6

The rendering process for browsers is very well defined, and has a very rigid definite ruleset where (virtually) every accountability is noted and handled. This is not optimal for Machine Learning, which works when we have a large pool of examples, and we don't know the ruleset; it will figure it out. Even if you were to train an Neural Network to process ...


5

At the highest level, all it needs is for the various systems already discussed to incorporate code objects. If it can interpret its source code / model architecture from the formatted text objects underpinning them, can 'understand' them in terms of having a useful ML model, and alter the code with its reaction, then it can self-program. That is, the ...


4

If you pick up a textbook on Neural Networks, you'll find that the simplest examples shown are ones that just implement an AND gate or something. They're trivial, probably fewer lines of code than what you have there. The bar to be an "artificial neural network" is pretty low... it certainly isn't the case that ANN's must be incredibly complicated with ...


4

If the system claims that a piece of code has violated standards, then to be useful to the programmer, it really needs to provide more information than just a 'yes/no' classifier: you need some form of explanation about why it is claimed to be wrong. Clearly ANNs aren't much use for that. If I were tackling such a problem (and my suspicion is that a lot of ...


2

Yes, that's possible. I am working on a project in which I have to detect text in images. I did a quick search and found these two algorithms: 1. EAST: (Efficient and Accurate Scene Text Detector) I am not sure if it is based on Machine Learning. Here are some links link1 link2 explaining how to use it with an example and using tesseract to extract the ...


2

We don't know how to do that yet. The problem is one of scale: Despite many years of research into program synthesis via heuristic methods, it's still not possible to automatically create programs (e.g. via Genetic Programming (GP), Grammatical Evolution (GE) or Learning Classifier Systems (LCS)) that are thousands of lines long, whether that's for mobile ...


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