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Artificial Intelligence (AI)...

going beyond 'knowledge' ....


What's AI all About?

To start with, AI stands for 'Artificial Intelligence'; Simply refers to the development of computer systems that can perform tasks that typically require human intelligence. These tasks include learning, reasoning, problem-solving, perception, language understanding, and even interaction. The goal of AI is to create machines or software that can exhibit intelligent behavior and adapt to new situations without explicit programming.

In fact, AI is big! Really big! AI has applications everywhere, from healthcare, finance and education through to entertainment and quantum computing. It will revolutionize the way we live and work, but cause lots of pain and problems (like ethical and societal challenges, job displacement, privacy concerns, and biases). The ongoing development of AI involves a combination of technological advancements, ethical considerations, and regulatory frameworks to ensure responsible and beneficial use.

Not all AI is the same, we can broadly classify AI into types.

Types of AI

Narrow or Weak AI: This type of AI is designed and trained for a particular task. It excels in performing that specific task but lacks the broad spectrum of human cognitive abilities. Examples include virtual personal assistants like Siri or Alexa, image recognition software, and recommendation systems.
General or Strong AI: This type of AI is more advanced and possesses the ability to understand, learn, and apply knowledge across a wide range of tasks. It would have cognitive abilities similar to those of humans. Strong AI is still largely theoretical and does not yet exist.

Subfields of AI

Trustworthy AI: The field of Trustworthy AI can be divided into areas like generalization, security, fairness, explainability, transparency, privacy, and safety.
Data Mining and Machine Learning: A subset of AI that involves the development of algorithms and statistical models that enable computers to improve their performance on a specific task over time. It includes supervised learning, unsupervised learning, and reinforcement learning.
Responsible AI: Responsible AI is about designing, developing, and deploying AI with good intention to empower employees and businesses, and fairly impact customers and society.
Explainable AI: Important to explain why a particular decision has been taken; it therefore follows that we need to understand why an AI has taken those decisions, hence explainable AI.
Natural Language Processing (NLP): The branch of AI that deals with the interaction between computers and humans using natural language. It enables computers to understand, interpret, and generate human language.
Computer Vision: This field enables machines to interpret and make decisions based on visual data. It involves tasks such as image recognition, object detection, and facial recognition.
Robotics: Integrating AI with physical machines to enable them to perform tasks in the real world. This includes autonomous vehicles, industrial robots, and other automated systems.
Expert Systems: Computer systems designed to emulate the decision-making ability of a human expert in a particular domain.

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Pandora's Box Series

The Pandora's box series are a range of books on and around AI. The name was inspired by the Greek myth of Pandora - that AI could offers both untold riches that would push mankind into a new era 'or' it could be the destruction of mankind and open the door to unimaginable problems and pain.

deep learning specialization introduction to large language models introduction to image generation introduction to reponsible ai reinforcement learning fundementals

Other Upcoming AI Texts

A range of texts and resources on and around artificial intelligence.

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