IDC4U: AI Powered T ...

AI algorithm

An AI algorithm refers to the specific programming that tells a machine how to function independently. It includes step-by-step instructions or rules that enable AI systems to process raw data, make decisions, and learn from it. Are you impressed by AI’s ability to understand language, recognize faces, play chess, or even drive a car? Well, the algorithm’s the brain!

AI Literacy

AI literacy refers to competencies that enable individuals to critically evaluate AI technologies, communicate and collaborate effectively with AI, and use AI in online, domestic, and workplace settings.

Artificial intelligence

The digital evolution of human intelligence is analogous to artificial intelligence. AI covers the field of computer science, including computer vision, that makes it possible for systems to think, learn, and carry out operations that normally call for human intelligence—but at a scale and speed that would make us mere mortals envious.

Automation

Automation implies using AI technology to run tedious work and business processes on autopilot—the focus is on task efficiency and reducing errors in manual work.

Big data

Big data includes large and complex datasets that are too substantial to be processed or analyzed using traditional data management tools. You need specialized AI technologies to uncover valuable insights, patterns, and trends from the data. In return, big data is used to train AI, so it’s a symbiotic relationship. 

ChatGPT

ChatGPT is an AI-powered conversational companion designed to engage in natural and informative conversations on various topics. It responds by answering questions, providing explanations, and offering insights. ChatGPT was trained using supervised learning and Reinforcement Learning from Human Feedback or RLHF, which makes it a versatile AI tool capable of human-like interactions.

Chatbot

A clever computer program that’s always up for a chat, ready to answer queries and lend a hand with specific tasks—that’s chatbot. It’s the unsung hero of customer support and information finding, as its main purpose is to engage with human language.

Deep learning

Deep learning is the brain behind the AI revolution. It’s a subset of the machine learning system that aims to mimic the human brain’s structure, using artificial neural networks with multiple layers to process vast amounts of data. Deep learning models can recognize patterns, make predictions, and learn complex tasks, revolutionizing fields like face and speech recognition and autonomous driving.

Ethical AI

Ethical AI is a branch encompassing issues related to the moral compass of AI. It involves designing and using AI systems in ways that prioritize fairness, transparency, accountability, and respect for human values and rights without causing harm or discrimination.

Generative AI

Generative AI or GenAI refers to AI models that craft fresh content—like photos or texts—reflecting styles and patterns derived from its training data. From imaginative art to informative articles, GenAI tools can produce a wide variety of output without code, which is why they serve as productivity sidekicks for many professionals.

GPT-3 and GPT-4

GPTs—or Generative Pre-trained Transformers—form an assortment of neural network-based language models developed by Open AI.

GPT-3 has been ranked among the most advanced models of its time. GPT-4 is an even more sophisticated and trained multimodal model than its predecessor. 

Large Language Model—LLM

A linguistic giant in the world of AI is a Large Language Model or LLM. It’s a powerful artificial intelligence system built on extensive data and sophisticated algorithms, enabling it to understand, generate, and manipulate human language with remarkable proficiency.

Machine learning

Machine learning involves training algorithms on data to recognize patterns and make decisions. As an algorithm is exposed to more data, its discerning process improves, making it more skilled at its intended tasks. It’s like teaching a computer to learn and adapt on its own.

Natural language generation—NLG

Natural language generation, or NLG systems, takes facts, figures, and data points and transforms them into coherent narratives, generating reports, articles, and content humans can easily understand. This technology powers automated reports and personalized responses to customers.

Natural language processing—NLP

Natural language processing, or NLP, is like a bridge between humans and machines, allowing computers to understand, interpret, and respond to human language. It uses advanced concepts like sentiment analysis to improve interpretations.

Neural network

The neural network is a computing system inspired by the human brain. It includes layers of interconnected nodes that work together to analyze and process data, facilitating deep learning and pattern recognition.

Open AI

Open AI is an American AI research company and the brainpower behind game changers like GPT-3 and GPT-4. It strives to offer responsible, ethical, and user-friendly products. It recently launched GPTs, an AI assistant that users can customize for various roles and intents.

Pre-training

Pre-training is the initial phase where AI models learn the basics of accomplishing a particular task, like learning the alphabet before diving into writing full sentences. The models are exposed to large datasets, helping them grasp languages and patterns. This sets the stage for fine-tuning, where they train to specialize in specific tasks.

Prompt

Prompt is the input or query the AI model uses to produce a meaningful and contextually relevant output. They can range from simple queries like Translate this sentence into French to more complex requests such as Write a short story about a detective solving a mystery. 🕵️

Using the right prompt is crucial to getting a useful response from AI. You have to phrase it suitably to make it work for the system’s processing style.

Reasoning

Reasoning in AI is the cognitive powerhouse driving artificial intelligence. An AI system’s reasoning can be based on logic, established rules and patterns, or common sense, but many models are also trained on abductive or monotonic reasoning.

Robotics

It’s a captivating blend of engineering, computer smarts, and AI that brings robots to life. These mechanical wonders can be anything from your helpful vacuum cleaner to futuristic human-like buddies. It is all about infusing machines with a sense of action, making them indispensable in fields like manufacturing, healthcare, and even exploring outer space. 

Strong AI

Often referred to as Artificial General Intelligence—AGI—or Deep AI, Strong AI represents the highest level of artificial intelligence. It possesses human-like intelligence and can understand, learn, reason, and apply knowledge across a wide range of tasks in a manner indistinguishable from humans. Strong AI is a broad concept—not a particular tool.

Unsupervised learning

Like a free-spirited explorer, unsupervised learning is a machine learning algorithm where the model doesn’t have a teacher/trainer providing clear answers. Instead, it sifts through data, finds patterns, and makes sense of it on its own. It’s used for tasks like clustering similar data or reducing the complexity of information.

Virtual reality—VR

With the help of AI, it transports you from your physical surroundings into a computer-generated world. With a VR headset, you can walk on Mars, fight dragons—or perhaps attend Taylor Swift’s Eras Tour someday—all without leaving your room.

Weak AI—Narrow AI

Weak AI, or Narrow AI, is the AI specialist in the room. It’s not your all-knowing generalist but a task-specific virtuoso. Picture it as a virtual expert, finely tuned to handle a particular job, whether it’s acing a chess game or spotting faces in photographs. While it’s brilliant within its specialized domain, it doesn’t step into the world of general human intelligence.

XAI—Explainable AI

Explainable AI is a special kind of artificial intelligence designed to show us the gears and cogs inside the AI’s decision-making process. With XAI, you don’t have to guess why AI makes certain choices—it tells you. This transparency is super important, especially in crucial areas like healthcare, finance, and self-driving cars, where we need to understand and trust the AI’s decisions.

From clickup.com。