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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

#171

Post by rurp »

laichzeit0 wrote: post #127
tachyonbeam wrote: post #88

Earlier quoted context omitted.

I worked in a place full of deep learning PhDs, and you'd have people trying to apply reinforcement learning to problems that had known mathematical solutions, and integer programming problems. I don't think the issue is just that companies hire people who are awful at ML, it's also that people are trying to shoehorn deep learning into everything, even when it currently has nothing to offer and we have better solutio…

How is this any different to developers who insist on using some shiny new web framework, micro service spaghetti and kubernates overkill infrastructure for their silly little CRUD app?

I don't think it is any different. Overvaluing the latest hotness is extremely common in the tech industry and is one of my least favorite parts of it.

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

#173

Post by emmap21 »

baron_harkonnen wrote: post #51
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…

> they paid more to get those insights than they were worth! This understates how awful ML is at many of these companies. I've seen quite a few companies that rushed to hire teams of people with a PhD in anything that barely made it through a DS/ML boot camp. To prove that they're super smart ML researchers without fail these hires rush to deploy a 3+ layer MLP to solve a problem that need at most a simple regression…

It sounds so painful as someone all-in this area. But I have to agree on a task of overdoing with fancy models. Nevertheless, the most common ML algo in industry is still linear regression along with boostraping.

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

#174

Post by xmprt »

apohn wrote: post #84
mrtksn wrote: post #61

Earlier quoted context omitted.

If you think about it, that's the natural outcome. Why? Because people in corporations don't have the incentive to benefit the business but to progress their careers and that's done through meeting the goals for their position and make their upper ups progress with their careers too. So essentially, you have a system where people spend other people's resources for living and their success is judged by making the chai…

>If you think about it, that's the natural outcome. Why? Because people in corporations don't have the incentive to benefit the business but to progress their careers and that's done through meeting the goals for their position and make their upper ups progress with their careers too. This is one of the reasons I roll my eyes whenever I read something like "McKinsey says 75% of Big Data/AI/Buzzword projects do not de…

Why do you roll your eyes? Isn't it a useful metric to know that most of the projects that are hiring these buzzword technologies are destined to fail (whether that's because the problem space wasn't fit for ML or whether management went on a hiring spree to pump their resume)?

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

#175

Post by erichocean »

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…

Without ML, our business today is literally impossible (from a financial perspective).

I work in 2D animation and we were able to design our current pipeline around adopting ML at specific steps to remove massive amounts of manual labor.

I know this doesn't disprove your anecdote, I just wanted to point out that real businesses are using ML effectively to deliver real value that's not possible without it.

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

#176

Post by data4lyfe »

mrtksn wrote: post #61
apohn wrote: post #43

Earlier quoted context omitted.

"Like Big Data, I think we'll see a few companies execute well and actually get some value, while most will just jump to the next shiny thing in a year or two." Here's another aspect - in many places nobody listens to the actual people doing the work. In my last job I was hired to lead a Data Science team and to help the company get value of Stats/ML/AI/DL/Buzzword. And I (and my team) were promptly overridden on eve…

If you think about it, that's the natural outcome. Why? Because people in corporations don't have the incentive to benefit the business but to progress their careers and that's done through meeting the goals for their position and make their upper ups progress with their careers too. So essentially, you have a system where people spend other people's resources for living and their success is judged by making the chai…

This is why almost all data scientists and ML engineers that succeed in many corporate structures are essentially "yes men".

Source: https://www.interviewquery.com/blog-do-they-want-a-data-scie...

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

#177

Post by xmprt »

jon_richards wrote: post #129
simonw wrote: post #97

Something I've learned: when non-engineers ask for an AI or ML implementation, they almost certainly don't understand the difference between that and an "algorithmic" solution. If you solve "trending products" by building a SQL statement that e.g. selects items with the largest increase of purchases this month in comparison to the same month a year ago, that's still "AI" to them. Knowing this can save you a lot of wa…

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.

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

#178

Post by stjohnswarts »

mgleason_3 wrote: post #149
apohn wrote: post #84

Earlier quoted context omitted.

>If you think about it, that's the natural outcome. Why? Because people in corporations don't have the incentive to benefit the business but to progress their careers and that's done through meeting the goals for their position and make their upper ups progress with their careers too. This is one of the reasons I roll my eyes whenever I read something like "McKinsey says 75% of Big Data/AI/Buzzword projects do not de…

OK, so, we're scientists...and we're in the middle of a pandemic...amplifying/arguing over a graph showing a steep decline in job listing...that doesn't control for the pandemic...or even include a line for "overall job loss"... https://www.burning-glass.com/u-s-job-postings-increase-four... Looks like all job postings "collapsed during the pandemic"

yeah looks like at the least you might have lines for "overall CS based jobs" and "overall tech industry" and see the same sort of fall off appears. While not all that scientific either logically if you see similaries you can cast some more doubt/support on the hypothesis that ML is special and failing. How is it doing relative to other "hyped" or even just plain technical hiring/firing trends.

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

#179

Post by stjohnswarts »

austinl wrote: post #74
apohn wrote: post #43

Earlier quoted context omitted.

"Like Big Data, I think we'll see a few companies execute well and actually get some value, while most will just jump to the next shiny thing in a year or two." Here's another aspect - in many places nobody listens to the actual people doing the work. In my last job I was hired to lead a Data Science team and to help the company get value of Stats/ML/AI/DL/Buzzword. And I (and my team) were promptly overridden on eve…

I've heard this happen in a lot of places — companies want to be "data-driven", but then leadership simply ignores the data. I think being data-driven is something that is built into company culture, or otherwise it's too easy to just ignore the results and ship. The place I currently work is data-driven (perhaps to a fault). Every change is wrapped behind an experiment and analyzed. Engineers play a major role in th…

You give them tons of data and then all you hear is "I'm gonna have to go with mah gut on this one"

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

#180

Post by Accujack »

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…

This has happened since the dawn of the computer age, and probably before.

Any technology too complex for the managers who purchase for it to understand fully can be sold and oversold by marketing people as "the next big thing".

Managers may or may not see through that, but if their superiors want them to pursue it or if they need to pursue something in order to show they're doing something of value, then they're happy to follow where the marketers lead.

Java everywhere, set top TV boxes, IOT devices, transitioning mainframes to minis, you name it... the marketers have made a mint selling it, usually for little benefit to the companies that bought into it.

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