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AI is not written, AI is trained using dataset, PyTorch, and lot of computer time (and manpower). Dataset is not a big problem (if you can speak, you can creat

• qchris 6y ago
  Depending on the architecture, though, it's possible to export the trained model into a stand-alone file that can be imported by somebody else's program, de-coupling the network's training data from model it produces. This is done pretty frequently in areas like computer vision and speech recognition, with the pre-trained weights for YOLO and Mozilla Deepspeech[0] being available for download. I'm not sure if the word "open-source" totally applies here, since as you pointed out, apart from downloading the dataset source might be tought, but OP's question might be answered by having the resulting models made publicly available with the source code of the networks they used to train and deploy it? [0] https://github.com/mozilla/DeepSpeech/releases/v0.6.0 https://github.com/mozilla/DeepSpeech/releases/v0.6.0
• solidasparagus 6y ago
  > Dataset is not a big problem (if you can speak, you can create your own) That's simply not true at all. Between the scale of the data and the need to label it, datasets are usually the biggest roadblock in ML.