Questions tagged [applications]

For questions about applications of Artificial Intelligence (and Machine Learning) algorithms.

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Why do Convolution Neural Networks work on NLP/sequential tasks?

I have read some articles where people use 1D CNN for NLP tasks like sentiment analysis. My questions are, given that CNNs are largely used for images, how/why does this work on sequences/NLP tasks? ...
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Usability of power series in AI analysis

In mathematics, power series is given by $$f(x) = \sum\limits_{n=0}^{\infty} c_n (x-a)^n$$ where $c_n , a \in \mathbb{R}$ Although most of the courses in academics cover moment generating functions in ...
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How can AlphaZero be used in other industries besides gaming?

I'm an AI Engineering student from Belgium and I'm writing my bachelor thesis on the creation of a chess computer with deep reinforcement learning based on AlphaZero. My implementation can be found ...
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How is AI used in Internet of Things?

I would really appreciate it if someone would explain how AI is used in IoT. In the papers that I have found, half of the paper itself is about what IoT is and very few information about how AI is ...
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What are the state-of-the-art AI methods to recognize elements on webpages or the purpose of webpage?

I'm curious to know about the capabilities of AI today in 2022. I know that AI has become pretty good at recognizing things like objects in photos. But what about when it comes to elements in HTML? ...
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Example of games in reinforcement learning where no model is available? [duplicate]

I'm reading the Sutton & Barto's book "Reinforcement Learning: An Introduction" (2nd Edition), as the classes I took were a long time ago, and I'm struggling to understand this part (p. ...
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How to represent multiple-output logic circuits in tree-based genetic programming

Consider the following digital logic circuit, which has multiple inputs and one output: The logic circuit above can be represented in tree form: This tree representation could then be used in a tree-...
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Does reaching the global optima guarantee good performance in a task?

It is to my understanding that, in deep learning, we are essentially trying to minimize the loss function that we have defined and reach its global optima through some form of optimization technique. ...
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What are some applications of virtual try-on other than in the fashion industry?

I've been considering doing research in virtual try-on technology. There are various computer vision techniques that go into this, but I was wondering if there is any potential application of virtual ...
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Is there any simple example for volumetric data except from physics and medicine?

Recently I heard about the term volumetric data. The definition for volumetric data is as follows #1: Definition Volumetric data is typically a set S of samples $(x, y, z, v)$, representing the value ...
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Do any practical deep learning algorithms deal with tensors containing non-real entries?

In deep learning, most of the applications are from text and images. Both text and images can be converted into a tensor of real numbers. Other than both mentioned above, there may be some other real-...
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Can AI be used for grading code copy exercises and adjust difficulty based on these scores?

I'm a senior in a bachelor Multimedia and Creative Technology. My experience is mostly full-stack web app development. For my bachelor's thesis, I need to do research in a subject I have no experience ...
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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 ...
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Usecases where pretrained models are used without retraining

I was starting out with deep learning and come across a lot of pretrained models in frameworks and sites such as tensorflow model zoo. Are these models actually used by other developers in real use ...
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1 answer
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When should we use CNN instead of MLP?

Is CNN only applicable to time-series data or image data? When should we use CNN instead of MLP?
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Where to start with reinforced learning on actions and rewards sampled from slow ongoing real life system

I would like some pointers, possible projects that solve conceptually similar goals, code examples or tutorials. I am trying to achieve a system that is able to start or stop ventilation of a given ...
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How can GPT-3 be used for designing electronic circuits from text descriptions?

I was wondering if it is possible to use GPT-3 to translate text description of a circuit to any circuit design language program, which in turn can be used to make the circuit. If it is possible, what ...
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What are the practical problems where full bayesian treatment is affordable?

Suppose, I have a problem, where there is rather a small number of training samples, and transfer learning from ImageNet or some huge NLP dataset is not relevant for this task. Due to the small number ...
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3 votes
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Can Reinforcement Learning be used to generate sequences?

Can we use reinforcement learning for sequence-to-sequence tasks? If yes, whether or not this is a good choice, how could this be done?
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Are there any successful applications of transformers of small size (<10k weights)?

In the problems of NLP and sequence modeling, the Transformer architectures based on the self-attention mechanism (proposed in Attention Is All You Need) have achieved impressive results and now are ...
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What's up with Neural Stochastic Differential Equations from a practical standpoint?

I've spent a few days reading some of the new papers about Neural SDEs. For example, here is one from Tzen and Raginsky and here is one that came out simultaneously by Peluchetti and Favaro. There are ...
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9 votes
2 answers
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What are the biggest barriers to get RL in production?

I am studying the state of the art of Reinforcement Learning, and my point is that we see so many applications in the real world using Supervised and Unsupervised learning algorithms in production, ...
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4 votes
1 answer
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Is non-negative matrix factorization for machine learning obsolete?

I am taking a course about using matrix factorization for machine learning. The first thing that came into my mind is by using the matrix factorization we are always limited to linear relationships ...
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What are the fundamental differences between VAE and GAN for image generation?

Starting from my own understanding, and scoped to the purpose of image generation, I'm well aware of the major architectural differences: A GAN's generator samples from a relatively low dimensional ...
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1 answer
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Can you use machine learning for data with binary outcomes?

I am totally new to artificial intelligence and neural networks and have a broad question that I hope is appropriate to ask here. I am an ecologist working in animal movement and I want to use AI to ...
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What is Grenander's pattern theory?

I came across Grenander's work "Probabilities on Algebraic Structures" recently, and I found that much of Grenander's work focused on what he called "Pattern Theory." He's written ...
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Can we use transformers for audio classification tasks?

Since transformers are good at processing sequential data, can we also use them for audio classification problems (same as RNNs)?
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1 answer
636 views

What kind of problems is DQN algorithm good and bad for?

I know this is a general question, but I'm just looking for intuition. What are the characteristics of problems (in terms of state-space, action-space, environment, or anything else you can think of) ...
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What are the use-cases of self-replicating neural networks?

I started researching the subject of self-replication in neural networks, and unexpectedly I saw that there is not much research on this subject. I should mention I am new in the field of NNs. This ...
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Are there any meaningful books entirely written by an artificial intelligence?

Are there any meaningful books entirely written by an artificial intelligence? I mean something with meaning, unlike random words or empty books. Something that can be charactersed as fiction ...
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1 answer
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What is a "learned emulator"?

In this article, the term "learned emulator" is used. Recently, scientists have started creating "learned emulators" using AI neural network approaches, but have not yet fully ...
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Why is domain adaptation and generative modelling for knowledge graphs still not applied widely in enterprise data? What are the challenges?

I see that domain adaptation and transfer learning has been widely adopted in image classification and semantic segmentation analysis. But it's still lacking in providing solutions to enterprise data, ...
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What are examples of problems where neural networks have achieved human-level or higher performance?

What are examples of problems where neural networks have been used and have achieved human-level or higher performance? Each answer can contain one or more examples. Please, provide links to research ...
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What are some other real-life examples of simple policies but complex value functions?

Hado van Hasselt, a researcher at DeepMind, mentioned in one of his videos (from 7:20 to 8:20) on Youtube (about policy gradient methods) that there are cases when the policy is very simple compared ...
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1 vote
1 answer
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Are neural networks really used apart from specific hi-tech organisations?

This is a generic question. Still posting it to get insights from experts in the field. I am interested in knowing if Neural Networks are used in general apart from specific hi-tech organizations. If ...
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4 votes
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What is the scope of real-world deep learning applications in 2020?

2015 was a milestone year for AI--"deep learning" was validated in a very public way with AlphaGo. However, at the time, the question was raised: "What else is deep learning good for?&...
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4 votes
1 answer
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How do AIs like Siri and Alexa respond to their names being called?

AIs like Siri and Alexa respond to their names being called. How does the system recognize the name by ignoring all the other words that have been said before their name? For example, "Hey Siri&...
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5 votes
1 answer
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Can GANs be used to generate something other than images?

AFAIK, GANs are used for generating/synthesizing near-perfect human faces (deepfakes), gallery arts, etc., but can GANs be used to generate something other than images?
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How is depth perception (e.g. in autonomous driving) addressed without using a Lidar or Radar unit?

For practical applications, like autonomous driving, depth perception is needed to make useful decisions. How is this normally addressed without using a LIDAR or RADAR unit (but using a camera)?
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2 votes
1 answer
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Do transformers have success in other domains different than NLP?

Everybody knows how successful transformers have been in NLP. Is there known work on other domains (e.g that also have a sequential natural way of occurring, such as stock price prediction or other ...
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Creating 4k HDR video from 720p footage

So, my company recently bought a big 4k HDR TV for our reception, where we keep showing some videos that were originally shot/created at 720p resolution. Before this, we had a relatively small HD TV, ...
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1 answer
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What are the real applications of hierarchical temporal memory?

What are the real applications of hierarchical temporal memory (HTM) in machine learning (ML) these days?
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Is there an AI system that, given a patient's symptoms, produces a diagnosis and suggests a treatment?

Is there an AI system (preferably, one that interacts with the human, such as a chatbot like this one) that, given some input (e.g. entered into the system by writing text), such as a person's ...
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1 answer
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Is there any practical application of knowing whether a concept class is PAC-learnable?

A concept class $C$ is PAC-learnable if there exists an algorithm that can output a hypothesis with probability at least $(1-\delta)$ (the "probably" part), and an error that is less than $\epsilon$ (...
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4 votes
2 answers
605 views

What are some use cases of few-shot learning?

Besides computer vision and image classification, what other use cases/applications are for few-shot learning?
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2 votes
1 answer
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Why can't DQN be used for self-driving cars?

Why can't DQN be used for self-driving cars? Why can't DQN and similar RL algorithms be used for self-driving cars? The reason why I am curious is that it successfully plays go and other multistate ...
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1 vote
3 answers
216 views

What are the most popular and effective approaches to leveraging AI for stock price prediction?

Currently, what are the most popular and effective approaches to leveraging AI for stock price prediction? It seems like there could be several approaches and problem formulations: Supervised ...
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1 vote
2 answers
71 views

What kinds of techniques do autopilots of autonomous cars use?

What kinds of techniques do autopilots of autonomous cars (e.g. the ones of Tesla) use? Do they use reinforcement learning? Which types of neural network architecture do they use?
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3 votes
2 answers
2k views

Could machine learning be used to measure the distance between two objects from a picture or live camera?

Could machine learning be used to measure the distance between two objects from a picture or live camera? An example of this is the measurement between the centre of each eye pupil. This area is ...
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1 vote
0 answers
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What are some real-world products or applications that can be developed using GANs?

GANs have shown good progress across a wide variety of domains ranging from image translation, image generation, text to image synthesis, audio/video generation, image super-resolution and many more. ...
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