All Questions
Tagged with difference or comparison
458 questions
104
votes
9
answers
17k
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?
What ...
- 1,335
97
votes
3
answers
87k
views
What is self-supervised learning in machine learning?
What is self-supervised learning in machine learning? How is it different from supervised learning?
- 41.4k
92
votes
6
answers
103k
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 ...
- 1,021
50
votes
3
answers
24k
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?
- 2,523
47
votes
2
answers
26k
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 ...
- 595
43
votes
5
answers
82k
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 ...
- 2,925
35
votes
8
answers
17k
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 ...
- 503
31
votes
2
answers
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?
- 10.5k
30
votes
1
answer
18k
views
How is BERT different from the original transformer architecture?
As far as I can tell, BERT is a type of Transformer architecture. What I do not understand is:
How is Bert different from the original transformer architecture?
What tasks are better suited for BERT,...
- 3,000
29
votes
4
answers
81k
views
Why does C++ seem less widely used than Python in AI?
I just want to know why do machine learning engineers and AI programmers use languages like Python to perform AI tasks and not C++, even though C++ is technically a more powerful language than Python.
- 509
26
votes
4
answers
10k
views
Can the decoder in a transformer model be parallelized like the encoder?
Can the decoder in a transformer model be parallelized like the encoder?
As far as I understand, the encoder has all the tokens in the sequence to compute the self-attention scores. But for a decoder,...
- 363
24
votes
2
answers
24k
views
What is the difference between First-Visit Monte-Carlo and Every-Visit Monte-Carlo Policy Evaluation?
I came across these 2 algorithms, but I cannot understand the difference between these 2, both in terms of implementation as well as intuitionally.
So, what difference does the second point in both ...
user9947
23
votes
5
answers
4k
views
What is the difference between machine learning and deep learning?
Can someone explain to me the difference between machine learning and deep learning? Is it possible to learn deep learning without knowing machine learning?
- 333
23
votes
2
answers
15k
views
What is the difference between reinforcement learning and optimal control?
Coming from a process (optimal) control background, I have begun studying the field of deep reinforcement learning.
Sutton & Barto (2015) state that
particularly important (to the writing of the ...
- 373
21
votes
1
answer
5k
views
Why has the cross-entropy become the classification standard loss function and not Kullback-Leibler divergence?
The cross-entropy is identical to the KL divergence plus the entropy of the target distribution. The KL divergence equals zero when the two distributions are the same, which seems more intuitive to me ...
- 321
20
votes
2
answers
20k
views
What are the main differences between skip-gram and continuous bag of words?
The skip-gram and continuous bag of words (CBOW) are two different types of word2vec models.
What are the main differences between them? What are the pros and cons of both methods?
- 1,763
20
votes
3
answers
4k
views
How are Artificial Neural Networks and the Biological Neural Networks similar and different?
I've heard multiple times that "Neural Networks are the best approximation we have to model the human brain", and I think it is commonly known that Neural Networks are modelled after our brain.
I ...
19
votes
4
answers
11k
views
What is the difference between actor-critic and advantage actor-critic?
I'm struggling to understand the difference between actor-critic and advantage actor-critic.
At least, I know they are different from asynchronous advantage actor-critic (A3C), as A3C adds an ...
- 1,077
19
votes
1
answer
52k
views
What is the difference between tree search and graph search?
I have read various answers to this question at different places, but I am still missing something.
What I have understood is that a graph search holds a closed list, with all expanded nodes, so ...
- 423
19
votes
1
answer
19k
views
How does LSTM in deep reinforcement learning differ from experience replay?
In the paper Deep Recurrent Q-Learning for Partially Observable MDPs, the author processed the Atari game frames with an LSTM layer at the end. My questions are:
How does this method differ from the ...
- 363
19
votes
1
answer
628
views
Could a Boltzmann machine store more patterns than a Hopfield net?
This is from a closed beta for AI, with this question being posted by user number 47. All credit to them.
According to Wikipedia,
Boltzmann machines can be seen as the stochastic, generative ...
- 2,925
18
votes
1
answer
512
views
Are these two versions of back-propagation equivalent?
Just for fun, I am trying to develop a neural network.
Now, for backpropagation I saw two techniques.
The first one is used here and in many other places too.
What it does is:
It computes the ...
- 181
17
votes
2
answers
2k
views
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 ...
- 293
17
votes
3
answers
13k
views
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-...
- 1,318
17
votes
2
answers
7k
views
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? ...
- 313
17
votes
2
answers
12k
views
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 ...
- 1,158
16
votes
1
answer
6k
views
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 ...
- 261
15
votes
2
answers
19k
views
Why is Sanskrit the best language for AI?
According to NASA scientist Rick Briggs, Sanskrit is the best language for AI. I want to know how Sanskrit is useful. What's the problem with other languages? Are they really using Sanskrit in AI ...
- 167
15
votes
2
answers
11k
views
What is the difference between artificial intelligence and computational intelligence?
Having analyzed and reviewed a certain amount of articles and questions, apparently, the expression computational intelligence (CI) is not used consistently and it is still unclear the relationship ...
- 1,183
14
votes
3
answers
68k
views
What are the differences between A* and greedy best-first search?
What are the differences between the A* algorithm and the greedy best-first search algorithm? Which one should I use? Which algorithm is the better one, and why?
- 375
14
votes
1
answer
11k
views
What are the consequences of layer norm vs batch norm?
I'll start with my understanding of the literal difference between these two. First, let's say we have an input tensor to a layer, and that tensor has dimensionality $B \times D$, where $B$ is the ...
- 1,369
13
votes
4
answers
12k
views
What does AI software look like, and how is it different from other software?
What does AI software look like? What is the major difference between AI software and other software?
- 233
13
votes
3
answers
14k
views
What is the relation between semi-supervised and self-supervised visual representation learning?
What's the differences between semi-supervised learning and self-supervised visual representation learning, and how they are connected?
- 281
13
votes
2
answers
2k
views
Is there a fundamental difference between an environment being stochastic and being partially observable?
In AI literature, deterministic vs stochastic and being fully-observable vs partially observable are usually considered two distinct properties of the environment.
I'm confused about this because what ...
- 255
13
votes
3
answers
3k
views
What is a recurrent neural network?
Surprisingly, this wasn't asked before - at least I didn't find anything besides some vaguely related questions.
So, what is a recurrent neural network, and what are their advantages over regular (or ...
- 759
13
votes
5
answers
8k
views
What is the fundamental difference between CNN and RNN?
What is the fundamental difference between convolutional neural networks and recurrent neural networks? Where are they applied?
- 151
13
votes
1
answer
5k
views
What is the difference between one-shot learning, transfer learning and fine tuning?
Lately, there are lots of posts on one-shot learning. I tried to figure out what it is by reading some articles. To me, it looks like similar to transfer learning, in which we can use pre-trained ...
- 789
13
votes
1
answer
14k
views
What are the fundamental differences between VAE and GAN for image generation?
Starting from my own understanding, and scoped to the purpose of image generation, I'm well aware of the major architectural differences:
A GAN's generator samples from a relatively low dimensional ...
- 1,369
12
votes
1
answer
6k
views
Are humans superior to machines in chess?
A friend of mine, who is an International Master at chess, told me that humans were superior to machines provided you didn't impose the time constraints that exist in competitive chess (40 moves in 2 ...
- 221
12
votes
1
answer
20k
views
What is the definition of "soft label" and "hard label"?
In semi-supervised learning, there are hard labels and soft labels. Could someone tell me the meaning and definition of the two things?
- 121
12
votes
1
answer
6k
views
In Computer Vision, what is the difference between a transformer and attention?
Having been studying computer vision for a while, I still cannot understand what the difference between a transformer and attention is?
- 123
12
votes
1
answer
6k
views
What exactly is the advantage of double DQN over DQN?
I started looking into the double DQN (DDQN). Apparently, the difference between DDQN and DQN is that in DDQN we use the main value network for action selection and the target network for outputting ...
- 369
12
votes
3
answers
5k
views
Is REINFORCE the same as 'vanilla policy gradient'?
I don't know what people mean by 'vanilla policy gradient', but what comes to mind is REINFORCE, which is the simplest policy gradient algorithm I can think of. Is this an accurate statement?
By ...
- 361
12
votes
1
answer
893
views
What are hyper-heuristics, and how are they different from meta-heuristics?
I wanted to know what the differences between hyper-heuristics and meta-heuristics are, and what their main applications are. Which problems are suited to be solved by hyper-heuristics?
- 399
11
votes
1
answer
13k
views
What is the relationship between gradient accumulation and batch size?
I am currently training some models using gradient accumulation since the model batches do not fit in GPU memory. Since I am using gradient accumulation, I had to tweak the training configuration a ...
- 1,168
11
votes
2
answers
2k
views
Are Q-learning and SARSA the same when action selection is greedy?
I'm currently studying reinforcement learning and I'm having difficulties with question 6.12 in Sutton and Barto's book.
Suppose action selection is greedy. Is Q-learning then exactly the same ...
- 131
11
votes
1
answer
1k
views
Why is the merged neural network of AlphaGo Zero more efficient than two separate neural networks?
AlphaGo Zero contains several improvements compared to its predecessors. Architectural details of Alpha Go Zero can be seen in this cheat sheet.
One of those improvements is using a single neural ...
- 1,684
11
votes
2
answers
9k
views
Why do we prefer ReLU over linear activation functions?
The ReLU activation function is defined as follows
$$y = \operatorname{max}(0,x)$$
And the linear activation function is defined as follows
$$y = x$$
The ReLU nonlinearity just clips the values ...
- 499
11
votes
3
answers
515
views
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....
- 513
10
votes
1
answer
1k
views
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 ...
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