11–20 of 41 posts
Algorithms doesn't seem to be the right term, this seems to be more tooling, like this wrapper for Tensorflow and YOLO training that runs a variety of monitoring tools for you: https://github.com/BMW-InnovationLab/BMW-YOLOv3-Training-Aut...
This is great. It would be good if all life-critical software was open-sourced like this. Maybe something that should in fact be required? But, ”in turn, we receive support in taking our AI software to the next level of development” I bet they are mainly looking for help. They are trying to figure out why their software is not capable to do what it is supposed to, and hoping someone can assist. I’m ready to consult t…
You’re saying I should be forced as a developer to share the code of everything I do? That sounds pretty despotic, tbh.
This is great. It would be good if all life-critical software was open-sourced like this. Maybe something that should in fact be required? But, ”in turn, we receive support in taking our AI software to the next level of development” I bet they are mainly looking for help. They are trying to figure out why their software is not capable to do what it is supposed to, and hoping someone can assist. I’m ready to consult t…
The article could be clearer on this, but when it refers to "production", I think it means factories and logistics. (At least that's how I put together "production" in the headline with "implementing next-level production processes throughout its plants" from the first sentence.)
In other words, I think they use these algorithms in manufacturing systems, and they aren't putting this software into the cars' computers.
the YoloV3 (the model that these tools are designed to work with) paper is extremely funny and worth reading for anyone who hasn't. https://pjreddie.com/media/files/papers/YOLOv3.pdf
What genre of papers does this belong to? I want to read more.
This is impressive only because they are in automotive. I worked in that industry for years, they are generally at least a decade behind the rest of the software world
the YoloV3 (the model that these tools are designed to work with) paper is extremely funny and worth reading for anyone who hasn't. https://pjreddie.com/media/files/papers/YOLOv3.pdf
> You can tell YOLOv3 is good because it’s very high and far to the left. Can you cite your own paper? Guess who’s going to try, this guy→[16]
This guy cites.
the YoloV3 (the model that these tools are designed to work with) paper is extremely funny and worth reading for anyone who hasn't. https://pjreddie.com/media/files/papers/YOLOv3.pdf
Mind blown, thanks. What genre of papers does this belong to? I want to read more.
the YoloV3 (the model that these tools are designed to work with) paper is extremely funny and worth reading for anyone who hasn't. https://pjreddie.com/media/files/papers/YOLOv3.pdf
> YOLOv3 is a good detector. It’s fast, it’s accurate. It’s not as great on the COCO average AP between .5 and .95 IOU metric. But it’s very good on the old detection metric of .5 IOU. Why did we switch metrics anyway? The original COCO paper just has this cryptic sentence: “A full discussion of evaluation metrics will be added once the evaluation server is complete”. Russakovsky et al report that that humans have a hard time distinguishing an IOU of .3 from .5! “Training humans to visually inspect a bounding box with IOU of 0.3 and distinguish it from one with IOU 0.5 is surprisingly difficult.” [18] If humans have a hard time telling the difference, how much does it matter?
> But maybe a better question is: “What are we going to do with these detectors now that we have them?” A lot of the people doing this research are at Google and Facebook. I guess at least we know the technology is in good hands and definitely won’t be used to harvest your personal information and sell it to.... wait, you’re saying that’s exactly what it will be used for??
> Oh. Well the other people heavily funding vision research are the military and they’ve never done anything horrible like killing lots of people with new technology oh wait.....
> I have a lot of hope that most of the people using computer vision are just doing happy, good stuff with it, like counting the number of zebras in a national park [13], or tracking their cat as it wanders around their house [19]. But computer vision is already being put to questionable use and as researchers we have a responsibility to at least consider the harm our work might be doing and think ofways to mitigate it. We owe the world that much. In closing, do not @ me. (Because I finally quit Twitter).
> 1 The author is funded by the Office of Naval Research and Google.
the YoloV3 (the model that these tools are designed to work with) paper is extremely funny and worth reading for anyone who hasn't. https://pjreddie.com/media/files/papers/YOLOv3.pdf
Lost it at page 4 figure 3 caption: > You can tell YOLOv3 is good because it’s very high and far to the left. Can you cite your own paper? Guess who’s going to try, this guy→[16] This guy cites.