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Deep learning still at least doubles every two years, it can be estimated by https://scholar.google.com/citations?user=kukA0LcAAAAJ https://scholar.google.com/c
by account73466 7y ago
Deep learning still at least doubles every two years, it can be estimated by https://scholar.google.com/citations?user=kukA0LcAAAAJ https://scholar.google.com/citations?user=kukA0LcAAAAJ .
- amelius 7y agoBut how do you estimate the quality of those publications? Is knowledge about DL exploding, or is it saturating?
- account73466 7y agoThis 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.
- xamuel 7y agoSounds 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.
- account73466 7y ago"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.
- xamuel 7y agoBy 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.
- account73466 7y ago>> 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.
- wuliwong 7y ago>Don't attack people on HN. Don't attack people on HN.
- account73466 7y agoTrue. I edited it to be nicer.
- amelius 7y agoBut I suppose that the amount of citations can be large even if the underlying research outcomes approach a horizontal asymptote.
- account73466 7y agoIt 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.
- asdfman123 7y agoOne 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?
- account73466 7y ago"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.
- asdfman123 7y agoHonest 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.
- ed312 7y agoPretty rare at your average non-tech company. Increasingly common as you get into major regional tech hubs and software as the product companies.
- account73466 7y agoI 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-machine-learning-papers/ 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.
- wuliwong 7y agoWhat do you mean by "Deep learning still at least doubles?"
- account73466 7y agosee here http://data-mining.philippe-fournier-viger.com/too-many-machine-learning-papers/ http://data-mining.philippe-fournier-viger.com/too-many-mach...