buff.

gmuslera•2mo ago
Or a human that does the LLM trick of recalling how the first reference I've read about that was written.
adgh•2mo ago
> With the emergence of AI in science, we are witnessing the prelude to a curious inversion – our human ability to instrumentally control nature is beginning to outpace human understanding of nature, and in some instances, appears possible without understanding at all.

This is not entirely new. For example, we had working (if inefficient) steam engines and pumps long before the development of thermodynamics. We had beer and cheese long before microbiology.

metalman•2mo ago
I think it's probably best to wait until we get to science, and then figure out an after.
tim333•2mo ago
I guess after AI figures out how many r's there are in Strawberry it'll move on to quantum gravity.
johnea•2mo ago
The whole article seemed a little tautological to me.

You could say: Scientific advances have massively accelerated with the use of the new tool of electricity, but there are serious concerns about the "black-box" nature of electricity, since no one has ever answered the question "what is charge?".

Modern semiconductors depend on quantum effects that no one has ever "explained", but they are highly repeatable, and make useful predictions that can be confirmed.

My expectation is that every advance cited in the article, and attributed to LLMs, is in fact the output of a team of human scientists using LLMs as a tool to expand their scope and increase productivity.

All of these examples are actually human endeavors.

The only qualitative difference I see, is that LLMs are a human invention, whereas electricity and quantum effects are natural phenomenon that were discovered, and utilized as a tool, by humans.

While LLMs, and subsequent s/w advances, may well lead us into new, even unexpected, realms of science, the need to be able to confirm repeatable results and verify the accuracy of predictions, will always be necessary.

As such, I would still call this science, not "after"...