this is not ragebait rule

I think we should avoid simplifying it to VLMs, LMs, Medical AI and AI for disabled people.

For instance, most automatic text capture ais (optical Character Recognition, or OCR) are powered by the same machine learning algorithms. Many of the finer-capability robot systems also utilize machine learning (Boston Dynamics utilizes machine learning for instance). There's also the ability to ID objects within footage, as well as spot faces and referencing it with a large database in order to find the person with said face.

All these are Machine Learning AI systems.

I think it would also be prudent to cease using the term 'AI' when what we actually are discussing is machine learning, which is a much finer subset. Simply saying 'AI' diminishes the term's actual broader meaning and removes the deeper nuance the conversation deserves.

Here are some terms to use instead

• Machine Learning = AI systems which increase their capability through automated iterative refinement.
• Evolutionary Learning = a type of machine learning where many instances of randomly changed AI models (called a 'generation') are run simultaneously, and the most effective is/are used as a baseline for the next 'generation'
• Neural Network = a type of machine learning system which utilizes very simple nodes called 'neurons' for processing. These are often used for image processing, LMs, and OCR.
• Convolution Neural Network (CNN) = a Neural network which has an architecture of neuron 'fliters' layered over each other for powerful data processing capabilities.

This is not exhaustive but hopefully will help in talking about this topic in a more definite and nuanced fashion. Here is also a document related the different types of neural networks