I understand semantic segmentation but it's been a while since I've tinkered in the computer vision space. Can you explain the push for panoptic segmentation and why you think it's a valuable technology? What can it accomplish that really good semantic segmentation can't?

Love it. I tried to come up with something like this myself but never found the time or extra help I'd need to implement it. Glad to see someone has done all the hard work!

You'll probably be dead long before you get a chance to be disappointed, so at least there's that.

Like someone said, this is r/science, not r/futurism or something. This is science and is fine the way it is.

Well to be fair, the act of weaving is specifically for making tiny strips into long ropes. Maybe they just need a super small weaver?

Also, carbon nanotubes have utility beyond being cables.

Run it through some denoisers like a VAE or something! But honestly, if you have labeled data, it should be able to handle noise just fine, especially if the features are evident.

This could probably be done without machine learning... but why bother? Machine learning is great!

I did something similar once, but I wrote code to turn the waveforms into composite images, then just ran those through an image classifier since all I had to do was repurpose a previous object recognition project that used Keras.

Tons of ways this can be done, just experiment!

Nice, I was just researching this topic. Does this touch on CI/CD and other late stage deployment and testing issues?

That's some good advice. I'm more interested in doing similar work in a green tech field, so I guess I'll focus more on the SWE skills. I don't necessarily want to limit the scope of what I apply to just yet. I'm sure if I poke around and pretend like I can't do my job otherwise, I can get some funding allocated to an IRAD project just for me. Should be able to swing a "mock cloud infrastructure for future ML/AI development." Plus, it'll probably help them out in the long run. The gov is both incredibly long and short sighted sometimes. "We want AI, it's the future, we want to invest in it for the next two decades" along with "wait, you need computers to do AI?"

I'm not excited about staying where I am for that long, but that whole "write your own ticket" part might be worth the time.

I guess I'm just not sure where my market is. This job was literally called "Machine Learning Engineer," and their description had all the things I was looking for. Not sure if it was a bait and switch or if I need to be looking for certain terms or job titles.

Not really aiming at big tech. I guess I should have clarified that, my mistake. If you know MLOps, you know stuff like Apache Spark, Databricks, etc are part of the ML pipeline. I agree, it isn't very ML, but that's what they keep asking for.

Eh, I've had 3 interviews so far and that's what they want. I've got lots of experience with data wrangling, model development, etc, but I keep hitting that wall of, "we use AWS and need someone to help with the production side of things."

I'm signed up for a lot of training courses, specifically GCS and AWS, so maybe I'll have more luck once I've completed them. There's still the issue of getting practical experience, but I'll figure it out at some point.

I've been doing ML work for the government in a research position. I've been trying to break out and get into commercial ML, but not having CI/CD and cloud experience is basically gatekeeping me. I can't get away from the military and into green tech no matter what I do. Very frustrating.