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Deep learning job postings have collapsed in the past six months

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Re: Deep learning job postings have collapsed in the past six months

#191

Post by voces »

Tepix wrote: post #169
AznHisoka wrote: post #144

According to data from Revealera.com, if you normalize the data, the % of job openings that mention 'deep learning' has actually remained stable YoY: https://i.imgur.com/sDoKwD0.png * Revealera.com crawls job openings from over 10,000 company websites and analyzes them for technology trends for hedge funds.

That was my suspicion as well. Btw. I don't like twitter's new feature that prevents everyone from responding to a tweet that was used by @fchollet. It no longer feels like twitter if you can't engage.

Once you reach 100k followers, you only need a 0.1% jerk rate, to always have a 100 people in your comment section that do nothing but troll, rile you up, or demand you defend your thoughts against their stupid uninformed disagreements. Chollet has 210k followers.

Re: Deep learning job postings have collapsed in the past six months

#192

Post by datameta »

AznHisoka wrote: post #144

According to data from Revealera.com, if you normalize the data, the % of job openings that mention 'deep learning' has actually remained stable YoY: https://i.imgur.com/sDoKwD0.png * Revealera.com crawls job openings from over 10,000 company websites and analyzes them for technology trends for hedge funds.

Disingenuous framing of data or a laughably fundamental misreading of it? This is akin to trying to gain insight from a bunch of data on a map that simply has a strong correlation with population density.

Re: Deep learning job postings have collapsed in the past six months

#194

Post by DenisM »

voces wrote: post #191
Tepix wrote: post #169

Earlier quoted context omitted.

That was my suspicion as well. Btw. I don't like twitter's new feature that prevents everyone from responding to a tweet that was used by @fchollet. It no longer feels like twitter if you can't engage.

Once you reach 100k followers, you only need a 0.1% jerk rate, to always have a 100 people in your comment section that do nothing but troll, rile you up, or demand you defend your thoughts against their stupid uninformed disagreements. Chollet has 210k followers.

> demand you defend your thoughts against their stupid uninformed disagreements.

And I shall use this pulpit to demand, in a mixture of derision and righteous anger, that you defend your comme... ah never mind.

This may not be a new thought, but it's eloquently put. Thank you.

Re: Deep learning job postings have collapsed in the past six months

#195

Post by proverbialbunny »

siliconvalley1 wrote: post #138
mritchie712 wrote: post #78

Earlier quoted context omitted.

Great point. Not as good point: is looking for pytorch and tf the right measure?

In his tweet I thought he made it clear he wasn't predicting an AI specific slowdown but a universal recession due to Covid?

He's wrong and using not the best data for such an assertion.

Data science jobs are not slowing down, though they're not really increasing either.

In comparison since 2016 software engineering jobs revolving around building up systems for data scientists have increased 6 fold, maybe even more since I last looked.

Re: Deep learning job postings have collapsed in the past six months

#196

Post by bluetwo »

PragmaticPulp wrote: post #46
eric_b wrote: post #28

I've worked in lots of big corps as a consultant. Every one raced to harness the power of "big data" ~7 years ago. They couldn't hire or spend money fast enough. And for their investment they (mostly) got nothing. The few that managed to bludgeon their map/reduce clusters in to submission and get actionable insights discovered... they paid more to get those insights than they were worth! I think this same thing is ha…

Ironically, I worked on a product that had a classic use case for machine learning during this time period and still had great difficulty getting results. It was difficult to attract top ML talent no matter how much we offered. Everyone wanted to work for one of the big, recognizable names in the industry for the resume name recognition and a chance to pivot their way into a top role at a leading company later. Meanw…

I find your post kind of interesting. I develop software in a non-AI field and have been following and experimenting with AI on the side for a long time. Academics seem intent on publishing papers, not finding solutions to creating value. Corporate AI seems focused on sizzle not substance.

It is so frustrating to see the potential in the AI world and realize almost no one is really interested in building it.

Re: Deep learning job postings have collapsed in the past six months

#197

Post by softwaredoug »

There's a lot of what I call "model fetishism" in machine learning.

Instead of focusing our energies on the infrastructure and quality of data around machine learning, there's eagerness to take bad data to very high-end models. I've seen it again and again at different companies, usually always with disastrous consequences.

A lot of these companies would do better to invest in engineering and domain expertise around the problem than worry about the type of model they're using to solve the problem (which usually comes later, once the other supporting maturity pieces are in place)

Re: Deep learning job postings have collapsed in the past six months

#198

Post by tarsinge »

eric_b wrote: post #28

I've worked in lots of big corps as a consultant. Every one raced to harness the power of "big data" ~7 years ago. They couldn't hire or spend money fast enough. And for their investment they (mostly) got nothing. The few that managed to bludgeon their map/reduce clusters in to submission and get actionable insights discovered... they paid more to get those insights than they were worth! I think this same thing is ha…

The problem I see is that in most non tech businesses they are not at the stage where they need ML, they are simply struggling with the basics: being able to seamlessly query or have consolidated up to date metrics and dashboards of the data scattered in all their databases. Of course the Big Data/AI “we’ll transform your data into insights” appealed to them, but that’s not what they need (also see the comments on the Palantir thread the other day).

Re: Deep learning job postings have collapsed in the past six months

#199

Post by jldugger »

xmprt wrote: post #177
jon_richards wrote: post #129

Earlier quoted context omitted.

Any sufficiently misunderstood algorithm is indistinguishable from AI.

In my AI class in college, we learned about first order logic. To me it didn't seem like we were really learning AI but I couldn't quite put my finger on it. I guess it's because it made too much sense so in my mind it couldn't be AI.

This is basically a form of the AI effect[1]:

> The AI effect occurs when onlookers discount the behavior of an artificial intelligence program by arguing that it is not real intelligence.

[1]: https://en.wikipedia.org/wiki/AI_effect

Re: Deep learning job postings have collapsed in the past six months

#200

Post by fhennig »

bluetwo wrote: post #196
PragmaticPulp wrote: post #46

Earlier quoted context omitted.

Ironically, I worked on a product that had a classic use case for machine learning during this time period and still had great difficulty getting results. It was difficult to attract top ML talent no matter how much we offered. Everyone wanted to work for one of the big, recognizable names in the industry for the resume name recognition and a chance to pivot their way into a top role at a leading company later. Meanw…

I find your post kind of interesting. I develop software in a non-AI field and have been following and experimenting with AI on the side for a long time. Academics seem intent on publishing papers, not finding solutions to creating value. Corporate AI seems focused on sizzle not substance. It is so frustrating to see the potential in the AI world and realize almost no one is really interested in building it.

I agree that it's a shame that many research results do not get to be "industrialized" and actually used, but also I feel like many research results are created in such a sterile way that they wouldn't be applicable to real world scenarios.

I think what we got really good at is "perceptive" ML, like speech and image recognition, and those things do see industry applications, like self-driving cars or voice assistants.

I'd be interested to know where you see unrealized potential.

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