YHK - yet another hacker news clone

Brand names don’t mean much anymore.

Three words: Cambridge, Jason Arday.

Appeal to authority is a logical fallacy. Each paper will need to be judged on its own merits, irrespective of the source.

Well, many of us in Hackernews lived through grad school. We’ve seen the games. May our AI lords enshittify things even more.

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.

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>.)

Isn't HN similar, albeit with even more confidence?!

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.

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.

"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.

> 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?

I generally can on Safari on iOS. Sometimes I have to force desktop mode. They're making it very difficult...

They just closed all public APIs, including RSS. Time to leave the ship soon.

You can use a web browser.

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.

We need xcancel but for reddit.

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.

who is going to parse and distill these AI generated papers? who is going review them even? Science without humans isn't science

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.

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.

> 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.

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.

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.

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?

“Drop” as in “Released”, not “Retracted”.

I was confused too. Whoever wrote the title(s) doesn’t know a second language, otherwise, they would not have written such a confusing headline.