All Questions
640 questions
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24
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How do neural scaling laws explain the improvements from LSTMs to Transformer based models
I was reading about a study on neural scaling laws from 2017 and they noted this as a summary. From Hestness, Joel; Narang, Sharan; Ardalani, Newsha; Diamos, Gregory; Jun, Heewoo; Kianinejad, Hassan; ...
- 279
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1
answer
53
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What is not an applicaton of AI?
With the AI era, everyone says everything is AI, which doesn't seem to be the case. What is advertised as AI and isn't?
For example, (1) Google's PageRank algorithm is called AI, is it really AI? (2) ...
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0
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37
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When should you use a transformer and when LSTM, GRU and other Neural Networks?
There is a lot of information on the Internet that the transformer is better than RNN in everything, but is it true?
Examples:
«What if I need to translate words?»
«Generate text, images?»
«Play a ...
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0
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22
views
What are the most useful AI features in smartphones for daily tasks?
I’ve been super curious about the AI stuff in smartphones lately. I know it’s everywhere now, but I’m not sure what’s actually useful for everyday stuff. Like, I’ve heard about voice assistants, ...
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2
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55
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Is there any actual difference between these 2 definitions of a state value function?
The definition of the value function in TRPO paper is
\begin{align}
V_\pi(s_t) &= \mathbb{E}_{a_t,s_{t+1},\ldots} \left[ \sum_{l=0}^{\infty} \gamma^l r(s_{t+l}) \right], \\[10pt]
a_t &\sim \pi(...
- 139
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votes
1
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108
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Does Machine Learning focus on discriminative AI while Deep Learning also focus on generative AI?
I know that Deep Learning is subset of Machine learning
But is it correct that classical ML algorithms mainly focus on implementing Discriminative AI while DL algorithms implement both Generative AI ...
- 181
0
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0
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17
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A concept for a simple NN as a transfer function for an hydraulic cylinder
For a RL project, my collagues and me need to create a virtual environment with an excavator, which needs to replicate a real existing excavator. The idea is to have a simulator, which simulate ...
- 204
0
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1
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107
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What are disadvantages/limitations of Monte Carlo Tree Search in RL?
What are disadvantages/limitations of Monte Carlo Tree Search in RL, and hence for what kind of applications might its use not be appropriate?
- 1,115
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2
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107
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What do we mean by "AI is correlated"?
From Wikipedia
Causal AI is a technique in artificial intelligence that builds a causal model and can thereby make inferences using causality rather than just correlation. One practical use for ...
- 117
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0
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28
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Need some feedback on an idea for using reinforcement learning in the context of medical imaging reconstruction
Disclaimer -- this idea may be totally half-baked, I'm not sure. I have used deep learning models in image reconstruction before (and this is a super hot topic in the field right now), but only in the ...
- 1
2
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2
answers
556
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Is it easier to use back-propagation or genetic algorithms to teach an artificial intelligence?
I am making a very simple neural network for a school project, and I would like to know what the best and easiest way to "teach" a neural network would be. From what I know, backpropagation ...
- 23
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0
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21
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Are there leaderboards/tables/stats that compare inference times between close-sourced LLMs such as GPT 3.5/4 and Claude?
https://huggingface.co/spaces/optimum/llm-perf-leaderboard is great to compare inference times between LLMs but it misses close-sourced LLMs such as GPT 3.5/4 and Claude.
- 3,267
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2
answers
1k
views
What is the difference between densenet and resnet?
Is the only difference between the two how the skip connection is combined? Resnet combines skip connections through addition and Densenet through concatenating.
The Densenet paper appears to be ...
- 233
2
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1
answer
618
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Is it possible to detect image manipulation, for example deep fakes?
Is it possible to detect image manipulation, for example deep fakes?
I will publish some photos on internet, and want others to be able to verify if photos are really from me, and also to detect if ...
- 29
2
votes
1
answer
116
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How are POMDPs solved in practice?
In the literature that I've seen so far on how to either exactly or approximately solve POMDPs (Partially-Observable Markov Decision Processes), there seems to be a lot of focus placed on maintaining ...
- 123
1
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1
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98
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Is there any advantage of genetic algorithm (or programming) over Neural Networks? [closed]
I am planning to switch from neural networks to genetic algorithms (GA) and programming (GP).
One of the main hassles of working with neural networks is that it requires a large amount of training ...
- 339
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2
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61
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Should I define my problem as image segmentation or detection?
I have a problem and have to decide wether it's an object detection or object segmentation problem. I want to use Yolov8 for training. We already have hundrets of images but they aren't labeled yet. ...
- 113
1
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1
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1k
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When to use Pruning, Quantization , Distillation and others when optimizing speed
I want to understand how to optimize models for inference speed and am seeking some advice and best practices for the same.
I am a little bit aware of the concepts of pruning, quantization, and ...
- 789
4
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2
answers
3k
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What are the differences between seq2seq and encoder-decoder architectures?
I've read many tutorials online that use both words interchangeably. When I search and find that they are the same, why not just use one word since they have the same definition?
user78615
1
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1
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133
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Why are these two implementations of the $\epsilon$-greedy policy different?
According to the book Reinforcement Learning An Introduction, the epsilon greedy policy can generally implemented as:
$$
\pi(a|s) =
\begin{cases}
\frac{\epsilon}{|A|} + 1 - \epsilon & \text{if } ...
- 195
2
votes
1
answer
541
views
What are the similarities between Q-learning and Value Iteration?
This is the explanation of value iteration in our notes where you keep applying bellman optimality equation till it stops changing and then acting greedily wrt the value function gives the optimal ...
- 23
1
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1
answer
48
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Is there validation data in K-fold cross-validation?
We know that in machine learning the dataset is divided into 3 parts: training data, validation data and test data.
On the other hand, K-fold cross-validation is defined as follows:
the dataset is ...
- 1,115
0
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1
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247
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What is the difference between Machine Learning model, algorithm and hypothesis?
I'm fairly new to Machine Learning field and still to grasp the basics, so this question may seem very stupid, but what is the difference between Machine Learning model, algorithm and hypothesis?
Like ...
2
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1
answer
82
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Forum to discuss deep learning ideas
Is anyone aware of an idea exchange for ai/deep learning/data science? I occasionally have ideas that don't relate to my focus areas that I would love to discuss with those who might like to hear ...
- 21
0
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1
answer
140
views
Which search algorithm expands nodes closest to the goal?
I want to know which search algorithm among A* and Best-First Search and Greedy First Search expands nodes closest to the goal. I have three opinions about A* and Best-First Search and Greedy First ...
- 3
0
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1
answer
169
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What is the difference between A/B testing and Reinforcement Learning?
I was learning ML, and I learnt a new section called, Reinforcement Learning. After some research on web, I found that it is a trial and error technique by which ...
0
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1
answer
192
views
How are the intuitions and mathematics of attention mechanisms related to those of PageRank?
Excuse me if you find this question too vague and not fitting to this forum and feel free to close it. The overall goal of my question is to get a better intuition of the attention concept and ...
4
votes
1
answer
289
views
How does Monte-Carlo Tree Search Compare to MCMC?
Monte-Carlo Tree Search was the method used for AlphaGo my understanding is: it would randomly search the state space of possible moves where the probability of choosing a move was proportional to the ...
- 454
4
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1
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2k
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What's the difference between GPT3.5 and InstructGPT?
I read about the different model series in GPT3.5 here - https://platform.openai.com/docs/models/gpt-3-5
At the beginning of the page, it mentions to look at https://platform.openai.com/docs/model-...
- 41
1
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1
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85
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Are on-policy algorithms always better than off-policy ones?
I am studying RL and I have a question: Are on-policy algorithms always better than off-policy ones?
1
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1
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96
views
How are these two equations for the optimal state-value function equivalent?
By substituting the optimal policy $\pi_{\star}$ into the Bellman equation, we get the Bellman equation for $v_{\pi_{\star}}(s)=v_{\star}(s)$:
$$ v_{\star}(s) = \sum\limits_a \pi_{\star}(a|s) \sum\...
- 1,115
3
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1
answer
588
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Do the terms 'sample complexity' and 'sample efficiency' mean the same thing in RL context
For example, the the paper Soft Actor-Critic:Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor, both terms are mentioned but without explaining. I have seen them in other ...
- 195
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1
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4k
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What's the difference between classification and segmentation in deep learning?
What's the difference between classification and segmentation in deep learning?
In particular, can the classification loss function be used for segmentation problems?
1
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0
answers
38
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What is the precise relation between Swarm Intelligence and Ensemble Methods?
I come from the machine learning side of AI, and have recently become more interested in the bio-inspired side of AI. Specifically I started reading about swarm intelligence and immediately started ...
- 11
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0
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50
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Are autoencoders computationally cheaper than MLPs with the same number of neurons?
Are autoencoders computationally cheaper than other neural networks such as MLP with the same number of neurons?
I have read in some papers that autoencoders train the network faster, and I could ...
- 1
0
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0
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1k
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What are the similarities and differences between ChatGPT and YouChat?
I have recently tried the both, and it looks to me that the both have similar capabilities.
YouChat says ChatGPT is more advanced.
YouChat has connection to the Internet, and according to it, ...
- 351
1
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1
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681
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For specific tasks, is it better to fine-tune models on examples or just use prompting with the context of the task?
These days large language models cover a vast amount of topics and information, but I wanted to understand: For specific tasks, is it better to fine-tune models on examples or just use prompting with ...
- 113
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2
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909
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Should I use multi-armed-bandits or RL for a financial time-series problem?
If we take simple financial timeseries data(stock/commodity/currency prices), State(t+1) does not depend on the action that we choose to take at State(t) as in Maze or Chess problem.
Simple example: ...
- 3
-1
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1
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452
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Is my understanding correct regarding the difference between policy and plan?
I am confused regarding the difference between policy and plan in reinforcement learning. According to my understanding, when we calculate the value of state using Bellman equation in deterministic ...
- 111
1
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0
answers
94
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How do transformers compare to CNNs in terms of compute budget (and computing time) during inference?
Transformers are data and GPU hungry during training. Is this also true at inference time? How do transformers compare to feedforward CNNs e.g., during bounding box generation at inference time? I ...
- 433
1
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0
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24
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Is there an AI technique (or general programming technique) suitable for seeing if two articles deal with the same event?
I'm looking for a way to work out if two or more articles deal with the same event or issue and I'm not sure where to start.
For example, back in August 2022 there were a few articles on the latest ...
- 11
3
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2
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4k
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What is the difference between A2C and Q-Learning, and when to use one over the other?
I'm trying to get an accurate answer about the difference between A2C and Q-Learning. And when can we use each of them?
- 33
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1
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283
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Why and when do we use ReLU over tanh activation function?
I was reading LeCun Efficient Backprop and the author repeated stressed the importance of average the input patterns at 0 and thus justified the usage of tanh sigmoid. But if tanh is good then how ...
0
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0
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62
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As someone starting out in RL, could you help me understand the differences between actor-only, critic-only, and actor-critic methods?
I have been reading some medium articles and these three methods pop up a lot. I am wondering what the differences between these are, what are the advantages of one over the other, etc. Also from my ...
- 101
3
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1
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9k
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Does SAC perform better than PPO in sample-expensive tasks with discrete action spaces?
I am currently using Proximal Policy Optimization (PPO) to solve my RL task. However, after reading about Soft Actor-Critic (SAC) now I am unsure whether I should stick to PPO or switch to SAC. ...
- 53
1
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1
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982
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Why does mean episode reward during training differ dramatically from "manual" runs of the trained model on same data?
I am training an RL agent, using PPO, on a time-series environment that comes from a tabular dataset. The possible scores during an episode goes from -1 to positive infinity (though realistically, I ...
- 362
3
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2
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1k
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Does LSTM provide any unique value or advantages compared to other algorithms, including "vanilla" RNN?
I have heard a lot of hype around LSTM for all kinds of time-series based applications including NLP. Despite this, I haven't seen many (if any) applications of LSTM where LSTM performs uniquely well ...
- 362
2
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0
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153
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Today's Practicality of Bayesian Neural Networks
Just having heard lately about BNNs (wow, ANNs and CNNs are clear; now there's a B? What's that? Ahh, Bayesian ;-)) and quickly getting their main idea and focus, that is, weights not being pure ...
- 153
2
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0
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111
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When are traditional image processing methods preferable to machine learning and why?
By traditional image processing I understand, e. g. using filters to improve the image, extracting edges and then classifying objects using template matching.
My current decision criteria are:
large ...
- 21
10
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1
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9k
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What is the difference between the triplet loss and the contrastive loss?
What is the difference between the triplet loss and the contrastive loss?
They look same to me. I don't understand the nuances between the two. I have the following queries:
When to use what?
What ...
- 373