Questions tagged [theory]

Use for questions on AI theory and other theoretical subjects related to AI.

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19 views

What does “episodic training” mean?

I'm reading the book Hands-On Meta Learning with Python, and in Prototypical networks said: So, we use episodic training—for each episode, we randomly sample a few data points from each class in ...
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1answer
50 views

Why everyone is using CNN for image segmentation?

I'm newbie in artificial intelligence. I have started to research about how to do image segmentation and all the papers that I have found are about CNN. Most of them use the same network, U-NET, but ...
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How many ways are there to perform image segmentation?

I'm new in Artificial Intelligence and I want to do image segmentation. Searching I have found these ways Digital image processing (I have read it in this book: Digital Image Processing, 4th edition)...
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Is this a problem well suited for machine learning?

The light-field of a certain scene is the set of all light rays that travel through the volume of that scene at a specific point of time. A light-field camera for example captures and stores a subset ...
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Are current AI models sufficient to achieve Artificial General Intelligence?

I read an interesting essay about how far we are from AGI. There were quite a few solid points that made me re-visit the foundation of AI today. A few interesting concepts arose: imagine that you ...
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27 views

How would you differentiate between different on-policy reinforcement learning algorithms?

How would you differentiate between different on-policy reinforcement learning algorithms?
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1answer
127 views

What are the current big challenges in Natural Language Processing and Understanding?

I'm doing a paper for a class on the topic of big problems that are still prevalent in AI, specifically in the area of Natural Language Processing and Understanding. From what I understand, the areas: ...
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1answer
61 views

When are compiled vs. interpreted languages more optimal in AI?

When are interpreted languages more optimal? When are compiled languages more optimal? What are the qualities and functions that render the so in relation to various AI methods?
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1answer
54 views

Is there anything theoretically revolutionary about Deep Neural Network?

In recent years we have seen quite a lot of impressive display of Deep Neural Network (DNN), as demonstrated most famously by AlphaGo and its cousin programs. But if I understand correctly, deep ...
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1answer
72 views

What is convergence in machine learning?

I came across this answer on Quora, but it was pretty sparse. I'm looking for specific meanings in the context of machine learning, but also mathematical and economic notions of the term in general.
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675 views

What does 'democratizing AI' exactly mean?

In my AI literature research, I often notice authors use term 'democratizing AI', especially in the AutoML area. I think I have an idea of what this means, but I would like to ask you for some more ...
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Is there a way to understand neural networks without using the concept of brain?

Is there a way to understand, for instance, a multi-layered perceptron without hand-waving about them being similar to brains etc? For example: it is obvious that what a perceptron does is ...
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1answer
34 views

Why is image classification tasks are dominated by minimizing cost function instead of maximizing ones?

I was watching a video of policy gradient by Andrej Karpathy at 10:00 there shows an equation for supervised learning for image classification. $max\sum _{i}log \:p(y_i|x_i)$ I have worked with ...
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Is the gradient at a layer independent of the activations of the previous layers?

Is the gradient at a layer (of a feed-forward neural network) independent of the activations of the previous layers? I read this in a paper titled Mean Field Residual Networks: On the Edge of Chaos (...
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Is it possible to control asymptotic behaviour of neural network models?

Is it possible to specify what the asymptotic behaviour of a Neural Networks (NN) model should be? I am thinking on NN which try to learn a mapping $\vec y=f(\vec x)$ with $\vec x$ a vector of ...
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Can Neural Networks self-optimize?

Suppose that you show a neural network its own code, and allow it to edit itself? Can a neural network modify its own weights and architecture (the number of layers, the number of neurons per layer, ...
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Are neural networks prone to catastrophic forgetting?

Imagine you show a neural network a picture of a lion 100 times and label with "dangerous", so it learns that lions are dangerous. Now imagine that previously you have shown it millions of images of ...
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89 views

Help and guide books in the study of AI

Useful knowledge is costly to obtain. Above all books require a substantial investment. I have bought 6 books on AI. For ...
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38 views

Why do neural networks have bias units?

Why do neural networks have bias units? Why is it sometimes okay to opt them out?
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1answer
427 views

What is an agent in Artificial Intelligence?

While studying artificial intelligence, I have often encountered the term "agent" (often autonomous, intelligent). For instance, in fields such as Reinforcement Learning, Multi-Agent Systems, Game ...
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1answer
43 views

Is explainable AI more feasible through symbolic AI or soft computing?

Is explainable AI more feasible through symbolic AI or soft computing? How much each paradigm, symbolic AI and soft computing (or hydrid approaches), adresses explanation and argumentation, where ...
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101 views

Would an artificial general intelligence have to be Turing complete?

Artificial general intelligence is the intelligence of a machine that could successfully perform any intellectual task that a human being can. Would an artificial general intelligence have to be ...
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1answer
59 views

What are the known ways to test AI black boxes?

Is there any conmprehensive paper or site that describes an overview of the known black box testing techniques?
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Theoretical grounding for ease of training with a prior

If we have a neural network that learns the generative model for P(A, B, C) And now, we want to learn the generative model for P(A, B, C, D) Is there any theory that says learning P(A,B,C) and then ...
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21 views

Superhuman AI to disguise as human players

TL;DR below. You entered a online mini video game. It's a fast-paced hypercasual game. But it's a ranked one - top 10 get prizes. The leaderboard resets and prizes are handed out every couple of ...
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Neural nets need a short term memory of some sort

I notice with the recent revelation of severe limitations in some AI domains such as self driving cars that NNets behave with the same sort of errors as in simpler models. Ie: They may be ~100% ...
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29 views

Is Intelligence a naturally occurring function of Information Technology?

Here intelligence is defined as any analytic or decision making process, regardless of strength (utility), and, potentially, any process of computation that produces output, regardless of the medium. ...
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Are winning and imitating the primary indicators of intelligence?

Conjecture 1: The smartest chess playing system is the one that wins the tournament. Conjecture 2: The computer system that imitates human dialog is as smart as the human whose dialog was imitated. ...
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79 views

How would a quantum computer potentially facilitate artificial consciousness, assuming it is possible?

How would a quantum computer potentially facilitate artificial consciousness, assuming it is possible?
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23 views

Batch PTA stopping condition

I am reviewing my Neural Network lectures and I have a doubt: My book's (Haykin) batch PTA describes a cost function which is defined over the set of the misclassified inputs. I have always been ...
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An idea I had to create the first Humanoid using Deep Learning

I've come up with an idea on how we could use a combination of Deep Learning and body sensors to create a walking talking living humanoid. Here goes: First, we will recruit 1 billion people and have ...
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108 views

What does learning mean?

Can someone explain what is the process of learning? What does it mean to learn something?
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148 views

Are human brain processes, like creativity, intuition or imagination, computable processes?

Are human brain processes, like intuition, creativity, imagination and the ability to create art, computable processes?
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76 views

How can I systematically learn about the theory of neural networks?

I have seen a few articles about neural nets. Mostly they went along these lines: we tried these architectures, these meta parameters, we trained it for $x$ hours on $y$ CPUs, and it gave us these ...
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95 views

Can NEAT produce neural networks where inputs are directly connected to outputs?

Can NEAT produce neural networks where inputs are directly (without intermediate hidden neurons) connected to outputs?
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78 views

Will a neural network always predict the correct label if it sees the exact same input during training and testing?

If I'm performing a text classification task using a model built in Keras, and for example, am attempting to predict the appropriate tag given a Stack Overflow question: "how to subtract 1 from an ...
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3answers
291 views

If AI can perceive, can it be sentient? [duplicate]

I think that AI perceive the world. Can an AI be sentient?
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Is AI truly doing anything that we can consider ''intelligent'' outside of subjective perception of what we perceive to function?

Artificial intelligence seems like a modelling program for interfaces of possible processes forming into another possible or greater architectures of further or differing processes. In what capacity ...
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82 views

How important are notations for Artificial Intelligence?

According to WIkipedia, a notation is a semiotics term to describe artistic disciplines. Famous examples are: chess notation, Siteswap notation for juggling, Labanotation for dancing, basketball play ...
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1answer
81 views

Can I filter barking sounds on the television?

My dog goes bonkers every time the sound of a barking dog is heard on a television program. I never noticed this before but literally every movie or show with an outdoors setting eventually includes ...
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1answer
403 views

Why does the “reward to go” trick in policy gradient methods work?

In policy gradient method, there's a trick to reduce a variance of policy gradient. We use causality, and remove part of the sum over rewards so that only actions happened after the reward are taken ...
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1answer
50 views

How Dempster-Shafer theory work in AI?

How does Dempster-Shafer theory work in representing ignorance in AI field?
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121 views

Is an algorithm that is no longer actively learning an AI?

This question assumes a definition of AI based on machine learning, and was inspired by this fun Technology Review post: SOURCE: Is this AI? We drew you a flowchart to work it out (Karen Hao, MIT ...
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175 views

How does Tara AI work?

Cisco and other companies are using Tara AI—a matching tool that connects IT projects with freelancers who have the exact skills required to complete them. Looking for an explanation of how Tara AI ...
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60 views

Is the proposal that more power leads to more intelligence correct?

One of the somewhat subliminal and entirely unsubstantiated assumptions we hear is that more computing power will allow us to approximate human intelligence — that quantitative augmentation will ...
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What are the most instructive movies about artificial intelligence?

The field of AI has expanded profoundly in recent years, as has public awareness and interest. This includes the arts, where fiction about AI has been popular since at least Isaac Asimov. Films on ...
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What is a learning agent?

What is a learning agent, and how does it work? What are examples of learning agents (e.g., in the field of robotics)?
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How much can the addition of new features improve the performance?

How much can the addition of new features improve the performance of the model during the optimization process? Let's say I have a total of 10 features. Suppose I start the optimisation process using ...
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2k views

What is the difference between goal-based and utility-based agents?

What is the difference between goal-based and utility-based agents? Please, provide a real-world example.
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1k views

What is the difference between learning and non-learning agents?

What is the difference between learning agents and other types of agents? In what ways learning agents can be applied? Do learning agents differ from deep learning