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171
votes
12answers
48k views

Could a paradox kill an AI?

In Portal 2 we see that AI's can be "killed" by thinking about a paradox. I assume this works by forcing the AI into an infinite loop which would essentially "freeze" the computer's consciousness. ...
99
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: ...
91
votes
10answers
14k 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? ...
88
votes
7answers
16k 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 ...
82
votes
9answers
6k 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 ...
73
votes
3answers
67k views

What is self-supervised learning in machine learning?

What is self-supervised learning in machine learning? How is it different from supervised learning?
71
votes
3answers
51k views

How can neural networks deal with varying input sizes?

As far as I can tell, neural networks have a fixed number of neurons in the input layer. If neural networks are used in a context like NLP, sentences or blocks of text of varying sizes are fed to a ...
67
votes
9answers
10k views

Why do we need explainable AI?

If the original purpose for developing AI was to help humans in some tasks and that purpose still holds, why should we care about its explainability? For example, in deep learning, as long as the ...
59
votes
10answers
39k 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 ...
59
votes
6answers
50k 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 ...
54
votes
11answers
10k views

What are some well-known problems where neural networks don't do very well?

Background: It's well-known that neural networks offer great performance across a large number of tasks, and this is largely a consequence of their universal approximation capabilities. However, in ...
53
votes
13answers
10k views

How could artificial intelligence harm us?

We often hear that artificial intelligence may harm or even kill humans, so it might prove dangerous. How could artificial intelligence harm us?
53
votes
8answers
42k 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 ...
52
votes
4answers
14k 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 ...
50
votes
4answers
81k views

How to select number of hidden layers and number of memory cells in an LSTM?

I am trying to find some existing research on how to select the number of hidden layers and the size of these of an LSTM-based RNN. Is there an article where this problem is being investigated, i.e., ...
47
votes
6answers
2k views

What is fuzzy logic?

I'm new to A.I. and I'd like to know in simple words, what is the fuzzy logic concept? How does it help, and when is it used?
45
votes
3answers
23k views

What is the difference between strong-AI and weak-AI?

I've heard the terms strong-AI and weak-AI used. Are these well defined terms or subjective ones? How are they generally defined?
44
votes
19answers
15k views

Can digital computers understand infinity?

As a human being, we can think infinity. In principle, if we have enough resources (time etc.), we can count infinitely many things (including abstract, like numbers, or real). For example, at least, ...
44
votes
5answers
2k 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?
39
votes
6answers
21k views

How do capsule neural networks work?

Geoffrey Hinton has been researching something he calls "capsules theory" in neural networks. What is it? How do capsule neural networks work?
38
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 ...
38
votes
4answers
1k views

What is the concept of the technological singularity?

I've heard the idea of the technological singularity, what is it and how does it relate to Artificial Intelligence? Is this the theoretical point where Artificial Intelligence machines have progressed ...
37
votes
1answer
20k views

Which library would you recommend to begin with deep learning? [closed]

Which library (TensorFlow or Keras) would you recommend for a first approach to deep learning? I'm a neuroscience student trying for the first time computational approaches, if that matters.
35
votes
8answers
16k views

Is a switch from R to Python worth it? [closed]

I just finished a 1-year Data Science master's program where we were taught R. I found that Python is more popular and has a larger community in AI. What are the advantages that Python may have over R ...
34
votes
6answers
10k views

Why do CNN's sometimes make highly confident mistakes, and how can one combat this problem?

I trained a simple CNN on the MNIST database of handwritten digits to 99% accuracy. I'm feeding in a bunch of handwritten digits, and non-digits from a document. I want the CNN to report errors, so I ...
34
votes
3answers
25k views

Why does the transformer do better than RNN and LSTM in long-range context dependencies?

I am reading the article How Transformers Work where the author writes Another problem with RNNs, and LSTMs, is that it’s hard to parallelize the work for processing sentences, since you have to ...
33
votes
5answers
64k views

What is the difference between a convolutional neural network and a regular neural network?

I've seen these terms thrown around this site a lot, specifically in the tags convolutional-neural-networks and neural-networks. I know that a neural network is a system based loosely on the human ...
33
votes
3answers
24k 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 ...
33
votes
2answers
13k views

What is the relation between Q-learning and policy gradients methods?

As far as I understand, Q-learning and policy gradients (PG) are the two major approaches used to solve RL problems. While Q-learning aims to predict the reward of a certain action taken in a certain ...
33
votes
4answers
1k views

How to find the optimal number of neurons per layer?

When you're writing your algorithm, how do you know how many neurons you need per single layer? Are there any methods for finding the optimal number of them, or is it a rule of thumb?
32
votes
5answers
11k views

How should I handle invalid actions (when using REINFORCE)?

I want to create an AI which can play five-in-a-row/gomoku. I want to use reinforcement learning for this. I use policy gradient method, namely REINFORCE, with baseline. For the value and policy ...
32
votes
4answers
15k views

Could a neural network detect primes?

I am not looking for an efficient way to find primes (which of course is a solved problem). This is more of a "what if" question. So, in theory, could you train a neural network to predict ...
30
votes
7answers
7k views

What are examples of promising AI/ML techniques that are computationally intractable?

To produce tangible results in the field of AI/ML, one must take theoretical results under the lens of computational complexity. Indeed, minimax effectively solves any two-person "board game"...
30
votes
8answers
5k views

Is artificial intelligence vulnerable to hacking?

The paper The Limitations of Deep Learning in Adversarial Settings explores how neural networks might be corrupted by an attacker who can manipulate the data set that the neural network trains with. ...
30
votes
5answers
18k 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-...
30
votes
2answers
1k views

How is a deep neural network different from other neural networks?

How is a neural network having the "deep" adjective actually distinguished from other similar networks?
30
votes
5answers
21k views

Is it possible to train the neural network to solve math equations?

I'm aware that neural networks are probably not designed to do that, however asking hypothetically, is it possible to train the deep neural network (or similar) to solve math equations? So given the ...
30
votes
5answers
30k 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 ...
28
votes
9answers
6k views

What is the actual quality of machine translations?

As an AI layman, till today I am confused by the promised and achieved improvements of automated translation. My impression is: there is still a very, very far way to go. Or are there other ...
28
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 ...
27
votes
7answers
4k 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 ...
26
votes
7answers
14k views

How can an AI train itself if no one is telling it if its answer is correct or wrong?

I am a programmer but not in the field of AI. A question constantly confuses me is that how can an AI be trained if we human beings are not telling it its calculation is correct? For example, news ...
26
votes
4answers
12k views

Is it possible to train a neural network as new classes are given?

I would like to train a neural network (NN) where the output classes are not (all) defined from the start. More and more classes will be introduced later based on incoming data. This means that, every ...
25
votes
8answers
4k views

Is there any research on the development of attacks against artificial intelligence systems?

Is there any research on the development of attacks against artificial intelligence systems? For example, is there a way to generate a letter "A", which every human being in this world can recognize ...
25
votes
4answers
5k views

What are the current theories on the development of a conscious AI?

What are the current theories on the development of a conscious AI? Is anyone even trying to develop a conscious AI? Is it possible that consciousness is an emergent phenomenon, that is, once we put ...
25
votes
4answers
1k views

Are Siri and Cortana AI programs?

Siri and Cortana communicate pretty much like humans. Unlike Google Now, which mainly gives us search results when asked some questions (not setting alarms or reminders), Siri and Cortana provide us ...
25
votes
4answers
407 views

Is the pattern recognition capability of CNNs limited to image processing?

Can a Convolutional Neural Network be used for pattern recognition in problem domains without image data? For example, by representing abstract data in an image-like format with spatial relations? ...
25
votes
4answers
2k views

Is Lisp still being used to tackle AI problems?

I know that language of Lisp was used early on when working on artificial intelligence problems. Is it still being used today for significant work? If not, is there a new language that has taken its ...
25
votes
5answers
29k views

How can I deal with images of variable dimensions when doing image segmentation?

I'm facing the problem of having images of different dimensions as inputs in a segmentation task. Note that the images do not even have the same aspect ratio. One common approach that I found in ...
24
votes
4answers
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 ...

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