Questions tagged [theory]

Use for questions on AI theory and other theoretical subjects related to AI.

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44 views

Input to "break" chatbots?

I was asked an interesting question today by a student in a cybersecurity and information assurance program related to getting spammed by chatbots on snapchat. He's tried many conventional means of ...
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2answers
60 views

What are the different types of goals for an AI system called?

I remember reading about two different types of goals for an intelligence. The gist was that the first type of goal is one that "just is" - it's an end goal for the system. There doesn't ...
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1answer
51 views

Flowchart for a simplified perceptron leaning algorithm [critique request]

I made a flowchart for a simplified perceptron leaning algorithm. Here is the process of the leaning algorithm. Step_1: Initialize the weights first. Step_2: Get a training example randomly and make ...
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1answer
35 views

Fitting a gaussian distribution into another distribution - and correlation with Machine Learning

Assume we have two vectors, containing random samples (maybe audio data?). Their distribution can be approximated to a normal distribution, so we can calculate their mean and standard deviation. I am ...
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0answers
28 views

How to detect dynamic hand gestures?

I already know how to detect static hand gestures like fist, peace etc. I wonder however, how to detect dynamic hand gestures like swipe left/right or "draw" circle with hand. Is some kind ...
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0answers
29 views

What would happen if we set the evaluation function in the best-first search algorithm as the cost of paths taken to new nodes?

I am reading AI: A Modern Approach. In Chapter 3, Section 3.3.1, The best-first search algorithm is introduced. We learn that in each iteration, this algorithm chooses which node to expand based on ...
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3answers
131 views

How much can the addition of new features improve the performance?

How much can the addition of new features improve the performance of the model during the optimization process? Let's say I have a total of 10 features. Suppose I start the optimisation process using ...
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0answers
110 views

What is the difference between learning agents and other kinds of agents, and more specifically, between performance standard and performance measure?

I am reading AI: A Modern Approach. In the 2nd chapter when introducing different agent types, i.e., reflex, utility-based, goal-based, and learning agents, I understood that all types of agents, ...
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2answers
676 views

Is there any scientific/mathematical argument that prevents deep learning from ever producing strong AI?

I read Judea Pearl's The Book of Why, in which he mentions that deep learning is just a glorified curve fitting technology, and will not be able to produce human-like intelligence. From his book ...
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2answers
6k views

What is convergence in machine learning?

I came across this answer on Quora, but it was pretty sparse. I'm looking for specific meanings in the context of machine learning, but also mathematical and economic notions of the term in general.
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2answers
6k views

What is the difference between goal-based and utility-based agents?

What is the difference between goal-based and utility-based agents? Please, provide a real-world example.
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1answer
53 views

What is "Pattern Theory"?

I came across Grenander's work "Probabilities on Algebraic Structures" recently and found that much of Grenander's work focused on what he called "Pattern Theory." He's written ...
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1answer
45 views

The are some fundamental learning theories for developing an AI that imitates human behavior

Most if not all AI systems are not to imitate human, but to finally out-perform human. Examples include using AI to play a game, classification problems, auto-driving, and goal-oriented chatbots. ...
2
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1answer
99 views

Is GPT-3 an early example of Strong AI in a Narrow setting?

In GPT-2, the large achievement was being able to generate coherent text over a long-form while maintaining context. This was very impressive but for GPT-2 to do new language tasks, it had to be ...
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7answers
2k views

What are the most instructive movies about artificial intelligence?

The field of AI has expanded profoundly in recent years, as has public awareness and interest. This includes the arts, where fiction about AI has been popular since at least Isaac Asimov. Films on ...
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4answers
576 views

Is the singularity something to be taken seriously?

The term Singularity is often used in mainstream media for describing visionary technology. It was introduced by Ray Kurzweil in a popular book The Singularity Is Near: When Humans Transcend Biology (...
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35 views

Is it a good idea to train a neural network to classify images without base-hypothesis?

I'm a relative beginner in deep-learning (understand by that, I'm doing my first kaggle competition right now, and I have loads to learn still) and I was just wondering something. Let's say you have ...
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1answer
85 views

How artificial intelligence will change the future?

AI is the emerging field and biggest business opportunity of the next decade. It's already automating manual and repetitive tasks. And in some areas, it can learn faster than humans, if not yet as ...
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4answers
14k views

Are neural networks prone to catastrophic forgetting?

Imagine you show a neural network a picture of a lion 100 times and label with "dangerous", so it learns that lions are dangerous. Now imagine that previously you have shown it millions of images of ...
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1answer
3k 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 ...
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0answers
27 views

Did people analyze dynamics of very simple LSTMs?

I wonder if researchers tried to understand how LSTMs work by analyzing the dynamics of simple LSTM (e.g. with 2 units)? For example how the hidden state evolves depending on the properties of weight ...
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0answers
57 views

Is there any application of topology to deep learning?

Is there any application of topology (as in math discipline) to deep learning? If so, what are some examples?
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2answers
50 views

Is it theoretically possible (or impossible) that principal component analysis worsens the performance of the model?

In case I had a prediction model and decided to add a PCA step prior to the model, is it theoretically possible/impossible that the number of output dimensions that is better for all tests may perform ...
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0answers
35 views

Is there a theory that captures the following ideas?

A big class of problems that are relevant in today's society are full of uncertainty and are also sometimes computationally intractable. Along our lives we come to realize that we are solving the same ...
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2answers
264 views

What are some examples of classical AI methods?

All of the attention in the AI field over the past few years has been toward statistical AI, now that Machine Learning has been validated on hard problems. However, I want to learn more about ...
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1answer
52 views

What is the theoretical basis for the use of Cross Validation set?

So let's follow this line of reasoning. We use a MLE estimator (implementation doesn't matter) and we have a train set. We assume that we have sampled training set from a Gaussian distribution $\...
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0answers
20 views

Suitable kernels for Gaussian processes

Consider a stochastic process $\{X_t \colon t \in T\}$ indexed by a set $T$. We assume for simplicty that $T \in \mathbb{R}^n$. We assume that for any choice of indexes $t_1, \dots, t_n$, the random ...
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2answers
164 views

Understanding CNN in a few sentences

I don't know if this is the right place to ask this question. If it is not, please tell me and I remove it. I've just started to learn CNN and I'm trying to understand what they do and how they do it....
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1answer
64 views

Is there a way to ensure that my model is able to recognize an unseen example?

My question is more theoretical than practical. Let's say that I am training my cat classifier with a dataset that I feel is pretty representative of cat images in general. But then a new breed of cat ...
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1answer
51 views

How many ways are there to perform image segmentation?

I'm new in Artificial Intelligence and I want to do image segmentation. Searching I have found these ways Digital image processing (I have read it in this book: Digital Image Processing, 4th edition)...
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1answer
188 views

What make a CNN suitable for image classification or for semantic segmentation?

I've just started with CNN and there is something that I haven't understood yet: How do you "ask" a network: "classify me these images" or "do semantic segmentation"? I think it must be something on ...
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0answers
516 views

What does "episodic training" mean?

I'm reading the book Hands-On Meta Learning with Python, and in Prototypical networks said: So, we use episodic training—for each episode, we randomly sample a few data points from each class in ...
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0answers
80 views

Is this a problem well suited for machine learning?

The light-field of a certain scene is the set of all light rays that travel through the volume of that scene at a specific point of time. A light-field camera for example captures and stores a subset ...
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2answers
200 views

Are current AI models sufficient to achieve Artificial General Intelligence?

I read an interesting essay about how far we are from AGI. There were quite a few solid points that made me re-visit the foundation of AI today. A few interesting concepts arose: imagine that you ...
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2answers
669 views

How can the multiple intelligences model be incorporated into AI?

I have been wondering since a while ago about the theory of multiple intelligences and how they could fit in the field of Artificial Intelligence as a whole. We hear from time to time about Leonardo ...
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0answers
31 views
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1answer
121 views

When are compiled vs. interpreted languages more optimal in AI?

When are interpreted languages more optimal? When are compiled languages more optimal? What are the qualities and functions that render the so in relation to various AI methods?
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1answer
80 views

How Dempster-Shafer theory work in AI?

How does Dempster-Shafer theory work in representing ignorance in AI field?
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4answers
5k views

What are the current theories on the development of a conscious AI?

What are the current theories on the development of a conscious AI? Is anyone even trying to develop a conscious AI? Is it possible that consciousness is an emergent phenomenon, that is, once we put ...
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1answer
707 views

What does 'democratizing AI' exactly mean?

In my AI literature research, I often notice authors use term 'democratizing AI', especially in the AutoML area. I think I have an idea of what this means, but I would like to ask you for some more ...
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3answers
165 views

Is there a way to understand neural networks without using the concept of brain?

Is there a way to understand, for instance, a multi-layered perceptron without hand-waving about them being similar to brains etc? For example: it is obvious that what a perceptron does is ...
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2answers
199 views

Is it possible to build an AI that learns humanity, morally?

It is a new era and people are trying to evolve more in science and technology. Artificial Intelligent is one of the ways to achieve this. We have seen lots of examples for AI sequences or a simple "...
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5answers
319 views

Is it possible for an AI to work in a computer without the power cord being plugged in?

Could an Artificial Intelligence be able to interact (see, talk, etc.) with someone even when there's no power cord connected to the machine it's running on? Might it find some way to generate its own ...
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2answers
86 views

Is the gradient at a layer independent of the activations of the previous layers?

Is the gradient at a layer (of a feed-forward neural network) independent of the activations of the previous layers? I read this in a paper titled Mean Field Residual Networks: On the Edge of Chaos (...
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1answer
40 views

Why is image classification tasks are dominated by minimizing cost function instead of maximizing ones?

I was watching a video of policy gradient by Andrej Karpathy at 10:00 there shows an equation for supervised learning for image classification. $max\sum _{i}log \:p(y_i|x_i)$ I have worked with ...
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1answer
255 views

Can NEAT produce neural networks where inputs are directly connected to outputs?

Can NEAT produce neural networks where inputs are directly (without intermediate hidden neurons) connected to outputs?
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1answer
91 views

How can I systematically learn about the theory of neural networks?

I have seen a few articles about neural nets. Mostly they went along these lines: we tried these architectures, these meta parameters, we trained it for $x$ hours on $y$ CPUs, and it gave us these ...
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9answers
1k views

Can Neural Networks self-optimize?

Suppose that you show a neural network its own code, and allow it to edit itself? Can a neural network modify its own weights and architecture (the number of layers, the number of neurons per layer, ...
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1answer
195 views

What does "hard for AI" look like?

In theoretical computer science, there is a massive categorization of the difficulty of various computational problems in terms of their asymptotic worst-time computational complexity. There doesn't ...
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0answers
43 views

Why do neural networks have bias units?

Why do neural networks have bias units? Why is it sometimes okay to opt them out?