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1500 questions
18
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3 answers
Which explainable artificial intelligence techniques are there?
Explainable artificial intelligence (XAI) is concerned with the development of techniques that can enhance the interpretability, accountability, and transparency of artificial intelligence and, in particular, machine learning algorithms and models,…
nbro
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17
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1 answer
Are search engines considered AI?
Are search engines considered AI because of the way they analyze what you search for and remember it? Or how they send you ads of what you've searched for recently?
Is this considered AI or just smart?
skistaddy
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17
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3 answers
How does AI "consume" water?
There's been a lot of talk about how much water AI uses. I keep reading that they use it for cooling, but after they do that where's the water going? From my understanding, liquid cooled PCs are fully enclosed not requiring top-ups unless there are…
Ora G. Walters
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17
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1 answer
How can policy gradients be applied in the case of multiple continuous actions?
Trusted Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO) are two cutting edge policy gradients algorithms.
When using a single continuous action, normally, you would use some probability distribution (for example, Gaussian)…
Evalds Urtans
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17
votes
2 answers
Why does ChatGPT not give the answer text all at once?
When ChatGPT is generating an answer to my question, it generates it word by word.
So I actually have to wait until I get the final answer.
Is this just for show?
Or is it really real-time generating the answer word by word not knowing yet what the…
Sander van den Oord
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17
votes
4 answers
How to reinvent jobs replaced by AI?
In general, what possibilities are there for reinventing job descriptions that could be replaced by an automated AI solution?
My initial ideas include:
Monitoring the AI and flagging its incorrect actions.
Possibly taking over the control in very…
tuomastik
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17
votes
3 answers
Are there any applications of reinforcement learning other than games?
Is there a way to teach reinforcement learning in applications other than games?
The only examples I can find on the Internet are of game agents. I understand that VNC's control the input to the games via the reinforcement network. Is it possible…
Mark Markrowave Charlton
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17
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2 answers
When is deep learning overkill?
For example, for classifying emails as spam, is it worthwhile - from a time/accuracy perspective - to apply deep learning (if possible) instead of another machine learning algorithm? Will deep learning make other machine learning algorithms like…
Alexander
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17
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3 answers
What is the difference between Q-learning, Deep Q-learning and Deep Q-network?
Q-learning uses a table to store all state-action pairs. Q-learning is a model-free RL algorithm, so how could there be the one called Deep Q-learning, as deep means using DNN; or maybe the state-action table (Q-table) is still there but the DNN is…
Dan D
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17
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2 answers
What is the difference between active learning and online learning?
The definitions for these two appear to be very similar, and frankly, I've been only using the term "active learning" the past couple of years. What is the actual difference between the two? Is one a subset of the other?
David
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17
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1 answer
Are information processing rules from Gestalt psychology still used in computer vision today?
Decades ago there were and are books in machine vision, which by implementing various information processing rules from gestalt psychology, got impressive results with little code or special hardware in image identification and visual…
Gottfried William
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17
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3 answers
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 pictures to an object (e.g., people saying the…
AvahW
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17
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2 answers
What is the difference between graph convolution in the spatial vs spectral domain?
I've been reading different papers regarding graph convolution and it seems that they come into two flavors: spatial and spectral. From what I can see the main difference between the two approaches is that for spatial you're directly multiplying the…
razvanc92
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1 answer
How does "Monte-Carlo search" work?
I have heard about this concept in a Reddit post about AlphaGo. I have tried to go through the paper and the article, but could not really make sense of the algorithm.
So, can someone give an easy-to-understand explanation of how the Monte-Carlo…
Dawny33
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16
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1 answer
What is the difference between a receptive field and a feature map?
In a CNN, the receptive field is the portion of the image used to compute the filter's output. But one filter's output (which is also called a "feature map") is the next filter's input.
What's the difference between a receptive field and a feature…
Monica Heddneck
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