# Artificial Intelligence Stack Exchange Community Digest

## Top new questions this week:

### Do we need automatic hyper-parameter tuning when we have a large enough dataset?

Hyperparameter tuning is the process of selecting the optimal hyperparameters for an ANN. Now, my guess is that, if we have sufficient data (say, 1.4 million for, say, 6 features), the model can be ...

neural-networks hyperparameter-optimization training-datasets

### What are the roles of the prior $\mathrm{p}(\mathbf{z})$ in a VAE?

I know the encoder is variational posterior $q_{\phi}(\mathbf{z} \mid \mathbf{x})$. I also know that the decoder represents the likelihood: $p_{\theta}(\mathbf{x} \mid \mathbf{z})$. My question is ...

generative-model variational-autoencoder

### What is the place of ontologies in artificial intelligence?

Very much a general question here, from a somewhat uneducated perspective. I'm currently part way through an MSc in AI, and at the minute I am taking a module on Knowledge Engineering and ...

ai-design ontology knowledge-based-systems

### How to train neural networks with multiprocessing?

I am trying to figure out how multiprocessing works in neural networks. In the example I've seen, the database is split into $x$ parts (depending on how many workers you have) and each worker is ...

### Demonstration of AI-powered Mario collecting lots of coins?

As part of a talk I'm giving, I'd like to show one of the many videos on YouTube where an AI is playing Mario, such as this one. What bothers me though is that the AI is trying to complete the level ...

reinforcement-learning game-ai atari-games

### In layman terms, what does "attention" do in a transformer?

I heard from many people about the paper titled Attention Is All You Need by Ashish Vaswani et al. What actually does the "attention" do in simple terms? Is it a function, property, or some ...

neural-networks papers transformer attention

### What are the major layers in a Vision Transformer?

Currently, I am studying deepfake detection using deep learning methods. Convolution neural networks, recurrent neural networks, long-short term memory networks, and vision transformers are famous ...

neural-networks deep-learning transformer layers vision-transformer
 asked by Pawara Siriwardhane 1 vote

## Greatest hits from previous weeks:

### What is the credit assignment problem?

In reinforcement learning (RL), the credit assignment problem (CAP) seems to be an important problem. What is the CAP? Why is it relevant to RL?

reinforcement-learning definitions credit-assignment-problem

### What is the difference between an agent function and an agent program?

In section 2.4 (p. 46) of the book Artificial Intelligence: A modern approach (3rd edition), Russell and Norvig write The job of AI is to design an agent program that implements the agent function — ...

terminology comparison norvig-russell

### How to choose an activation function for the hidden layers?

I choose the activation function for the output layer depending on the output that I need and the properties of the activation function that I know. For example, I choose the sigmoid function when I'm ...

neural-networks deep-learning activation-function hyperparameter-optimization hyper-parameters

### Why do we need common sense in AI?

Let's consider this example: It's John's birthday, let's buy him a kite. We humans most likely would say the kite is a birthday gift, if asked why it's being bought; and we refer to this reasoning ...

philosophy agi knowledge-representation commonsense-knowledge

### How do I show that uniform-cost search is a special case of A*?

How do I show that uniform-cost search is a special case of A*? How do I prove this?

comparison search proofs a-star uniform-cost-search

### What is the Bellman operator in reinforcement learning?

In mathematics, the word operator can refer to several distinct but related concepts. An operator can be defined as a function between two vector spaces, it can be defined as a function where the ...

reinforcement-learning terminology math bellman-equations bellman-operators

### Audio enhancing using AI? (removing background noise during lecture recording)

I wonder if it's possible to 'clean up' an audio recording of a lecture from a smartphone, using some type of AI system?

deep-learning

## Can you answer these questions?

### When is an object detection approach over a CNN approach appropriate?

I understand that CNNs are for image classification while object detection is for localization + classification of the objects detected. However, in particular, AI for chest radiographs, why is object ...

neural-networks convolutional-neural-networks object-detection applications
 asked by Hi There 1 vote

### How to detect the sine wave signal with different frequency using neural networks?

I'm wondering if there is a way to use a neural network that can detect the noisy sine wave, where the frequency is not constant. In other words, I'm not looking for a solution that would detect the ...

neural-networks algorithm-request signal-processing