To put it more simply, people with academic credentials should not demand acknowledgement of their current intellectual work while denigrating and ridiculing the importance of very similar work done in the past.
And that's where Schmidhuber goes off the rails: publicly shaming published papers into citing you isn't good academic practice. It's bullying.
You can't claim independence from past work simply because you didn't look directly at it. The job of an academic researcher is to know the landscape of relevant ideas, where they come from, where they're going, and to hopefully contribute a few new good ones.
Citation chains should extend back from your work, along a reasonable line conceptual inheritance, back to a reasonable point of origin. Schmidhuber has different definitions for both of these reasonables than the bulk of the ML research community, to a point that makes him difficult to satisfy.
For example, take a look at Albert Einstein's Google Scholar profile. He's not the top cited physicist. Not even close. It's because other researchers don't explicitly cite his papers. https://scholar.google.com/citations?user=qc6CJjYAAAAJ&hl=en...
Same with Tim Berners-Lee and the World Wide Web. Imagine if his original paper were cited every time someone deployed a web site.
If I’m in the private sector, and I rediscover something from first principles, it is not my responsibility to go search all academia to see if someone’s done it before so I can cite their work.
If I rely on a code library that doesn’t explicitly cite papers it was built on, it is also not my responsibility to go find all the papers that it might’ve been built from and cite those papers.
Spamming citations is unnecessary.
Eh, I think the correct answer is: read it, then cite it.
You're not really supposed to cite something without reading it, as it might say something different than you think. But sure, citing it w/o reading it is better than not citing it at all.
But if you build on them you should have read them. I don't know about the specifics and I don't know if Schmidhuber is out of line or not, and citations and impact factors are a terrible mess, but generally speaking, you are responsible for finding and reading and citing any related work that needs to be cited, and if you work on neural networks in an academic context you probably have been forced to read that particular one at some point. Citation obligations don't just disappear because you don't want to do the research.
What you're referring to is the "development" part of that. In some sense: the job you have _exists precisely because it's not part of the research phase_, and it's equally as valuable as the research part. Research is the proof of concept; development is scaling up and making production-ready and finding small efficiencies and so on.
From an industry perspective, it's tempting to conflate these, because that's what industry research labs are designed to do: integrated R&D. But that is not at all how academic research labs work.
Soon we will also blame academia for not providing iOS and android apps
The goal of academia isn't to be practical, "only" learning.
Many ideas come from philosophy, which many find useless.
Heraclitus discovered change back in ancient Greek, I don't know where we would be in scientific research without that (deliberately ignoring the debate about the originality of what we know about Heraclitus work). I bet his contemporaries found his "research" useless.
The closest to that that I've seen is that traditional academia approaches are too far removed from practical applications for highly applied fields like software engineering, or too slow for fast-moving fields like modern day ML (thus, all the preprints).
I used to work at Nokia Research when they still made phones. Probably the closest thing Europe had to Silicon Valley twenty years ago. Except it was in Helsinki. Lots of stuff got invented there. Nokia didn't really manage to capitalize on its own inventions of course. Or rather it got caught up in its own clumsy attempts throwing babies out of the window by the bucket load. But others sure did. A lot of modern smart phones still have tech in them that Nokia pioneered before either Google or Apple shipped a smart phone.
At the time there was a lot of talk about the demise of industrial research labs. Bell labs (now actually owned by Nokia!), Xerox PARC, IBM, and all the other big US labs that produced amazing stuff are former shadows of themselves. There is some truth in that
But you could argue that Google and Apple picked up some of the slack. And the current AI boom came out of Google cherry picking all the best universities for their AI talent and putting them all together in a research group that then got free reign. Like Nokia, that involved a lot of ejecting of babies with the bath water. But it seems to have spawned lots of new startups that can trace their roots back to that research group in Google.
You don't know ahead of time, where the breakthrough will come from.
There is ton of research that sits on the shelf, and then years later, it gets re-combined with some other useless research, and boom, some big breakthrough.
This current attitude of all research is worthless, so it should be cancelled, is shooting our future selves in the face.
Just as the Dewey Decimal System really only served the purpose of providing the facetious nominal linearization of an arbitrary depth ontological oversimplification, so too humans are much more like random pattern matching machines than festidious sense-makers glued to absolutes derived from false appeals to static mono-perspective ontological hierarchies. The same is becoming lived experience in the LLM age, although the tiktokked youth apparently cannot string ten words together or focus longer than three seconds to attest, I'd wager they can feel it. Are we losing something by rejecting the habit of rigorously manually tending to spurious and temporary ontologies? Yes. Is it necessarily a loss in the long term? Probably not, in the same way we no longer write long-form letters or leave calling cards. Are we gaining something in response? Yes, at a minimum much stronger cross-pollination between ivory towers by fearless exploratory pragmatists who disrespect the would-be scope of nominal professions in favor of holistic thinking... both AI and human.
[0] https://en.wikipedia.org/wiki/Science_and_Civilisation_in_Ch...
Practically no one is against hard science research, properly conducted. The issues are rampant fraud / p-hacking / unreproducible garbage mixed with an unhealthy dose of ideological monoculture and indoctrination, garnished with rising tuition prices while sitting on huge endowments in case of the Ivy Leagues.
As long as you do that with your own money (or money got freely given from other people), sure.
If you use taxpayer money, that's a different game.
However I often see this going from "there's issues" to discounting academia altogether and positioning private labs as a good or only alternative.
After all, most people in the open science collaboration which published the seminal paper kicking off the replication crisis were from academia.
Eh, I grew up conservative evangelical, and they were pretty much always going to have a problem with research in evolution and astronomy. Same goes for the fossil fuel industry w.r.t. climate science.
When the scientific evidence interferes with religious doctrine or industrial paycheck, then yeah, folks are still going to have a problem with hard science research.
Well... that's "starve the beast" in action. A lot of things we take for granted, that underpin our modern ways of life, came to be due to government investing. Laser, radar, microwaves, the early Internet, that all was military R&D.
"Unfortunately" (well, for the rich and the MIC, at least) there is no way for people to siphon off money in government-funded research, so once the libertarian/small-state BS completely took over following the collapse of the USSR, a lot of that got torn down or supplemented with enough bureaucracy to make Germans cry... and that's why reusable rockets were not invented at NASA but at SpaceX instead.
https://en.wikipedia.org/wiki/Jet_Propulsion_Laboratory
> Founded in 1936 by California Institute of Technology (Caltech) researchers, the laboratory is now owned and sponsored by NASA and administered and managed by Caltech.
Minimum-Landing-Error Powered-Descent Guidance for Mars Landing Using Convex Optimization http://larsjamesblackmore.com/BlackmoreEtAlJGCD10.pdf
Elon originally wanted parachutes and was convinced by Lars to go with self landing rockets.
Unfortunately, as the early history of SpaceX shows, it required a lot of failures to learn from to design the current crop of rockets. And that's the advantage that private R&D has... as long as the person in charge has money, failure is an option, because in anything publicly funded, any failure will relentlessly be blamed on the currently governing party by the opposition.
If sentiment on HN were as you say, how could your pro-academia and anti-big tech comment be sitting at the top as the most upvoted comment?