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by pdimitar
2054 days ago
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> This may not result in new widgets next CES but may be game changing to society in a decade. And I am tired of hearing that ever since the 90s. Clearly, deep fakes changed society. Made people more paranoid and less believing of what they see. Is that a positive change though? Meanwhile, you still have to manually load dishes in the dishwasher, and robot vacuum cleaners stumble and block on the easiest of obstacles. Call me a cynic but AI work needs to get out of its comfy well-funded bro-club corner and start to seriously try and solve real-actual-physical-world problems. It's all well and good that scientist X can model a text paragraph with this or that NN but when will he solve a car driving itself? And don't get me wrong. I know science can take a long time to make a breakthrough. It's not adhering to the same laws as everyday work -- I am aware and I am clamouring for science. But I don't feel the AI area is even heading in any direction at all. Could be wrong though. |
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If you just read the "AI" comment sections on HN it may seem everybody is just training a cat/dog classifier in Keras on ImageNet and nothing new is going on. In reality there's tons of work in one-shot/few-shot learning, unsupervised, self-supervised methods, combining modalities, quantifying uncertainty, robustness to attacks, etc.
Yes, robotics is still not at the stage where you could get a human-like dexterous dishwashing/T-shirt folding machine. But people are working on it as well.
However, not all companies need it. The "comfy well-funded bro-club corner" (why so much envy in the phrasing?) probably does not need physical robots, they just do data analysis, like if you need to process videos uploaded to Youtube, or you program an intelligent tool for photo or video editing software, that's also important and has nothing to do with robotic arms.
I think it's the fault of the media that "AI" appears as this single conceptual blur, when it's actually tons of different applications. It is capable of a lot more than 1-2 decades ago. But it's not AGI, and not everyone needs to work on human-like/conversational AGI in a humanoid body.
Image analysis, machine translation, speech recognition, all these work today at least to some extent and just a short time ago they just did not work at all outside extremely carefully crafted cases in prototypes that fell apart immediately when the researcher wasn't there to keep it from collapsing (I mean this metaphorically: the predictions were extremely bad outside the scenario and dataset it was crafted for).