AI Broadly Categorized

On a daily, I get asked ”Roine, what is AI, really?” And every time I’m a little stumped for words because I have, so far, not been able to really get myself to categorize the different areas. This means that I, of course, felt a little compelled to do some looking into this.

I mainly work with Generative AI, which is a combination of several of the areas listed and described in this post.

Artificial Intelligence can be broadly categorized into several main branches, each focusing on different aspects of intelligence and applications. The list below is broad, remember that. Here’s an overview of the main branches of AI:

1. Machine Learning (ML): This branch focuses on developing algorithms and statistical models that enable computers to perform specific tasks without using explicit instructions. Instead, they rely on patterns and inferences derived from data. Machine learning itself is divided into subcategories, such as supervised learning, unsupervised learning, and reinforcement learning.
2. Natural Language Processing (NLP): NLP involves the interaction between computers and humans using natural language. The goal is to enable computers to understand, interpret, and generate human language in a valuable way. It encompasses tasks like machine translation, sentiment analysis, and speech recognition.
3. Computer Vision: This branch enables machines to interpret and make decisions based on visual data. Computer vision tasks include image and video analysis, object detection, and facial recognition.
4. Robotics: Robotics combines AI with mechanical engineering, electrical engineering, and computer science to design, construct, operate, and use robots. AI in robotics allows robots to perform tasks autonomously or semi-autonomously, adapting to their environments.
5. Expert Systems: These are AI systems that use knowledge and inference procedures to solve problems that are difficult enough to require significant human expertise for their solutions. They mimic the decision-making ability of a human expert.
6. Speech Recognition: While sometimes considered a part of NLP, speech recognition can be seen as its own branch. It focuses on enabling machines to understand and interpret human speech, converting spoken words into text.
7. Planning and Scheduling: This branch focuses on systems that process a set of actions, determining a sequence of actions to achieve specific goals. This involves decision-making, resource allocation, and problem-solving.
8. Neural Networks and Deep Learning: Deep learning is a subset of machine learning that uses neural networks with many layers. It’s particularly powerful for tasks like image and speech recognition.
9. AI Ethics and Safety: As AI systems become more prevalent, there’s a growing branch focused on understanding and ensuring the ethical use of AI, addressing issues like bias, privacy, and the impact of AI decisions on society.

These branches are not mutually exclusive and often overlap. AI continues to evolve, and as it does, new branches or subfields may emerge, reflecting the dynamic nature of the field.