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AI (Artificial Intelligence) : What is AI?

AI (Artificial Intelligence) is being discussed everywhere, especially in the News and in classrooms. What is AI and how can people use it in a conscious fashion?

What is AI?

What is AI (Artificial Intelligence)?

AI has had many definitions over the years, but according to IBM the current accepted definition was written by John McCarthy from Stanford University. In his paper “What is Artificial Intelligence?”, he writes:

It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable. (2)

It is generally accepted that there are two types of AIs (Artificial Intelligence) in use, the names include Traditional/Weak/Narrow AI and Generative/Strong/Creative AI. Traditional AI “focuses on performing preset tasks using predetermined algorithms and rules”. A few examples of traditional AI include algorithms, translation, digital assistants, and opponents in video games. Generative AI is exciting because it can “create something new”. A few examples of Generative AI are ChatGPT, Bard, and DALL-E.

AI Vocabulary

Artificial Intelligence AI

"Technology that enables computers and machines to simulate human intelligence and problem-solving capabilities". - IBM

programing focused on cognitive skills such as learning, reasoning, self correction, and creativity. - TechTarget

Building an Artificial Intelligence:

Chatbot
- “A chatbot is a computer program that simulates human conversation with an end user. Not all chatbots are equipped with artificial intelligence (AI), but modern chatbots increasingly use conversational AI techniques such as natural language processing (NLP) to understand user questions and automate responses to them.” - IBM

Generative AI
- “Generative AI refers to deep-learning models that can generate high-quality text, images, and other content based on the data they were trained on.” - IBM
Machine Learning (ML)
- “Machine learning (ML) is a branch of artificial intelligence (AI) and computer science that focuses on the using data and algorithms to enable AI to imitate the way that humans learn, gradually improving its accuracy.” - IBM
Natural Language Processing (NLP)
- “Natural language processing, or NLP, combines computational linguistics—rule-based modeling of human language—with statistical and machine learning models to enable computers and digital devices to recognize, understand and generate text and speech.” - IBM

Large Language Model (LLM)
- “Large language models (LLMs) are a category of foundation models trained on immense amounts of data making them capable of understanding and generating natural language and other types of content to perform a wide range of tasks.” - IBM
Small Language Model (SLM)
- "A small language model applies the same methodology [as a LLM] but goes a step further to tackle domain-specific data and domain-specific use cases" Tech Target

Using Large Language Models

Understanding Large Language Models (LLMs)

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