What type of AI is designed to perform a single or limited set of tasks, such as voice assistants? Artificial Superintelligence (ASI) Artificial Narrow Intelligence (ANI) Machine Learning Artificial General Intelligence (AGI)

Artificial Narrow Intelligence (ANI)

What is the term for hypothetical AI that can perform any intellectual task a human can? Cognitive Computing Artificial Superintelligence (ASI) Artificial Narrow Intelligence (ANI) Artificial General Intelligence (AGI)

Artificial General Intelligence (AGI)

What type of neural network is optimized for image recognition and processing using special filters? Convolutional Neural Network (CNN) Feedforward Neural Network Recurrent Neural Network (RNN) Radial Basis Function Network

Convolutional Neural Network (CNN)

What is a computational model inspired by the human brain, consisting of layers of artificial neurons? Support Vector Machine Deep Belief Network Artificial Neural Network (ANN) Biological Neural Network

Artificial Neural Network (ANN)

Understanding AI Concepts: From Deepfakes to Neural Networks

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Computer Science - Software Engineering

user_kambeorv Created by 7 mon ago

Cards in this deck(48)

What term describes AI-generated media that convincingly mimics real people, often used for entertainment or misinformation?

What is the name of the test proposed by Alan Turing to determine if a machine can exhibit human-like intelligence?

What type of AI is designed to perform a single or limited set of tasks, such as voice assistants?

What is the term for hypothetical AI that can perform any intellectual task a human can?

What technique involves adapting a pre-trained AI model to a new but similar task, reducing training time?

Which type of neural network is designed for processing sequential data by maintaining memory of previous inputs?

What type of neural network is optimized for image recognition and processing using special filters?

What is a computational model inspired by the human brain, consisting of layers of artificial neurons?

Which branch of machine learning uses multi-layered neural networks to analyze large amounts of data?

What is the network of interconnected neurons in the human brain that AI models attempt to mimic?

What are the individual computing units within artificial neural networks that process and pass information?

What are the adjustable parameters in a neural network that determine the importance of different inputs?

What function in neural networks determines whether a neuron should be activated based on input data?

What problem in machine learning occurs when one class in a dataset is much more common than another?

What is a step-by-step procedure or set of rules used to perform computations and solve problems?

What statistical model describes sequences of events where the next event depends only on the current state?

Which type of RNN can remember long-term dependencies, making it useful for text and speech recognition?

What machine learning method uses multiple decision trees to make more accurate and stable predictions?

What is a flowchart-like model used in machine learning to make decisions by splitting data into branches?

What optimization algorithm helps neural networks learn by adjusting weights to minimize errors?

What is a point in a mathematical function where a value is higher than nearby points but not the highest overall?

What problem in optimization involves the best solution being hidden among many poor ones?

What optimization techniques are inspired by natural selection, where AI 'evolves' better solutions over time?

What measure is used to evaluate how good a solution is within an evolutionary algorithm?

What is the process of generalizing from many concrete, low-level instances to fewer higher-order categories?

What is one of the earliest machine learning models, based on a simplified version of a human neuron?

What mechanical loom is capable of creating complex woven patterns by 'reading' encoded information on punch cards?

What early chatbot was modeled to mimic the behavior of a Rogerian psychotherapist?

In the writings of Paracelsus, what is a miniature artificial human endowed with superior knowledge and strength?

In Talmudic writings, what is a mechanical automaton with superhuman strength, created from dust and clay?

What is the specific neural-network architecture developed at Google in 2017 used in today's large language models?

What key innovation of the transformer architecture enables a large language model to update its response based on context?

What is the text input given to a language model to produce its response?

What are units of text, each with a numerical ID, used to encode language for processing by LLMs?

What term describes the amount of text used by an LLM to determine its output?

What parameter controls randomness in AI-generated text, where higher values result in more chaotic outputs?

What term describes AI-generated text that does not match a real-world fact?

What is the matrix of internal weights and biases in a neural network that captures key meanings about words?

What is the technique of providing a single example within a prompt to guide the AI's response format?

What prompting technique involves providing a stepwise sequence of decomposed tasks to guide complex thinking?

What prompting technique involves perfecting a prompt over multiple stages of trial-and-error?

What prompting technique involves including language associated with a specific role or personality?

What term describes AI-generated internet content being used to train the next generation of AI?

What is the degradation in LLM model behavior produced by autophagy called?

What is the deliberate act of feeding incorrect data to an AI so that it generates incorrect results?

What does RLHF stand for in the context of LLM training?

What stage of LLM training involves unsupervised training of a language model on large quantities of text?

What stage of LLM training involves lightly training models to update parameters toward a specific genre or task?

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Understanding AI Concepts: From Deepfakes to Neural Networks

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