conversation_id int64 0 999 | messages listlengths 2 2 |
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0 | [
{
"context": "Could a paradox kill an AI? In Portal 2 we see that AI's can be \"killed\" by thinking about a paradox.\n\nI assume this works by forcing the AI into an infinite loop which would essentially \"freeze\" the computer's consciousness.\nQuestions: \n\nWould this confuse the AI technology we have today... |
1 | [
{
"context": "How could self-driving cars make ethical decisions about who to kill? Obviously, self-driving cars aren't perfect, so imagine that the Google car (as an example) got into a difficult situation.\nHere are a few examples of unfortunate situations caused by a set of events:\n\nThe car is heading towa... |
2 | [
{
"context": "How can neural networks deal with varying input sizes? As far as I can tell, neural networks have a fixed number of neurons in the input layer.\nIf neural networks are used in a context like NLP, sentences or blocks of text of varying sizes are fed to a network. \nHow is the varying input size rec... |
3 | [
{
"context": "Do scientists know what is happening inside artificial neural networks? Do scientists or research experts know from the kitchen what is happening inside complex \"deep\" neural network with at least millions of connections firing at an instant? Do they understand the process behind this (e.g. what... |
4 | [
{
"context": "What is self-supervised learning in machine learning? What is self-supervised learning in machine learning? How is it different from supervised learning?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"context": "Introduction\nThe term self-su... |
5 | [
{
"context": "How is it possible that deep neural networks are so easily fooled? The following page/study demonstrates that the deep neural networks are easily fooled by giving high confidence predictions for unrecognisable images, e.g.\n\n\nHow this is possible? Can you please explain ideally in plain English?... |
6 | [
{
"context": "Why does the transformer do better than RNN and LSTM in long-range context dependencies? I am reading the article How Transformers Work where the author writes\n\nAnother problem with RNNs, and LSTMs, is that it’s hard to parallelize the work for processing sentences, since you have to process wor... |
7 | [
{
"context": "Why do we need explainable AI? If the original purpose for developing AI was to help humans in some tasks and that purpose still holds, why should we care about its explainability? For example, in deep learning, as long as the intelligence helps us to the best of their abilities and carefully arri... |
8 | [
{
"context": "Why is Python such a popular language in the AI field? First of all, I'm a beginner studying AI and this is not an opinion-oriented question or one to compare programming languages. I'm not implying that Python is the best language. But the fact is that most of the famous AI frameworks have primar... |
9 | [
{
"context": "Are neural networks prone to catastrophic forgetting? Imagine you show a neural network a picture of a lion 100 times and label it with \"dangerous\", so it learns that lions are dangerous.\nNow imagine that previously you have shown it millions of images of lions and alternatively labeled it as \... |
10 | [
{
"context": "What are some well-known problems where neural networks don't do very well? Background: It's well-known that neural networks offer great performance across a large number of tasks, and this is largely a consequence of their universal approximation capabilities. However, in this post I'm curious a... |
11 | [
{
"context": "How does ChatGPT retain the context of previous questions? One of the innovations with OpenAI's ChatGPT is how natural it is for users to interact with it.\nWhat is the technical enabler for ChatGPT to maintain the context of previous questions in its answers? For example, ChatGPT understands a pr... |
12 | [
{
"context": "How could artificial intelligence harm us? We often hear that artificial intelligence may harm or even kill humans, so it might prove dangerous.\nHow could artificial intelligence harm us?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"contex... |
13 | [
{
"context": "What is fuzzy logic? I'm new to A.I. and I'd like to know in simple words, what is the fuzzy logic concept? How does it help, and when is it used?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"context": "As complexity rises, precise statemen... |
14 | [
{
"context": "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?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"context":... |
15 | [
{
"context": "To what extent can quantum computers help to develop Artificial Intelligence? What aspects of quantum computers, if any, can help to further develop Artificial Intelligence?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"context": "Quantum co... |
16 | [
{
"context": "Can digital computers understand infinity? As a human being, we can think infinity. In principle, if we have enough resources (time etc.), we can count infinitely many things (including abstract, like numbers, or real).\nFor example, at least, we can take into account integers. We can think, princ... |
17 | [
{
"context": "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 state, policy gradients dire... |
18 | [
{
"context": "What is the time complexity for training a neural network using back-propagation? Suppose that a NN contains $n$ hidden layers, $m$ training examples, $x$ features, and $n_i$ nodes in each layer. What is the time complexity to train this NN using back-propagation? \nI have a basic idea about how t... |
19 | [
{
"context": "How do capsule neural networks work? Geoffrey Hinton has been researching something he calls \"capsules theory\" in neural networks. What is it? How do capsule neural networks work?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"context": "It... |
20 | [
{
"context": "How should I handle invalid actions (when using REINFORCE)? I want to create an AI which can play five-in-a-row/Gomoku. I want to use reinforcement learning for this.\nI use the policy gradient method, namely REINFORCE, with baseline. For the value and policy function approximation, I use a neural... |
21 | [
{
"context": "Could a neural network detect primes? I am not looking for an efficient way to find primes (which of course is a solved problem). This is more of a \"what if\" question.\nSo, in theory, could you train a neural network to predict whether or not a given number $n$ is composite or prime? How would s... |
22 | [
{
"context": "What is the difference between latent and embedding spaces? In general, the word \"latent\" means \"hidden\" and \"to embed\" means \"to incorporate\". In machine learning, the expressions \"hidden (or latent) space\" and \"embedding space\" occur in several contexts. More specifically, an embeddi... |
23 | [
{
"context": "What is the purpose of an activation function in neural networks? It is said that activation functions in neural networks help introduce non-linearity.\n\nWhat does this mean?\nWhat does non-linearity mean in this context?\nHow does the introduction of this non-linearity help?\nAre there any other... |
24 | [
{
"context": "How is ChatGPT aware of today's date? I asked ChatGPT (3.5 and 4) about current date and (s)he answered correctly. In subsequent conversation (s)he was not able to explain how (s)he has this knowledge.\nI always thought that the model only sees the conversation above and a pretrained NN is used. H... |
25 | [
{
"context": "What is the \"temperature\" in the GPT models? What does the temperature parameter mean when talking about the GPT models?\nI know that a higher temperature value means more randomness, but I want to know how randomness is introduced.\nDoes temperature mean we add noise to the weights/activations ... |
26 | [
{
"context": "What is the concept of the technological singularity? I've heard the idea of the technological singularity, what is it and how does it relate to Artificial Intelligence? Is this the theoretical point where Artificial Intelligence machines have progressed to the point where they grow and learn on t... |
27 | [
{
"context": "Is the \"Chinese room\" an explanation of how ChatGPT works? Sorry if this question makes no sense. I'm a software developer but know very little about AI.\nQuite a while ago, I read about the Chinese room, and the person inside who has had a lot of training/instructions how to combine symbols, an... |
28 | [
{
"context": "Why is Lisp such a good language for AI? I've heard before from computer scientists and from researchers in the area of AI that that Lisp is a good language for research and development in artificial intelligence.\n\nDoes this still apply, with the proliferation of neural networks and deep learnin... |
29 | [
{
"context": "How can Transformers handle arbitrary length input? The transformer, introduced in the paper Attention Is All You Need, is a popular new neural network architecture that is commonly viewed as an alternative to recurrent neural networks, like LSTMs and GRUs.\nHowever, having gone through the paper,... |
30 | [
{
"context": "Why do CNN's sometimes make highly confident mistakes, and how can one combat this problem? I trained a simple CNN on the MNIST database of handwritten digits to 99% accuracy. I'm feeding in a bunch of handwritten digits, and non-digits from a document.\nI want the CNN to report errors, so I set a... |
31 | [
{
"context": "How does the (decoder-only) transformer architecture work? How does the (decoder-only) transformer architecture work which is used in impressive models such as GPT-4?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"context": "Introduction\nLar... |
32 | [
{
"context": "Can BERT be used for sentence generating tasks? I am a new learner in NLP. I am interested in the sentence generating task. As far as I am concerned, one state-of-the-art method is the CharRNN, which uses RNN to generate a sequence of words.\nHowever, BERT has come out several weeks ago and is ver... |
33 | [
{
"context": "Is a switch from R to Python worth it? 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.\nWhat are the advantages that Python may have over R in terms of features applicable to the field of Data Scie... |
34 | [
{
"context": "Is it possible to train the neural network to solve math equations? I'm aware that neural networks are probably not designed to do that, however asking hypothetically, is it possible to train the deep neural network (or similar) to solve math equations?\nSo given the 3 inputs: 1st number, operator... |
35 | [
{
"context": "How to find the optimal number of neurons per layer? When you're writing your algorithm, how do you know how many neurons you need per single layer? Are there any methods for finding the optimal number of them, or is it a rule of thumb?\n",
"images": null,
"role": "user",
"thinking": n... |
36 | [
{
"context": "How does an AI like ChatGPT answer a question in a subject which it may not know? After seeing StackOverflow's banning of ChatGPT, I explored it out of curiosity. It's marvellous as it can write code by itself!\nLater to check if it knows chess as well like Google-Deepmind's AlphaZero AI, I asked ... |
37 | [
{
"context": "What is sample efficiency, and how can importance sampling be used to achieve it? For instance, the title of this paper reads: \"Sample Efficient Actor-Critic with Experience Replay\".\nWhat is sample efficiency, and how can importance sampling be used to achieve it?\n",
"images": null,
"r... |
38 | [
{
"context": "How can I deal with images of variable dimensions when doing image segmentation? I'm facing the problem of having images of different dimensions as inputs in a segmentation task. Note that the images do not even have the same aspect ratio.\nOne common approach that I found in general in deep learn... |
39 | [
{
"context": "Where can I find the proof of the universal approximation theorem? The Wikipedia article for the universal approximation theorem cites a version of the universal approximation theorem for Lebesgue-measurable functions from this conference paper. However, the paper does not include the proofs of th... |
40 | [
{
"context": "What is the Bellman operator in reinforcement learning? In mathematics, the word operator can refer to several distinct but related concepts. An operator can be defined as a function between two vector spaces, it can be defined as a function where the domain and the codomain are the same, or it ca... |
41 | [
{
"context": "What is the credit assignment problem? In reinforcement learning (RL), the credit assignment problem (CAP) seems to be an important problem. What is the CAP? Why is it relevant to RL?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"context": "... |
42 | [
{
"context": "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?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"context": "The differe... |
43 | [
{
"context": "Is it possible to train a neural network as new classes are given? I would like to train a neural network (NN) where the output classes are not (all) defined from the start. More and more classes will be introduced later based on incoming data. This means that, every time I introduce a new class, ... |
44 | [
{
"context": "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:\n\nHow is Bert different from the original transformer architecture?\n\nWhat tasks are better suited for BERT, and what tasks are better ... |
45 | [
{
"context": "What are \"bottlenecks\" in neural networks? What are \"bottlenecks\" in the context of neural networks?\nThis term is mentioned, for example, in this TensorFlow article, which also uses the term \"bottleneck values\". How does one calculate bottleneck values? How do these values help image classi... |
46 | [
{
"context": "Is Lisp still being used to tackle AI problems? I know that language of Lisp was used early on when working on artificial intelligence problems. Is it still being used today for significant work? If not, is there a new language that has taken its place as the most common one being used for work in... |
47 | [
{
"context": "Are Siri and Cortana AI programs? Siri and Cortana communicate pretty much like humans. Unlike Google Now, which mainly gives us search results when asked some questions (not setting alarms or reminders), Siri and Cortana provide us with an answer, in the same way that a person would do.\nSo, are ... |
48 | [
{
"context": "How could we build a neural network that is invariant to permutations of the inputs? \nGiven a neural network $f$ that takes as input $n$ data points: $x_1, \\dots, x_n$. We say $f$ is permutation invariant if\n$$f(x_1 ... x_n) = f(\\sigma(x_1 ... x_n))$$\nfor any permutation $\\sigma$.\n\nHow cou... |
49 | [
{
"context": "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.\n",
"images": null,
"role": "user",... |
50 | [
{
"context": "Is there any research on the development of attacks against artificial intelligence systems? Is there any research on the development of attacks against artificial intelligence systems?\nFor example, is there a way to generate a letter \"A\", which every human being in this world can recognize but... |
51 | [
{
"context": "What are the minimum requirements to call something AI? I believe artificial intelligence (AI) term is overused nowadays. For example, people see that something is self-moving and they call it AI, even if it's on autopilot (like cars or planes) or there is some simple algorithm behind it.\nWhat ar... |
52 | [
{
"context": "What exactly are the \"parameters\" in GPT-3's 175 billion parameters and how are they chosen/generated? When I studied neural networks, parameters were learning rate, batch size etc. But even GPT3's ArXiv paper does not mention anything about what exactly the parameters are, but gives a small hin... |
53 | [
{
"context": "Is Prolog still used in AI? According to Wikipedia,\n\nProlog is a general-purpose logic programming language associated with artificial intelligence and computational linguistics.\n\nIs it still used for AI?\n\nThis is based off of a question on the 2014 closed beta. The author had the UID of 330... |
54 | [
{
"context": "Why do ChatGPT “jailbreaks” work? Do developers not genuinely want to prevent them? It seems like if they are able to develop such impressive AI models then it wouldn’t be that difficult to create catch-all/wildcard mitigations to the various jailbreak methods that are devised over time.\nWhat giv... |
55 | [
{
"context": "Can the decoder in a transformer model be parallelized like the encoder? Can the decoder in a transformer model be parallelized like the encoder?\nAs far as I understand, the encoder has all the tokens in the sequence to compute the self-attention scores. But for a decoder, this is not possible (i... |
56 | [
{
"context": "How do I handle large images when training a CNN? Suppose that I have 10K images of sizes $2400 \\times 2400$ to train a CNN. \nHow do I handle such large image sizes without downsampling?\nHere are a few more specific questions.\n\nAre there any techniques to handle such large images which are to... |
57 | [
{
"context": "What is a Dynamic Computational Graph? Frameworks like PyTorch and TensorFlow through TensorFlow Fold support Dynamic Computational Graphs and are receiving attention from data scientists.\nHowever, there seems to be a lack of resource to aid in understanding Dynamic Computational Graphs.\nThe adv... |
58 | [
{
"context": "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.\nSo, what difference does the second point in bo... |
59 | [
{
"context": "What is non-Euclidean data? What is non-Euclidean data?\nHere are some sub-questions\n\nWhere does this type of data arise? I have come across this term in the context of geometric deep learning and graph neural networks.\n\nApparently, graphs and manifolds are non-Euclidean data. Why exactly is t... |
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