AI, Artificial Intelligence, Explained
In both business and consumer circles, the term AI, Artificial Intelligence, is used frequently, but oiften without understanding what it really means, or is.
AI, as it exists commercially today, uses a wide range of technologies and applications intended to mimic or augment human cognitive functions. Let us break down how AI is integrated into various commercial sectors:
Types of AI:
- Narrow or Weak
AI:
- This is the most common form of AI currently in use. It's designed to perform a narrow task (like searching the internet, analyzing text, playing chess, recommending movies, or voice recognition) very well but lacks the general intelligence of humans.
- Examples
include:
- Siri, Alexa, and Google Assistant for voice recognition and personal assistance.
- Recommendation Systems on platforms like Netflix, Spotify, or Amazon, which use AI to suggest content or products based on user behavior.
- Chatbots for customer service, which provide automated responses to common queries. Examples of these are OpenAI's ChatGPT, Microsoft Gemini and X/Twitter's Grok.
- Machine
Learning (ML):
- A subset of AI, ML involves algorithms that improve automatically through experience.
- Supervised Learning (e.g., predicting house prices from historical data) and Unsupervised Learning (e.g., clustering customers by buying behavior) are common techniques.
- Deep
Learning, a more advanced form of ML, uses neural networks with multiple layers (deep neural networks) and is
behind many breakthroughs, particularly in:
- Image and Speech Recognition (like facial recognition systems or voice-activated devices).
- Natural Language Processing (NLP), which includes language translation, sentiment analysis, and text generation.
- Artificial
Neural Networks (ANNs):
- Inspired by the human brain, these are used in deep learning to process complex data inputs like images or voice signals. This type of AI requires much more advanced processors as well as immense data storage capability.