Glossary of Artificial Intelligence
Understand key concepts like AI-human interlacing, AGI, cyborgs, and the technological singularity, AI containment, or Quantum AI.
Glossary of the book “Machines of Tomorrow: From AI Origins to Superintelligence & Posthumanity.” How AI Will Shape Our World.
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AI-Human Interlacing or Interlace: a technological, physical, and psychological interrelationship between humans and AI that results in the progressive erosion of the boundaries between the two. Humans influence AI by designing and training its algorithms and platforms. AI influences humans through cyborg implants, brain-computer interfaces, and AI-powered synthetic biological technologies, all of which modify the essence of human nature. Through these interactions, AI and humans get into a series of evolutive cycles, potentially resulting in a number of post-human hybrid species.
AI Superstars or Superstars: highly successful individuals in the tech and AI-driven economy who leverage digital technologies to amass vast wealth, control markets, and influence politics.
Artificial Emotional Intelligence (AEI): the capability of AI systems to comprehend, interpret, and respond to human emotions, enhancing their ability to engage with users on a more emotionally intelligent level.
Artificial General Intelligence (AGI) or General AI: AI systems that possess human-level intelligence and can understand, learn, and adapt to a wide range of tasks, similar to the broad capabilities of the human mind.
Artificial Super Intelligence (ASI) or Superintelligence: a highly advanced form of AI that surpasses human intelligence in all aspects.
Artificial Intelligence (AI): computer systems capable of executing complex tasks that typically require human intelligence, such as learning from experience, solving problems, or understanding natural language.
Containment: strategies and safeguards used to control and limit the behavior of AI systems, mainly to prevent them from causing harm or taking actions that go against human values and objectives.
Convolutional Neural Network (CNN): a specialized neural network designed for analyzing structured data, particularly well-suited for tasks involving grid-like information, such as images.
Cyborg or Cybernetic Organism: a being that combines biological and mechanical or electronic components. This can include humans with implanted technology to enhance their abilities or even robots with biological elements.
Deep Learning: a Machine Learning form that relies on neural networks featuring a large number of layers, or deep neural networks, to model and solve complex tasks. It is especially good at tasks like image and speech recognition.
Faustian Bargain: a deal in which a person sacrifices their core principles in exchange for personal gain, often at great cost. It is derived from the character Faust in German folklore, who makes a pact with the devil for knowledge and power, ultimately leading to his downfall.
Generative AI: AI models that generate new content, such as text, images, or music, based on patterns and examples in existing data.
Genetic Divide: unequal access to emerging human enhancement technologies, which intensifies socio-economic disparities by disproportionately favoring those with greater financial resources.
Humanoid, or Android: a robot that imitates human physical characteristics, such as body shape and movement abilities. Humanoid robotics aims to create machines capable of performing tasks in human-centered environments.
Industrial Automation: control systems, machinery, and technologies to operate industrial processes with minimal human intervention. By automating repetitive tasks and processes, industrial automation aims to increase efficiency, productivity, and safety in manufacturing and production environments.
Large Language Model (LLM): a sophisticated AI algorithm designed to understand and generate human-like text based on extensive training on diverse linguistic data. These models, such as GPT-3, possess the capability to comprehend context, generate coherent responses, complete or summarize texts, translate, engage in conversations, and analyze sentiments, among other tasks.
Machine Learning (ML): a subset of AI that equips computer systems with the ability to autonomously improve their performance on specific tasks by learning from data and experiences without the need for explicit, rule-based programming.
Machine Vision: technology used to equip computers to interpret visual information, such as images or videos. It is commonly used for tasks like object recognition and quality control in manufacturing.
Mind Uploading or Mind Emulation: the theoretical process of transferring an individual’s consciousness, memories, and cognitive functions from a biological brain to a digital or artificial substrate, with the objective of emulating those mental functions in the new substrate.
Narrow or Weak Artificial Intelligence: AI systems that, despite possibly having general intelligence characteristics similar to humans, lack sentience, consciousness, or self-awareness.
Neural Network (NN): a computational model inspired by the human brain. It comprises interconnected nodes or neurons that process information and can be used in Machine Learning applications, most specifically deep learning.
Operating System (OS): a program that controls all other application applications on the computer after being first loaded by the boot program. It is the governing rules of the computer. Examples include Windows, iOS, and Android. Each OS is distinct from each other, generally running different types of hardware configurations while enabling some but not complete compatibility among applications. By extension, the unique culture, economy, and Government of any society, from bees to humans, can be regarded as its OS.
Posthumanity: a group of species and societies that emerge as a result of substantial augmentations and modifications to human beings, often achieved through AI-powered technologies such as cyborg implants and synthetic biology. These modifications lead to enhanced physical and cognitive abilities, transcending the conventional boundaries of human existence.
Quadrupedal Robot: a type of robot that moves on four legs, resembling the locomotion of quadruped animals like dogs and horses. These robots are valued for their stability and adaptability, making them suitable for traversing challenging terrains and performing search and rescue missions.
Quantum Computing: a kind of computing that leverages the principles of quantum mechanics. While still largely experimental, quantum computers have the potential to be much faster than classical computers at specific tasks and calculations, especially in areas like cryptography and complex simulations.
Quantum Supremacy: a milestone in quantum computing where a quantum computer performs a specific computational task faster than the most powerful classical computer.
Recurrent Neural Network (RNN): a neural network that processes data sequences. It can maintain a memory of past inputs, making it suitable for time series analysis, Natural Language Processing, or other sequential data.
Reinforcement Learning: a family of Machine Learning algorithms that make sequential decisions by interacting with the surrounding environment, typically a game, market, or user. AI agents implementing this approach receive feedback in the form of rewards and penalties, and its goal is to find a strategy that optimizes the cumulative gain over time.
Robot: a programmable, mechanical device designed to perform tasks autonomously or semi-autonomously. Robots can range from simple, single-purpose machines to complex, multifunctional systems. Robots execute physical movements and actions, often in response to environmental stimuli, pre-programmed instructions, or AI algorithms.
Robotic Arm: a mechanized limb or manipulator designed to perform various tasks, often with precision and dexterity. Robotic arms are programmable and typically used in applications that require controlled movements, such as manufacturing, assembly, and surgery.
Self-Driving Car: an autonomous vehicle equipped with sensors, AI modules, and control systems to navigate and operate without human intervention. Self-driving cars can perceive their surroundings, make driving decisions, and safely transport passengers from one location to another.
Strong Artificial Intelligence: an AI that exhibits sentience consciousness and self-awareness.
Superalignment: the process in AI development wherein the goals, values, and decision-making principles of the AI system continuously align and adapt to closely match those of its human operators or the societal framework it interacts with. This iterative process aims to enhance the harmony and compatibility between AI objectives and human values over time.
Supervised Learning: an approach to machine learning in which labeled data is used to train a model, which learns to make predictions by generalizing this training data. Labeled data means input data is associated with corresponding target outputs.
Synthetic Biology (SynBio): an interdisciplinary field that combines principles of biology and engineering, often assisted by AI algorithms, to design and create artificial biological systems, such as genetically modified organisms, for various purposes, including medicine and biotechnology.
Technological Singularity: a hypothetical future point where AI is able to self-improve and gets into an exponential explosion of successive cycles of self-improvement, resulting in a Superintelligence that surpasses humans in all intellectual abilities. This potentially leads to profound and unpredictable changes in society and human existence.
Transhumanism: a philosophy and movement that advocates using technology to enhance and improve the human condition, potentially leading to the augmentation of human abilities and extending human life.
Uncanny Valley: a concept in robotics and human-computer interaction that suggests that as robots and avatars become more human-like in appearance and behavior, there is a point at which they elicit a sense of eeriness or discomfort in humans. This phenomenon occurs when the likeness to humans is almost perfect but not quite, causing an uncanny feeling.
Unsupervised Learning: an approach to Machine Learning in which unlabeled data is used to train a model. The model extracts general conclusions such as patterns, structures, or relationships within the data without specific guidance in the form of target labels.
Buy “Machines of Tomorrow” on Amazon
Author: Pedro Uria-Recio
Check us out at machinesoftomorrow.ai
us out at machinesoftomorrow.ai
