[jcattle]

There's this crowd on HN which is very vocal against academia. From what I've seen, the main points are that academia isn't efficient, most of the science coming out of academia is useless and that the whole system is just a waste of taxpayers money. Instead, what is often argued, all good research is done in private labs. Then pointing to SpaceX, Moderna, OpenAI, Google, etc.

And while it is very true that often the research coming out of Academia is useless, what is always neglected are the roots of the research done in private labs.

When Jürgen Schmidhuber and team published their work on Neural Nets back in 1991 it was also useless. Unless you had a supercomputer and very, very deep pockets you were not going to do anything with what came out of their lab.

But still, 30 years later here we are, standing on top of the shoulders of this useless research.

[yorwba]

Like half of what Schmidhuber is always complaining about is that (except for LSTMs) people aren't standing on the shoulders of his research very much. They try to solve some of the same problems people have always wanted to solve, try some of the same approaches people always tend to try, and then tinker until it works. At no point do they consult Schmidhuber's decade-old papers where he tried something kind of similar but didn't get very impressive results, and hence they also do not think to cite him. Then he comes out of the woodwork to assert priority.

[suddenlybananas]

You can be influenced downstream by papers you haven't personally read.

[bonzini]

Shane Legg was in Schmidhuber's lab at IDSIA before being one of the founders of DeepMind, so he probably read the papers personally and knows what influenced him or not...

[gillesjacobs]

Of course, but if you haven't read them you also shouldn't cite them.

And that's where Schmidhuber goes off the rails: publicly shaming published papers into citing you isn't good academic practice. It's bullying.

[psb217]

"if you haven't read them you also shouldn't cite them" -- this is wildly incorrect in an academic context. If I'm using ResNets, I should cite the original ResNet paper, even if I haven't read it. If I'm using Transformers, I should cite the original Transformer paper, even if I haven't read it. If my work is a direct extension of method B, and method B is a direct extension of method A, I should cite the source of A, even if I haven't read it.

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.

[dividedbyzero]

> Of course, but if you haven't read them you also shouldn't cite them.

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.

[elorant]

I do a lot of work that is based on academic research, aka building a proprietary sparse embedding model. My issue with academia is that they don’t bother to solve the practical issues. They tell you how to build a PPMI model, but what about hitting a database that’s 500TB to find co-occurrence numbers? This isn’t even touched so you’d then have to go and invent a bazillion of algorithms yourself to make your life easier. So while the bedrock is based on academic research and we thank them for that, scaling anything requires a lot of work in uncharted territories.

[jhbadger]

But that isn't the purpose of academia -- the purpose of it is to discover new phenomena not to make products. It is true that there is a lot of work to turn a new advance into a product whether it is software or turning biological knowledge into a drug, but without discovery of new phenomena new products will come to a halt. While it is true that some corporate labs, most famously Bell Labs in its heyday, but also for example IBM's T.J. Watson and Xerox's PARC did do basic research besides product-focused work, this is pretty rare because it is hard to justify the cost of something that may only be practical in decades and often help your competitors as much as yourself.

[ACCount37]

Where is "this crowd" that you are talking about?

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).

[wolfi1]

and you still need tons of money

[tcp_handshaker]

I think most of criticism of academia is about the rampant fraud and unreproducible results, due to the way the incentives are structured.

[MrBuddyCasino]

This is a straw-man if I ever saw one.

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.

[jcattle]

Yes all good points showing issues that academia has at the moment.

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.

[MrBuddyCasino]

Yes there is no substitute for academia. Monopolist's research labs get close (Bell Labs etc), but they tend to be more "applied".