Artificial Intelligence Stack Exchange
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What benefits can be got by applying Graph Convolutional Neural Network instead of ordinary CNN?

What benefits can we got by applying Graph Convolutional Neural Network instead of ordinary CNN? I mean if we can solve a problem by CNN, what is the reason should we convert to Graph Convolutional Neural Network to solve it? Are there any examples…
piratesailor
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Can non-differentiable layer be used in a neural network, if it's not learned?

For example, AFAIK, the pooling layer in a CNN is not differentiable, but it can be used because it's not learning. Is it always true?
RedRus
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Is Nassim Taleb right about AI not being able to accurately predict certain types of distributions?

So Taleb has two heuristics to generally describe data distributions. One is Mediocristan, which basically means things that are on a Gaussian distribution such as height and/or weight of people. The other is called Extremistan, which describes a…
Josiah Swaim
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How do I keep track of already visited states in breadth-first search?

I was trying to implement the breadth-first search (BFS) algorithm for the sliding blocks puzzle (number type). Now, the main thing I noticed is that, if you have a $4 \times 4$ board, the number of states can be as large as $16!$, so I cannot…
user9947
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Do self-driving cars resort to randomness to make decisions?

I recently heard someone make a statement that when you're designing a self-driving car, you're not building a car but really a computerized driver, so you're trying to model a human mind -- at least the part of the human mind that can drive. Since…
guillaume31
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Why does training an SVM take so long? How can I speed it up?

I'm trying to create and test non-linear SVMs with various kernels (RBF, Sigmoid, Polynomial) in scikit-learn, to create a model which can classify anomalies and benign behaviors. My dataset includes 692703 records and I use a 75/25%…
Panagiotis
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What are the models that have the potential to replace neural networks in the near future?

Are there possible models that have the potential to replace neural networks in the near future? And do we even need that? What is the worst thing about using neural networks in terms of efficiency?
Abaqus
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Why does Stephen Hawking say "Artificial Intelligence will kill us all"?

This quote by Stephen Hawking has been in headlines for quite some time: Artificial Intelligence could wipe out humanity when it gets too clever as humans will be like ants. Why does he say this? To put it simply: what are the possible threats…
Soham
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Why does Monte Carlo work when a real opponent's behavior may not be random

I am learning about Monte Carlo algorithms and struggling to understand the following: If simulations are based on random moves, how can the modeling of the opponent's behavior work well? For example, if I have a node with 100 children, 99 of…
kgautron
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Can an AI be trained to generate the outline of a story?

I know that one of the recent fads right now is to train a neural network to generate screenplays and new episodes of e.g. the Friends or The Simpsons, and that's fine: it's interesting and might be the necessary first steps toward making programs…
bsideswiped
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Back-of-the-envelope machine learning (specifically neural networks) calculations

There is a popular story regarding the back-of-the-envelope calculation performed by a British physicist named G. I. Taylor. He used dimensional analysis to estimate the power released by the explosion of a nuclear bomb, simply by analyzing a…
Charles
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How does Q-learning work in stochastic environments?

The Q function uses the (current and future) states to determine the action that gets the highest reward. However, in a stochastic environment, the current action (at the current state) does not determine the next state. How does Q learning handle…
redlum
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What is the difference between expected return and value function?

I've seen numerous mathematical explanations of reward, value functions $V(s)$, and return functions. The reward provides an immediate return for being in a specific state. The better the reward, the better the state. As I understand it, it can be…
user3168961
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How should I represent the input to a neural network for the games of tic-tac-toe, checkers or chess?

I've been reading a lot about TD-Gammon recently as I'm exploring options for AI in a video game I'm making. The video game is a turn-based positional sort of game, i.e. a "units", or game piece's, position will greatly impact its usefulness in that…
NeomerArcana
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Do full-text translators such as DeepL or Google Translate fall under the term "Generative AI"?

My question relates to full-text translators that are not specifically based on LLMs. My current understanding is that the term Generative AI goes beyond LLMs and that the full-text translators (especially those which are based on artificial neural…
Doc Brown
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