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1500 questions
58
votes
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…
58
votes
13 answers

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?
M14
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51
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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51
votes
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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49
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
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…
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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45
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…
44
votes
4 answers

Meaning of roles in the API of GPT-4/ChatGPT (system/user/assistant)

In the API of GPT-4 and ChatGPT, the prompt for a chat conversation is a list of messages, each marked as one of three roles: system, user or assistant.* I understand which information this represents - but what does the model with that…
Volker Siegel
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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…
43
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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43
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…
43
votes
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
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…