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20
votes
7answers
2k views

If digital values are mere estimates, why not return to analog for AI?

The impetus behind the twentieth century transition from analog to digital circuitry was driven by the desire for greater accuracy and lower noise. Now we are developing software where results are ...
24
votes
4answers
7k views

How to handle invalid moves in reinforcement learning?

I want to create an AI which can play five-in-a-row/gomoku. As I mentioned in the title, I want to use reinforcement learning for this. I use policy gradient method, namely REINFORCE, with baseline. ...
78
votes
8answers
13k views

Do scientists know what is happening inside artificial neural networks?

Do scientists or research experts know from the kitchen what is happening inside complex "deep" neural network with at least millions of connections firing at an instant? Do they understand the ...
24
votes
7answers
3k views

What are the minimum requirements to call something AI?

I believe artificial intelligence (AI) term is overused nowadays. For example, people see that something is self-moving and they call it AI, even if it's on autopilot (like cars or planes) or there is ...
72
votes
10answers
5k views

How is it possible that deep neural networks are so easily fooled?

The following page/study demonstrates that the deep neural networks are easily fooled by giving high confidence predictions for unrecognisable images, e.g. How this is possible? Can you please ...
54
votes
10answers
33k views

Why is Python such a popular language in the AI field?

First of all, I'm a beginner studying AI and this is not an opinion-oriented question or one to compare programming languages. I'm not implying that Python is the best language. But the fact is that ...
20
votes
5answers
14k views

What is the time complexity for training a neural network using back-propagation?

Suppose that a NN contains $n$ hidden layers, $m$ training examples, $x$ features, and $n_i$ nodes in each layer. What is the time complexity to train this NN using back-propagation? I have a basic ...
16
votes
6answers
16k views

How does one start learning artificial intelligence? [duplicate]

I am a software engineering student and I am complete beginner to AI. I have read a lot of articles on how to start learning AI, but each article suggests a different way. I was wondering if some of ...
31
votes
3answers
20k views

Why is Lisp such a good language for AI?

I've heard before from computer scientists and from researchers in the area of AI that that Lisp is a good language for research and development in artificial intelligence. Does this still apply, with ...
8
votes
1answer
1k views

What are the steps to follow to learn artificial intelligence? [closed]

I know nothing about AI. Can anybody tell me what steps I have to follow to learn artificial intelligence? Are there any special technologies, or anything else, I have to learn?
9
votes
1answer
1k views

Where can I find the proof of the universal approximation theorem?

The Wikipedia article for the universal approximation theorem cites a version of the universal approximation theorem for Lebesgue-measurable functions from this conference paper. However, the paper ...
1
vote
1answer
408 views

Is back propagation applied for each data point or for a batch of data points?

I am new to deep learning and trying to understand the concept of back propagation. I have a doubt on when the back propagation is applied. Assume that I have a training data set of 1000 images for ...
83
votes
14answers
13k views

What is the difference between artificial intelligence and machine learning?

These two terms seem to be related, especially in their application in computer science and software engineering. Is one a subset of another? Is one a tool used to build a system for the other? ...
19
votes
6answers
10k views

What is the purpose of an activation function in neural networks?

It is said that activation functions in neural networks help introduce non-linearity. What does this mean? What does non-linearity mean in this context? How does the introduction of this non-...
38
votes
6answers
22k views

What's the difference between model-free and model-based reinforcement learning?

What's the difference between model-free and model-based reinforcement learning? It seems to me that any model-free learner, learning through trial and error, could be reframed as model-based. In ...
16
votes
5answers
4k views

What exactly are genetic algorithms and what sort of problems are they good for?

I've noticed that a few questions on this site mention genetic algorithms and it made me realize that I don't really know much about those. I have heard the term before, but it's not something I've ...
12
votes
2answers
695 views

Why doesn't Q-learning converge when using function approximation?

The tabular Q-learning algorithm is guaranteed to find the optimal $Q$ function, $Q^*$, provided the following conditions (the Robbins-Monro conditions) regarding the learning rate are satisfied $\...
17
votes
3answers
1k views

How are Artificial Neural Networks and the Biological Neural Networks similar and different?

I've heard multiple times that "Neural Networks are the best approximation we have to model the human brain", and I think it is commonly known that Neural Networks are modelled after our brain. I ...
1
vote
3answers
708 views

What is the difference between a stochastic and a deterministic policy?

In reinforcement learning, there are the concepts of stochastic (or probabilistic) and deterministic policies. What is the difference between them?
43
votes
4answers
11k views

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 ...
38
votes
8answers
32k views

In a CNN, does each new filter have different weights for each input channel, or are the same weights of each filter used across input channels?

My understanding is that the convolutional layer of a convolutional neural network has four dimensions: input_channels, filter_height, filter_width, number_of_filters. Furthermore, it is my ...
86
votes
14answers
6k views

How could self-driving cars make ethical decisions about who to kill?

Obviously, self-driving cars aren't perfect, so imagine that the Google car (as an example) got into a difficult situation. Here are a few examples of unfortunate situations caused by a set of events:...
11
votes
5answers
573 views

Sources on the AI theory, philosophy, tools and applications [closed]

I am software/hardware engineer for many years now. However, I know nothing about AI and machine learning. I have a strong background in digital signal processing, and various programming languages (...
36
votes
6answers
3k views

Is the Turing Test, or any of its variants, a reliable test of artificial intelligence?

The Turing Test was the first test of artificial intelligence and is now a bit outdated. The Total Turing Test aims to be a more modern test which requires a much more sophisticated system. What ...
20
votes
2answers
2k views

Problems that only humans will ever be able to solve

With the increasing complexity of reCAPTCHA, I wondered about the existence of some problem, that only a human will ever be able to solve (or that AI won't be able to solve as long as it doesn't ...
9
votes
6answers
1k views

What do I need to study for machine learning?

Starting from last year, I have been studying various subjects in order to understand some of the most important thesis of machine learning like S. Hochreiter, & J. Schmidhuber. (1997). Long ...
15
votes
5answers
2k views

What is the difference between machine learning and deep learning?

Can someone explain to me the difference between machine learning and deep learning? Is it possible to learn deep learning without knowing machine learning?
9
votes
10answers
1k views

Could an AI feel emotions?

Assuming humans had finally developed the first humanoid AI based on the human brain, would It feel emotions? If not, would it still have ethics and/or morals?
10
votes
3answers
738 views

What is wrong with the idea that the AI will be capable of omniscience?

In the context of artificial intelligence, the singularity refers to the advent of an artificial general intelligence capable of recursive self-improvement, leading to the rapid emergence of ...
8
votes
2answers
777 views

What kind of education is required for researchers in AI?

Suppose my goal is to collaborate and create an advanced AI, for instance one that resembles a human being and the project would be on the frontier of AI research, what kind of skills would I need? I ...
6
votes
1answer
7k views

What is the fringe in the context of search algorithms?

What is the fringe in the context of search algorithms?
41
votes
5answers
1k views

To what extent can quantum computers help to develop Artificial Intelligence?

What aspects of quantum computers, if any, can help to further develop Artificial Intelligence?
13
votes
2answers
6k views

How to choose an activation function?

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 ...
23
votes
4answers
4k views

Can neural networks be used to prove conjectures?

Imagine I have a list (in a computer-readable form) of all problems (or statements) and proofs that math relies on. Could I train a neural network in such a way that, for example, I enter a problem ...
22
votes
5answers
1k views

How could emotional intelligence be implemented?

I've seen emotional intelligence defined as the capacity to be aware of, control, and express one's emotions, and to handle interpersonal relationships judiciously and empathetically. What are some ...
11
votes
3answers
454 views

How would an AI learn language?

I was think about AIs and how they would work, when I realised that I couldn't think of a way that an AI could be taught language. A child tends to learn language through associations of language and ...
14
votes
1answer
8k views

How does LSTM in deep reinforcement learning differ from experience replay?

In the paper Deep Recurrent Q-Learning for Partially Observable MDPs, the author processed the Atari game frames with an LSTM layer at the end. My questions are: How does this method differ from the ...
13
votes
4answers
1k views

How close are we to creating Ex Machina?

Are there any research teams that attempted to create or have already created an AI robot that can be as close to intelligent as these found in Ex Machina or I, Robot movies? I'm not talking about ...
7
votes
2answers
1k views

Which areas of applied math are relevant to AI? [duplicate]

My background is in electrical engineering. I have a good grasp of CS foundations (e.g. data structures, algorithms, operating systems, discrete math and software engineering). I have option of ...
6
votes
3answers
13k views

What are the differences between A* and greedy best-first search?

What are the differences between the A* algorithm and the greedy best-first search algorithm? Which one should I use? Which algorithm is the better one, and why?
7
votes
3answers
728 views

What makes animal brain so special?

So this is an introductory question. Whenever I read any book about Neural Nets or Machine Learning, their introductory chapter says that we haven't been able to replicate the brain's power due to its ...
9
votes
1answer
614 views

Can an AI learn to suffer?

I had first this question in mind "Can an AI suffer?". Suffering is important for human beings. Imagine that you are damaging your heel. Without pain, you will continue to harm it. Same for an AI. But ...
10
votes
4answers
1k views

What are the purposes of autoencoders?

Autoencoders are neural networks that learn a compressed representation of the input in order to later reconstruct it, so they can be used for dimensionality reduction. They are composed of an encoder ...
6
votes
2answers
384 views

What is the difference between artificial intelligence and cognitive science?

Sometimes I understand that people doing cognitive science try to avoid the term artificial intelligence. The feeling I get is that there is a need to put some distance to the GOFAI. Another ...
5
votes
6answers
481 views

Is transistor the first artificial intelligence?

Artificial Intelligence is any device that perceives its environment and takes actions that maximize its chance of success at some goal. I got this definition from Wikipedia that cited "Russell and ...
4
votes
1answer
825 views

What does “death” intuitively mean in the paper “Death and Suicide in Universal Artificial Intelligence”?

In the paper Death and Suicide in Universal Artificial Intelligence, a proposal is given for what death could mean for Artificial Intelligence. What does this mean using English only? I understand ...
3
votes
1answer
249 views

Is it possible to build human-brain-level artificial intelligence based on neuromorphic chips and neural networks?

I read a lot about the structure of the human brain and artificial neural networks. I wonder if it is possible to build an artificial intelligence with neural networks that would be divided into ...
2
votes
4answers
385 views

Can a brain be intelligent without a body? [duplicate]

The dialog context Turing proposed at the end of the description of his famous test, "Will the interrogator decide wrongly as often when the game is played like this as he does when the game is ...
2
votes
1answer
579 views

Why are Q values updated according to the greedy policy?

Apparently, in the Q-learning algorithm, the Q values are not updated according to the "current policy", but according to a "greedy policy". Why is that the case? I think this is related to the fact ...
5
votes
3answers
601 views

What is the actual learning algorithm: back-propagation or gradient descent?

What is the actual learning algorithm: back-propagation or gradient descent (or, in general, the optimization algorithm)? I am reading through chapter 8 of Parallel Distributed Processing hand book ...

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