AI Knowledge

A Generative Adversarial Network (GAN) is a type of AI framework made of two competing Neural Networks. One network (the Generator) creates new things like images or data, while the other (the Discriminator) tries to figure out if the generated things are real or fake. They get better by playing this game against each other.

AI-based Automation integrates artificial intelligence like machine learning and natural language processing—with traditional software automation. Unlike traditional rule-based scripts, it enables software to process unstructured data, adapt to changing inputs, and execute complex business tasks requiring human-like judgment.

A Chatbot is a computer program designed to have conversations with humans, often online through text messages or voice. It uses AI to understand what you say or type and then responds, often helping you find information, answer questions, or perform simple tasks automatically. Think of it as a digital talking assistant.

IoT or "Internet of Things" is a network of everyday objects – like smart devices, appliances, and sensors – that are connected to the internet. These objects can collect and share information, allowing them to "talk" to each other and often to AI systems to make our lives smarter and more automated.

Edge computing is a decentralized IT infrastructure that processes data and makes smart decisions near its source—like IoT devices, sensors, or local servers—rather than a remote cloud. By minimizing distance, it drastically reduces latency, conserves bandwidth, and enables real-time processing for critical applications.

Edge AI is like giving everyday devices – like your phone, smart camera, or even a robot – their own built-in "AI brain" so that is gets closer to the “eyers” and “ears” of the device and they can think and make faster and smarter decisions right there, without always needing to connect to the internet.

Reinforcement learning is a machine learning training method where an AI agent learns to make optimal decisions through trial and error. By taking actions in an environment, it receives rewards for positive outcomes and penalties for mistakes, continuously refining its strategy to maximize long-term success.

A prompt is a text instruction, question, or input provided to an AI model to guide its response. It acts as the primary starting point that directs the AI on what task to perform, what tone or format to adopt, and how to structure its output to generate accurate, relevant results.

Prompt engineering is the practice of designing, structuring, and refining text inputs to guide generative AI models toward producing accurate, relevant, and optimal outputs. While a prompt is simply the input given to an AI, prompt engineering is the systematic technique of crafting that input for high-quality results.

Explainable AI (XAI) is about making Artificial Intelligence (AI) decisions more transparent and understandable to humans, especially important in critical applications like healthcare and finance. It's the effort to show why an AI system came up with a particular answer, prediction, or decision, instead of it being a mystery "black box."