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1500 questions
11
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3 answers
Who was the first person to recognize the distinction between human-like general intelligence and domain-specific intelligence?
In the 1950s, there were widely-held beliefs that "Artificial Intelligence" will quickly become both self-conscious and smart-enough to win chess with humans. Various people suggested time frames of e.g. 10 years (see Olazaran's "Official History of…
liori
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11
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3 answers
What is the intuition behind TD($\lambda$)?
I'd like to better understand temporal-difference learning. In particular, I'm wondering if it is prudent to think about TD($\lambda$) as a type of "truncated" Monte Carlo learning?
Nick Kunz
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11
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5 answers
Why can neural networks generalize at all?
Neural networks are incredibly good at learning functions. We know by the universal approximation theorem that, theoretically, they can take the form of almost any function - and in practice, they seem particularly apt at learning the right…
Nico A
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11
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1 answer
What regulations are already in place regarding artificial general intelligences?
What regulations are already in place regarding artificial general intelligences? What reports or recommendations prepared by official government authorities were already published?
So far, I know of Sir David King's report done for UK government.
liori
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11
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1 answer
How does the forget layer of an LSTM work?
Can someone explain the mathematical intuition behind the forget layer of an LSTM?
So as far as I understand it, the cell state is essentially long term memory embedding (correct me if I'm wrong), but I'm also assuming it's a matrix. Then the…
user8714896
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11
votes
4 answers
Are there any online competitions for Reinforcement Learning?
Kaggle is limited to only supervised learning problems. There used to be www.rl-competition.org but they've stopped.
Is there anything else I can do other than locally trying out different algorithms for various RL problems?
Dhanush Giriyan
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11
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1 answer
What is the reason AMD Radeon is not widely used for machine learning and deep learning?
What is the reason AMD Radeon is not widely used for machine learning and deep learning? Is it mainly an issue of lack of software? Or is Radeon's GPU not as good as NVIDIA's?
noviceFedora
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11
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1 answer
Can supervised learning be recast as reinforcement learning problem?
Let's assume that there is a sequence of pairs $(x_i, y_i), (x_{i+1}, y_{i+1}), \dots$ of observations and corresponding labels. Let's also assume that the $x$ is considered as independent variable and $y$ is considered as the variable that depends…
TomR
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11
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2 answers
When should I use 3D convolutions?
I am new to convolutional neural networks, and I am learning 3D convolution. What I could understand is that 2D convolution gives us relationships between low-level features in the X-Y dimension, while the 3D convolution helps detect low-level…
Shobhit Verma
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11
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1 answer
What is the time complexity of the forward pass algorithm of a feedforward neural network?
How do I determine the time complexity of the forward pass algorithm of a feedforward neural network? How many multiplications are done to generate the output?
Artificial
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11
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3 answers
How powerful a computer is required to simulate the human brain?
How much processing power is needed to emulate the human brain? More specifically, the neural simulation, such as communication between the neurons and processing certain data in real-time.
I understand that this may be a bit of speculation and it's…
kenorb
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11
votes
2 answers
What are the common myths associated with Artificial Intelligence?
What are some interesting myths of Artificial Intelligence and what are the facts behind them?
fabien
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11
votes
3 answers
What algorithms are considered reinforcement learning algorithms?
What are the areas/algorithms that belong to reinforcement learning?
TD(0), Q-Learning and SARSA are all temporal-difference algorithms, which belong to the reinforcement learning area, but is there more to it?
Are the dynamic programming…
Miguel Saraiva
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11
votes
4 answers
What are the domains where SVMs are still state-of-the-art?
It seems that deep neural networks and other neural network based models are dominating many current areas like computer vision, object classification, reinforcement learning, etc.
Are there domains where SVMs (or other models) are still producing…
Steven Davis
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11
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1 answer
What is the meaning of $V(D,G)$ in the GAN objective function?
Here is the GAN objective function.
$$\min _{G} \max _{D} V(D, G)=\mathbb{E}_{\boldsymbol{x} \sim p_{\text {data }}(\boldsymbol{x})}[\log D(\boldsymbol{x})]+\mathbb{E}_{\boldsymbol{z} \sim p_{\boldsymbol{z}}(\boldsymbol{z})}[\log…
i_rezic
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