One thing is though that lots of deep learning is becoming simplified to the point of where anyone can do it, with tools like Azure ML studio and whatever the AWS offering is called (I forget).

Of course, there will always be a need for people with deep expertise, but unless you work in a very technical or prestigious field, how many compiler experts have you worked with?

"how many compiler experts have you worked with"

you meant CS PHDs? because it is a better analogy. My answer would be with many, because I am one of them.

Honest question: how common is this in tech hubs? Is the talent level that much higher? I work in the enterprise world and few people have advanced degrees.

I mean, I know there are some shops that are doing really advanced stuff, but I'm talking about your normal tech hub employer.

I don't think that people are ranked by talent. This is also true for academia. You don't have to be more talented than the next guy to show better results according to some metric. Right place + right time + avoid confrontations = a huge boost for your success.

See http://data-mining.philippe-fournier-viger.com/too-many-mach...

Roughly speaking, about 50k papers are published every year in arxiv/ML by perhaps 20k different researchers. Since some people still don't publish there, you may say there exists about 50k ML/AI/DL researchers.

Say 5k of them are pushing the field forward, most of them have a PhD. The remaining 45k deliver various local optimizations/adaptations, many of them don't have a PhD. Now it depends on the size of your normal tech hub employer. If it is big, then you have a few people from 5k and many from 45k. Otherwise, a few people from 45k.

I don't work in a tech hub but in a city with a world-leading university. Having worked for a local consultancy and a startup, I'd say over half of my colleagues have had technical PhDs and it's rare to meet people without at least a Masters. I now work for a remote company and it's probably closer to 65% with over 200 staff, but we are CS research oriented.

I'm currently studying a part-time MSc in CS because not having one is notable here (and being around academic people has inspired me to learn more).

PhD doesn't imply talent level is higher, just knowledge.

Pretty rare at your average non-tech company. Increasingly common as you get into major regional tech hubs and software as the product companies.

But how do you estimate the quality of those publications? Is knowledge about DL exploding, or is it saturating?

This person is the most cited scientist in machine learning (when measured by # citations per year) and is about to become the most cited scientist in the whole world. He has a lab of about 100 people and most of his works are at least good. I just provided an estimated. Once you see his citations count has saturated (probably in 5-10 years), you may guess that the hype is over.

But I suppose that the amount of citations can be large even if the underlying research outcomes approach a horizontal asymptote.

It can be. Still, he made some contribution to the progress in that field. Personally, I don't like the 'Canadian Mafia', I tend to prefer Schmidhuber.

Sounds like someone reeeeeallly good at nudging envelopes and writing grant proposals. Will be mostly forgotten a couple hundred years from now. Academic playwrights thought Shakespeare was a joke in his day.

"a couple hundred years from now" by whom? He contributed to AI, will not be forgotten by AI.

Edit: if you don't get what I mean by "not be forgotten", he will be the most cited scientist so why AI will exclude all his papers from some of its training sets (assuming that at least some stage of AI's development it will learn how humans do research)? Sounds unlikely.

By human beings. And he did not contribute to AI capable of contemplating human research like a human does, because no such AI exists yet. When it does exist (if ever), it will surely not consider this person or his hundred lab workers to have contributed to AI. It will consider them to have contributed to applied statistics.

Edit: I realized these comments might be very mean to you (assuming you're the lab director with the hundred workers). I should disclaim that what I say is something I assume is true about most people who gloat about their citation counts, but it's certainly not true about all such people, and might not be true about you. Myself, I'm a bit resentful because I'm so bad at the whole academic game, so that probably makes me quite biased.

>> assuming you're the lab director with the hundred workers

You make wrong assumptions and proceed. I am not that person and thus I don't get why you attack me personally.

While AI does not exist yet, that guy contributed to its development independently of your opinion about it.

Don't attack people on HN.

>Don't attack people on HN.

Don't attack people on HN.

True. I edited it to be nicer.

What do you mean by "Deep learning still at least doubles?"

see here http://data-mining.philippe-fournier-viger.com/too-many-mach...