Artificial intelligence

Artificial intelligence (AI) refers to machine actions that are perceived by humans as intelligent. Machine learning is a subset of AI where the "intelligence" is not programmed in but learned from data by a machine learning model. In current mainstream usage, these terms are nearly synonymous, but AI in general is a very vast field of different approaches, most of which are quite obscure to non-experts.

Dumb and smart programs

Humans instinctively relate to machines and tools either as body extensions or as autonomous creatures. It is generally not a good idea to require a user to use both approaches simultaneously. "Smartness" is not wanted in applications that are supposed to be wielded as tools or instruments, if it makes them more complex and less predictable. If there are "smart" functions in a tool, they should be clearly separate from the "wielded" portion, with the option of disabling them completely.

Among the most important software, ?compilers are programs that are generally supposed to be rather smart in order to produce efficient code for the target platform. It is also where a large amount of resource use can often be justified by the energy that is saved by the efficiency of the produced code.

Green AI

The research, training and deployment of very large machine learning models takes a radically increasing amount of energy and dedicated hardware in today's world. This is why "Green AI" has become a thing.

The tinyML foundation is concerned about small machine learning models that run on very low power when trained (but may still require a lot of resources to train).

(Please include interesting information/resources about low-power AI/ML, if you have studied this topic)