Live data from Hacker News

Munich 1991: The Roots of the Current AI Boom

people.idsia.ch

21–30 of 108 posts

Re: Munich 1991: The Roots of the Current AI Boom

#21
post #3

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…

and you still need tons of money

Re: Munich 1991: The Roots of the Current AI Boom

#22
post #8

Earlier quoted context omitted.

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 simi…

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

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.

Re: Munich 1991: The Roots of the Current AI Boom

#24
post #3

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…

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.

Re: Munich 1991: The Roots of the Current AI Boom

#25
post #3

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…

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.

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.

Re: Munich 1991: The Roots of the Current AI Boom

#27
post #24
post #3

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…

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 ea…

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.

Re: Munich 1991: The Roots of the Current AI Boom

#28

Also see Schmidhuber's take on the Hinton + Hopfield Nobel prize: https://people.idsia.ch/~juergen/physics-nobel-2024-plagiari...

[flagged]

well, so you think, all parts and peoples of USSR were voluntarily part of USSR?

Re: Munich 1991: The Roots of the Current AI Boom

#29

Earlier quoted context omitted.

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

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.

> 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.

Re: Munich 1991: The Roots of the Current AI Boom

#30
post #25

Earlier quoted context omitted.

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.

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.

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