I have seen ML and big data crowd out remote openings though.
Deep learning job postings have collapsed in the past six months
241–250 of 274 posts
Re: Deep learning job postings have collapsed in the past six months
#242According 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.
If only we could apply ML/AI to the data on ML/AI job postings.
Re: Deep learning job postings have collapsed in the past six months
#243Most data-related problems, or extraction of knowledge from data, simply doesn't benefit from Deep Learning. In my experience, what many organizations lack is simple but high-quality "Business Analytics": Reporting & dashboards are developed that look good but jam too much information together. It is often the wrong information: Something is requested, and the developer develops exactly what was asked. The problem is…
I think we’re starting to see peak managerialism. The latest wave in stats has shown more than anything that a significant shortfall in basic statistics knowledge makes it almost impossible to make good decisions with vast amounts of data.
Without the skillsets to work with and then understand that data, they are forced into this long process of asking for data to be put into reporting and dashboards and then once they finally get them, either fixating on the limited metrics it provides while being oblivious to other context not in front of them, or to instead forced to start another long iteration to adjust that reporting and dashboards.
We’ve gone almost 30 years believing management was the sole skill required to manage teams and companies, but dealing with the new era of data is starting to show the limits
Re: Deep learning job postings have collapsed in the past six months
#244I'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…
There's also a lot of deception going on.
The easiest way to solve many problems is through lexers, regular expressions and plain-old pattern matching. But that doesn't sell, so, they call it AI anyways.
Re: Deep learning job postings have collapsed in the past six months
#245Earlier quoted context omitted.
> big data That's because it didn't get a chance to mature and to show how it could be powerful. People kept trying to force hadoop into it and call themselves "big data experts" We've gotten a bit more clarity in this world with streaming technologies. However, there hasn't been a good and clear voice to say "hey .. this is how it fits in with your web app and this is what you expect of it". (I'm thinking about deve…
These days it's people trying to force Kafka into it and call themselves "streaming experts"
Kafka is good.. but it requires a lot of good work to get it working well for a pipeline.
Re: Deep learning job postings have collapsed in the past six months
#246I'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 is sadly so consistent with what I'm seeing at a big corporation. We are working so hard to make a centralized ML platform, get our data up to par, etc. but so many ML projects either have no chance of succeeding or have so little business value that they're not worth pursuing. Everyone on the development team for the project I'm working on is silently in agreement that our model would be better off being replac…
I think part of the problem here is that ML development is extraordinarily more expensive then traditional dev.
I don't generally need to develop my own deployment infrastructure for every new project. However I've yet to see an ml team or company consistently use the same toolchain between 2 projects. The same pattern repeats across data processing, model development, and inference.
Oddly, adding more scientists appears to have a super-linear increase in cost - with the net effect being either duplicated effort or exhaustive search across possible solutions.
Re: Deep learning job postings have collapsed in the past six months
#247According 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.
I think the fact the original tweet was not normalized in this incredibly obvious way is at least one valid reason companies could use less deep learning folk
The original tweet is one of the authors of TensorFlow (specifically Keras, a large section of the API for v2), if it's any indication of the quality of the framework.
Re: Deep learning job postings have collapsed in the past six months
#248Earlier 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 exactly describes my experience with self driving cars
Re: Deep learning job postings have collapsed in the past six months
#249The way I see it, only those companies that had already been using a data oriented approach to business can really reap the benefits of ML. From a company's point of view, ML/AI should be a natural evolution of an existing tool set to better solve problems they have been trying to solve in the past using deterministic methods and then statistical methods, etc. Any other project that is diving right into ML is likely…
Yeah, you really shouldn't conform data to the problem. It's more an emergent silver gun than a constructed silver bullet.
Re: Deep learning job postings have collapsed in the past six months
#250Earlier 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…
This exactly describes my experience with self driving cars
Can you share more details?