We do it to everything. When ChatGPT was launched to the public it basically woke the market up to the results of years of research. Now we’ve attached AI to everything as we tend to do. AI Editors, AI Pricing Estimators, AI Schedulers, AI designed fashion. I’m sure AI Cat food “specially crafted” by a machine is just around the corner. But there are in fact multiple different forms of the overall catch-all term of AI. Let’s briefly explore these to empower your understanding.
- Machine Learning (ML): AI systems that improve performance over time by learning from data. Some examples are recommendation systems or email filtering.
- Deep Learning: A subset of ML using neural networks to analyze factors like sound, time, and other layers of data. Examples include image classification or voice assistants
- Natural Language Processing (NLP): Focused on enabling machines to understand and respond to human language. These Large Language Models (LLM) versions of these are what is creating so much hype at the moment. E.g. ChatGPT, Chatbots, transcription services.
- Robotics: Machines capable of handling tasks in the real world, from simple repetitive jobs to complex activities.
- Computer Vision: Giving machines the ability to visually interpret the world, often used in facial recognition and image tagging.
- Expert Systems: Computers programmed to mimic the decision-making abilities of a human expert in specific domains, such as medical diagnosis.
- Speech Recognition: Systems trained to interpret and respond to voice commands, such things like Siri.
As you can see there are lot of different forms of AI. All of which can be used to make us more efficient or capable in our careers.