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Pi 1.0

https://earendil.com/posts/pi-1-0/
1473•sergiotapia•18h ago•483 comments

Shimano Bicycle Museum Review

https://inrng.com/2026/10/shimano-bicycle-museum/
184•pietroppeter•8h ago•34 comments

Several vulnerabilities have been discovered in the Linux kernel

https://lwn.net/Articles/1097401/
401•luispa•14h ago•291 comments

Show HN: Audionaut – an open-source cross-platform multitrack audio editor

https://github.com/kvoltmer/Audionaut
56•vltmrkls•5h ago•19 comments

Clef: Open-weight decision models, and new RL fine-tuning platform

https://blog.cloudflare.com/clef-decision-models/
551•jasondavies•21h ago•195 comments

SvelteKit 3

https://svelte.dev/blog/sveltekit-3-is-here
334•sampsn•17h ago•137 comments

DeepSeek Harness Desktop for macOS and Windows

https://www.deepseek.com/en/harness/
291•Kuyawa•10h ago•150 comments

Pi Durable

https://earendil.com/posts/pi-durable/
427•paulsmith•18h ago•56 comments

Ask HN: Who is hiring? (October 2026)

225•whoishiring•22h ago•217 comments

Frog and Toad and the Increasingly Capable Machines

https://www.frogandtoad.ai/
275•supermdguy•15h ago•63 comments

Git 3.0's upcoming SHA-256 default will be a costly mistake

https://blog.gitbutler.com/git-3-sha-256
444•chmaynard•20h ago•414 comments

Automatic Transmission – a data-privacy study of connected vehicles

https://automatictransmission.khoury.northeastern.edu/index.html
212•rafaelc•17h ago•182 comments

StreetComplete on iOS is now in public beta

https://github.com/streetcomplete/StreetComplete/issues/5421
587•Snowly•1d ago•160 comments

Turbo Haskell

https://comonad.com/reader/2026/turbo-haskell/
134•pjmlp•23h ago•28 comments

Using Opus 5.5 to discover a new eyewitness record of the dodo

https://resobscura.substack.com/p/using-opus-55-to-discover-a-new-eyewitness
178•benbreen•16h ago•51 comments

RIP, vector database

https://turbopuffer.com/blog/rip-vector-database
349•razin•21h ago•99 comments

Various Projects Find Hidden SDR Capabilities in ESP32 Microcontrollers

https://www.rtl-sdr.com/various-projects-independently-find-hidden-sdr-capabilities-in-esp32-micr...
249•nkw•22h ago•47 comments

Vote on which of Hacker News' challenges for AI have been met

https://stoppels.ch/goalposts/
172•stabbles•20h ago•199 comments

CSS Bed: Classless CSS themes to use as starting points in web development

https://www.cssbed.com
128•sea-gold•16h ago•36 comments

Show HN: Janus – Go binary that runs GGUF models via Vulkan on AMD/Intel/Nvidia

https://github.com/Vibra-Ingenn/Janus
83•Maverick617•16h ago•14 comments

ArXiv's Updated Rate Limit Policy

https://blog.arxiv.org/2026/10/01/updated-rate-limit-policy/
134•50kIters•17h ago•67 comments

Cloudflare K2: serverless event streams

https://blog.cloudflare.com/cloudflare-k2-streams/
255•elffjs•23h ago•100 comments

How Singapore's government-run dating service works

https://www.singapore-samizdat.com/p/how-singapores-government-run-dating-service-firstdate-works
206•danielfoster•11h ago•199 comments

Oxygen-deprived underwater zones may not be “dead zones” but clue to early life

https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2026AV002570
114•gumby•18h ago•16 comments

Memory executives expect RAM shortage to continue through 2028

https://arstechnica.com/information-technology/2026/10/memory-supplies-are-only-getting-tighter-m...
8•el_duderino•1h ago•2 comments

Butterflies use optical illusions to dodge predators

https://www.essex.ac.uk/news/2026/09/30/butterflies-use-optical-illusions-to-dodge-predators
66•gmays•14h ago•12 comments

Context Language Models

https://arxiv.org/abs/2609.37725
156•emersonmacro•22h ago•42 comments

How to speed up the Rust compiler in September 2026

https://nnethercote.github.io/2026/09/30/how-to-speed-up-the-rust-compiler-in-september-2026.html
261•trickypr•1d ago•150 comments

RacketCon Is Saturday

https://con.racket-lang.org/
153•spdegabrielle•22h ago•41 comments

GPT-Synopsys: Frontier Intelligence to Revolutionize Chip Design

https://news.synopsys.com/2026-09-30-OpenAI-and-Synopsys-Announce-GPT-Synopsys-Frontier-Intellige...
185•giuliomagnifico•1d ago•109 comments
Open in hackernews

Harvard particle physicist Matthew Schwartz drops 36 papers authored with Claude

https://www.reddit.com/r/Physics/comments/1wvin77/harvard_particle_physicist_matthew_schwartz_drops/
37•xqcgrek2•1h ago

Comments

phoghed•1h ago
A very high number of Redditors think they know more/better than a Harvard professor and dismiss him out of hand. May someone grant us all a measure of their confidence.
eieje12•57m ago
Brand names don’t mean much anymore.

Three words: Cambridge, Jason Arday.

f6v•44m ago
Stanford, Marc Tessier-Lavigne.
sdcfgy•43m ago
As Cambridge alumni, that one hurt when it happened. You're not wrong.
sickofparadox•15m ago
At Harvard itself, Claudine Gay.
glitchc•49m ago
Appeal to authority is a logical fallacy. Each paper will need to be judged on its own merits, irrespective of the source.
sdcfgy•41m ago
From my own experience, I'm not sure that is necessarily the case. Retraction Watch is also an interesting read.

I suspect there will be citations galore shortly, faster than anyone can think.

goalieca•41m ago
Well, many of us in Hackernews lived through grad school. We’ve seen the games. May our AI lords enshittify things even more.
iLoveOncall•31m ago
It's extremely likely that a very high number of Redditors do actually know more/better than a Harvard Particle Physics professor on the topics on which he published papers, which include ecology, health, economy, geology, etc.

This is literal slop.

b3lvedere•27m ago
Is this the same as the infinite monkeys with infinite typewriters eventually writing Shakespeare theory?
iLoveOncall•25m ago
No, because the monkeys do end up writing the work correctly. There's absolutely no guarantee that any of those papers are correct in any way.

It literally is just spam, and nothing else.

It's like the Nobel disease: https://en.wikipedia.org/wiki/Nobel_disease

b3lvedere•21m ago
Thanks. Amazing examples in that weblink.
ToValueFunfetti•19m ago
?

Surely, this is not correct. The monkeys are drastically less likely to produce valid words; the set of monkeys that produce valid words are much less likely to produce valid sentences, etc. etc. Very low bar to clear, but of course this is vastly better than infinite monkeys at producing good research.

oefrha•30m ago
As a former hep-th guy from a very reputable institution I was ready to at least skim and briefly evaluate 36 particle physics papers. Turns out most of them have nothing to do with physics. It takes a special kind of personality to have the hubris to publish in so many domains at once, and most Harvard/Princeton/etc. physicists I know would probably be critical of this. Not that the disapproval would mean much.

(I did learn much of my QFT from Schwartz’s QFT textbook though, so I hold him in higher regard than <insert random Harvard Physics prof here>.)

parthdesai•28m ago
Isn't HN similar, albeit with even more confidence?!
phoghed•7m ago
Yeah but I’ve earned it by learning JavaScript
d--b•27m ago
The professor co-wrote 36 papers (40+page each) with Claude on things ranging from clinical trials, to shared authorship between Shakespeare and the Bible, to decyphering the Voynich Manuscript.

I didn't read the papers, and I am no specialist in any of the fields that guy meddles in, but it really does sound too good to be true. And if not, well, we're entering a new era of humanity right now.

stingraycharles•23m ago
Too good to be true, or an accurate reflection of the unfortunate state of the world right now?
d--b•20m ago
what do you mean?
_the_inflator•26m ago
Remedial Math - I love it.

Wisdom of the crowd has finally proven to be more valuable than some obscure title in academia. Crowds are relentless and ruthless, kind of a red team instead of a cronyism.

PS: The infamous replication crisis deserves a honorable mention here.

well_ackshually•23m ago
"50 year old tenured teacher that slaps his name on literally everything his students put out believes he's uniquely qualified to criticize hegelian dialectics" is a headline you can read approximately every year in academia. He's out of his zone, with absolutely zero ability to review his "research" nor credibility to push it out.

May someone grant me an ounce of his hubris and I'll become president of the united states. And I'm not even a citizen.

mcphage•21m ago
> A very high number of Redditors think they know more/better than a Harvard professor and dismiss him out of hand.

How many different fields would you imagine a Harvard professor to be an expert in?

LadyCailin•59m ago
Can you just not use Reddit at all anymore without the app?
jjice•57m ago
I generally can on Safari on iOS. Sometimes I have to force desktop mode. They're making it very difficult...
nicce•55m ago
They just closed all public APIs, including RSS. Time to leave the ship soon.
Narishma•45m ago
You can use a web browser.
vlyan•45m ago
on desktop, it's going to be usable for a while longer if you can access old.reddit.com. they've finally set their sights on killing it off though.

on mobile, it's cancer like the rest of the internet, unapologetically growth-hacked with shit like "warning!!1 mature content!!1 log in with official reddit app to keep our community safe" modal you get regardless of which benign subreddit you try to browse.

cma•36m ago
You can use old reddit on mobile, use Firefox and ublock origin to hide the sidebar or videos get clipped wrong.
program_whiz•59m ago
Is this actually good? Seems like they created a new tool that allows LLM to do a lot of numerical analysis. The papers seem somewhat legit? https://bootloops.ai/papers.html

I suppose if this framework allows physics and other sciences to rapidly progress (e.g. publish more findings), that is good? It destroys a certain model we had, that science should be arduous and require a genius many years of work to uncover something, but if these papers truly add knowledge via this new tool, then this is for the good.

Not sure implications for researchers, but from the public perspective, now we have 36 new papers that increase our knowledge. But maybe an expert can weigh in, the papers might be slop?

softwaredoug•55m ago
I think we can only say we are forwarding human knowledge if a human understands the content they’re putting out in the world. I don’t know if that applies in this case, it I think it’s an important bar to clear.
program_whiz•39m ago
Yes but people doing research will be asking LLMs to review many papers prior to their reading most likely. If more humans come to understand the findings of these papers, then its good right?

I guess on a theoretical level, if you had a button which would create breakthroughs in a field, but you yourself couldn't understand it, would you push it? I would because otherwise the field may not discover it, and others will be able to understand the breakthrough.

cma•35m ago
As long as AI engineers understand it when they put it to use that shouldn't matter for the practical aspects. Most people already don't understand physics or engineering. It's just keeping the models aligned that's the big issue.
bananaflag•57m ago
If AI is so good at research then maybe instead of people researching comparatively easy problems which only get you a publication, they will research problems that matter. (I'm not dismissing here problems just because they are "easy" or "not practical", I am sure that there are a ton of worthwile ones among those, I am dismissing just those which are artificial and only researched out of publication incentives.)
bluGill•25m ago
AI is only good at a subset of problems. However in that subset it is often very good. There is a lot of "low hanging fruit" in that subset and we can learn a lot quickly by having AI work in that area.

We do of course need to watch for hallucinations, but I in general expect AI to be very good at theoretical physics. AI can take a lot of known equations and prove/propose (these are different things!) generalizations to that may or may not match reality. AI can suggest experiments to see if the predictions match the real world. Maybe string theory can finely make a non-trivial prediction that we can test in the real world...

However AI is terrible for other parts of physics (at least so far) and those are also important we shouldn't lose track of them despite the excitement that we can get from progress in things AI is good at.

bananaflag•11m ago
> AI is only good at a subset of problems.

I wouldn't count on that to last in any area.

lp4v4n•48m ago
I once read the criticism that science is already moving too fast and that wrong results get published and accepted as true because nobody reaps any laurels for verifying or reproducing results, even if that's an indispensable part of the scientific method.

Now in the age of AI this problem will be heavily accentuated. Who's going to review the quality and validity of dozens and dozens of papers being generated by a researcher who used to publish sporadically?

It's not hard to see science going through a "slop crisis" in the next few years, in the same way that now projects are getting inundated with PRs.

f6v•41m ago
> nobody reaps any laurels for verifying or reproducing results

That's not entirely true. There's a whole genre of "response" and "response to response" papers that voice concerns when there's a methodological issue. That's somewhat common in my fields (computational biology and biomedical research).

And even if a "response" isn't published, people still try to reproduce published techniques if those seem useful.

geerlingguy•25m ago
A lot of useful studies take weeks, months, or years to do the first time, and require a staff, a grant, etc. at least in medicine, physics, chemistry...

You'd be surprised how rarely (overall) reproduction / verification is attempted. Sadly, a lot of research is taken at face value. That's done quite often with AI/tech stuff these days, and even more so for scientific research. It's a hard problem.

coliveira•38m ago
Which is interesting because the solution should be obvious: use AI to reproduce results and test what's published, instead of using bogus AI to publish more bogus results.
kps•37m ago
Did he drop them because they were hallucinated, or did he millennial-drop them? I still can't tell.
guessmyname•22m ago
“Drops” as in “Releases”, not “Retracts”.

I was confused too. Whoever wrote the title(s) doesn’t know a second language, otherwise, they would have realized how confusing that was, even to native English speakers.

delichon•8m ago
Maybe he should be "sanctioned".
dataengineer56•37m ago
"drops" is unclear here - it could mean either "publishes" or "retracts"
frereubu•32m ago
Reminds me of this - https://statmodeling.stat.columbia.edu/2026/08/27/258/ - which I think was on HN at some point in the last week. The fact that (according to another comment here) these papers were in areas outside his specialism, and therefore things he doesn't have the domain knowledge to critique, makes me think we're going to see more of this special kind of madness that seems to have some kind of grandiosity at its heart. It really does feel like some people are falling hard for plausibility rather than rigour.

Edit: the papers do seem to have other names on them, and he says that all papers "were reviewed by humans for accuracy", but I still think there's a very serious risk of people being gulled into okaying something that's plausible rather than rigorously checking everything. There's enough human-generated slop in science already!

seydor•29m ago
Anus Mirabilis
glimshe•15m ago
Well, he sure met his papper publishing quota for the year.
amelius
•
42m ago
We need xcancel but for reddit.
lovelymono•28m ago
Something like https://github.com/redlib-org/redlib?
gradstudent•49m ago
who is going to parse and distill these AI generated papers? who is going review them even? Science without humans isn't science
program_whiz•41m ago
I see the point, but also if these papers provide proof that human can eventually use, or another AI system can use to make further progress, then is it for the best? A great deal of academic papers are drivel couched in dense language and prose to obfuscate the lack of substance. So far, humans rely on search engines and heuristics to avoid wasting time and energy on them. Now, humans are already using LLMs to assist in reading and understanding papers, so perhaps it still contributes to knowledge.
sourdecor•25m ago
Scientific progress only requires the scientific method, not humans being in-the-loop.
coliveira•35m ago
I believe the bar for publication should be "can this be understood by (expert) humans". If that's not the case, it may even be true, but who cares? It's not improving knowledge, which is by definition human understanding.
Gigioingiro•38m ago
I agree, will be interesting to see the evolution. I know notable sources from the US academia that points to the problem since way before the AI, even if the they are from human science and economics, don't know much about the STEM status. Accordingly, the first slop crisis got a big hit with the initial woke wave in the mid 2000', then another hit during COVID, in which thousands of pointless papers about the effect where produced and an immense amount of research effort was towards it, and now AI. Science will keep progressing, even at a faster piece, the real problem will be to justify the work and output of thousand of people and researcher that currently need a salary. It may be that the academia will adjust to split between professionals focused on the pure teaching skill, while the research and publication aspect of academia will go to have much higher barriers and restricted to less people. Relevant publication will not become a standard requirement for a successful academic career but also teaching skills.
vanviegen•23m ago
Yeah, science needs to reinvent itself.

How about this: instead of going through publishers, researchers are required (by their funding organizations) to put a bounty on falsifying the result (for, say, 10 years). The higher the bounty, the higher the 'impact factor'. Put your money where your mouth is. A bounty of at least the cost of the study should be expected for serious research.

I can imagine a 'falsification insure' industry. They'd look at reputation as well as employ people close to the subject matter to asses risk, taking over the role of peer review. But with aligned incentives.

This way researchers and institutions who don't care too much about truth are marginalized; they either have low impact factors or they'll need to pay huge falsification insure fees.

And researchers who are sceptical of certain results will have an incentive (money!) to try to replicate it.

Remaining question: who is the authority on whether a publication has been falsified?