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It's not impossible. But there is a very real gap between "this is cool in a research paper" and "this is deep learning that works in real life". It's a large
by huffmsa 6y ago
It's not impossible. But there is a very real gap between "this is cool in a research paper" and "this is deep learning that works in real life".
It's a large gap, covering everything from application topics, to data quality, to the need to actually run the damn think in a production setting with scalability, availability, error handling, etc.
Production applications of deep learning aren't particularly glamorous, they're not the "next big thing" right now. Rather they're improvements of existing applications.
Google's on device live captioning works really well, but still somewhat niche, and requires special / higher end SoC's to run.
- hejja 6y agomakes sense. thanks. models I have used seem to have their usefulness greatly outweighed by performance demands. scaling and economics are another question entirely. Perhaps we were spoiled with democratized web tech and it's wishful thinking to want everything to be that.
- huffmsa 6y agoIt will get there eventually. A lot of it is hardware / deployment constrained. Search by image and object detection and computer vision in general is cool and potentially useful, but right now, it's cumbersome as fuck to pull out your phone, find the Lens application, take a picture etc. Needs to be baked into a wearable / neuralink type setup. But self driving applications of CV work because the cameras are always deployed and running. But the hardware is expensive.