The AI Universe

Australian Health Practitioner Regulation Agency (AHPRA)  guidelines on the use of AI in healthcare

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Health practitioners should familiarise themselves with the components of the AI universe.

Source:  Brij kishore Pandey

AI has fundamentally reshaped the IT world, driving innovation across industries and opening new frontiers in technology.

Let’s break down the key components:

1. Artificial Intelligence: The overarching field that’s revolutionizing everything from healthcare to finance.

  • Natural Language Processing: Powering chatbots like ChatGPT and language translation services like Google Translate.
  • Computer Vision: Enabling facial recognition in security systems and powering autonomous vehicles.
  • Expert Systems: Used in medical diagnosis and financial planning tools.
  • AI Ethics: Addressing crucial questions about bias, privacy, and the societal impact of AI.

2. Machine Learning: The engine driving AI’s rapid advancement.

  • Supervised Learning: Used in spam detection and credit scoring.
  • Unsupervised Learning: Powering recommendation systems on platforms like Netflix and Amazon.
  • Reinforcement Learning: Crucial for robotics and game-playing AI like AlphaGo.
  • Automated Reasoning: Employed in legal tech for contract analysis and in scientific research for hypothesis generation.

3. Neural Networks: These brain-inspired systems are at the heart of many AI breakthroughs. 

  • Convolutional Neural Networks (CNNs): Transforming image recognition, used in medical imaging for disease detection.
  • Recurrent Neural Networks (RNNs): Advancing language translation and speech recognition technologies.
  • Long Short-Term Memory (LSTM): Improving predictive text and stock market forecasting.

4. Deep Learning: This subset has led to remarkable advances in AI capabilities. 

  • Multi-Layer Perceptrons: Enhancing fraud detection in financial services.
  • Backpropagation: The key algorithm behind training complex neural networks, crucial for all deep learning applications.
  • Transfer Learning: Allowing models trained on one task to be quickly repurposed for another, accelerating AI development.

5. Generative AI: The cutting edge of AI, giving machines the ability to create. 

  • GPT Models: Revolutionizing text generation, used in content creation and coding assistance.
  • GANs (Generative Adversarial Networks): Producing photorealistic images, used in art creation and video game design.
  • Text-to-Image Models: Like DALL-E and Midjourney, creating images from textual descriptions.
  • Transformer Architecture: The backbone of modern language models, powering everything from chatbots to code completion tools.