Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

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1500 questions
56
votes
11 answers

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 this post I'm curious about the…
ABIM
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51
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6 answers

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?
kenorb
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50
votes
3 answers

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?
WilliamKF
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48
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2 answers

How does ChatGPT retain the context of previous questions?

One of the innovations with OpenAI's ChatGPT is how natural it is for users to interact with it. What is the technical enabler for ChatGPT to maintain the context of previous questions in its answers? For example, ChatGPT understands a prompt of…
milez
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48
votes
5 answers

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?
wythagoras
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48
votes
19 answers

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, we can take into account integers. We can think,…
verdery
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46
votes
3 answers

Was ChatGPT trained on Stack Overflow data?

Has ChatGPT used highly rated and upvoted questions/answers from Stack Overflow in its training data? For me it makes complete sense to take answers that have upwards of 100 upvotes and include them in your training data, but people around me seem…
Nicolas Zein
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44
votes
2 answers

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 state, policy gradients directly predict the…
sloth
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43
votes
5 answers

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 brain. But what's the difference between a…
Mithical
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43
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6 answers

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?
rcpinto
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41
votes
2 answers

How is ChatGPT aware of today's date?

I asked ChatGPT (3.5 and 4) about current date and (s)he answered correctly. In subsequent conversation (s)he was not able to explain how (s)he has this knowledge. I always thought that the model only sees the conversation above and a pretrained NN…
Peter Franek
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41
votes
5 answers

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 whether or not a given number $n$ is composite or prime? How…
Fullk33
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41
votes
5 answers

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 the policy gradient method, namely REINFORCE, with baseline. For the value and policy function approximation, I use a neural network. It…
Molnár István
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40
votes
4 answers

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 idea about how they find the time complexity of…
user9947
40
votes
5 answers

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-linearity help? Are there any other purposes of…
Mohsin
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