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No, I remember talking to people in defense research around that time period working on facial recognition. Please take the "sophisticated" and "state-of-the-a
by lallysingh 6y ago
No, I remember talking to people in defense research around that time period working on facial recognition.
Please take the "sophisticated" and "state-of-the-art" phrases as marketing.
- raverbashing 6y agoYeah I doubt they had RNNs 15 years ago. > "sophisticated" and "state-of-the-art" phrases as marketing^W ways of charging more money
- ganzuul 6y agoThey may have been honing datasets for 15 years.
- tomrod 6y agoWhat is "^W"?
- raverbashing 6y agoGo to a terminal, type a series of words then press Ctrl+w see what happens (not sure if it works on the Windows Shell though)
- kop316 6y agoI think it means "Exclusive or" https://en.wikipedia.org/wiki/W%5EX https://en.wikipedia.org/wiki/W%5EX This is why I am thinking that.
- BayesianDice 6y ago^W denotes Ctrl-W, the shortcut to delete the previous word for example originally in Berkley (thanks Wikipedia!) Unix-style terminals (and ^H denotes the control code for backspace, deleting the previous letter). The Jargon File's example shows how these are used for humorous effect: '"Be nice to this fool^H^H^H^Hgentleman, he's visiting from corporate HQ." reads roughly as “Be nice to this fool, er, gentleman...”, with irony emphasized.' (http://www.catb.org/~esr/jargon/html/writing-style.html http://www.catb.org/~esr/jargon/html/writing-style.html)
- tomrod 6y agoCtrl+H is maintained!
- cat199 6y agoRNN's are 80's technology at least: https://en.wikipedia.org/wiki/Recurrent_neural_network#History https://en.wikipedia.org/wiki/Recurrent_neural_network#Histo... With neural network use in image recognition (if not facial recognition) being used at least as early as 1983 (I'm not in the field, so just did 5s of research and found something related) - https://ieeexplore.ieee.org/document/6313076 https://ieeexplore.ieee.org/document/6313076 "A recognition with a large-scale network is simulated on a PDP-11/34 minicomputer and is shown to have a great capability for visual pattern recognition. The model consists of nine layers of cells. ..." another paper from 1990 using neural networks for facial sex identification: https://www.researchgate.net/publication/221619290_SEXNET_A_Neural_Network_Identifies_Sex_From_Human_Faces https://www.researchgate.net/publication/221619290_SEXNET_A_... and software facial recognition itself dates to the 60s. despite what the 'data science and AI and by AI I really only mean the subset of AI referring to ML' hypetrain tells you, these things are not new, the processors are just faster, and the tools are more accessible, which means the relevant application space is larger.
- WorldMaker 6y ago> these things are not new, the processors are just faster, and the tools are more accessible, which means the relevant application space is larger. The core to my argument that most of contemporary ML isn't new or different in an "algorithmic breakthrough" sense, but in that we've massively sped up GIGO. An AI researcher in the 60s/70s teleported to today isn't going to have a rough time figuring out what's going on, they are going to whistle in shock at how massively bloated our "sample sets" and data corpuses have grown, how fast we're churning through that data (regularly), and how much of it we are leaving unsupervised or "self-supervised", and with maybe some questions as to what we did with our (lack of) QA/QR processes along the way.
- alacombe 6y agoI was studying RNN-driven image classification 12 years ago. No doubt defense companies were waayyyy ahead of a master-degree course in an university outside the US.