Artificial Intelligence (AI) and Machine Learning (ML) uses a system which is called an algorithm, which is essentially a set of actions to be followed in order to get to a solution. When it comes to ML, the algorithms involve taking data and performing calculations to find an answer. The complexity of these calculation varies on what task Is trying to be performed. When it comes to algorithms, it is useless if it takes longer to come to spit out an answer, after a human. It is also useless if the answers it provided are incorrect. The accuracy, efficiency and speed are all dependable on the training quality. Using algorithms does not essentially mean you are using AI/ML, however, if these two features were implemented into the algorithm all it would be doing is taking advantage of algorithms in general.
This means that a lot of people just assume that AI/ML are used whenever an algorithm exists, but this just not the case. When using an algorithm to predict an event, the outcome does not involve ML. In turn, when the outcome is to improve the future predictions, it does involve ML.
The term AI is a broadly used term. Essentially, it is a science of making the computer behave in such a way, it requires human intelligence. It is the study of training a computer to execute tasks, in the digital world it is applicable in the marketing and SEO efforts.
Machine learning is basically a branch from AI, again that is a study of computer algorithms that the main goal of it is to automatically compliment the outcomes of the algorithm at hand. AI and ML require huge sets of data to work with. This is because, it will recognise the patterns in the data by examining and comparing the sets of data to get to an outcome. A great example of this being used is if the algorithm is used with ML and was given instructions with a program to ask it to look at photos of pregnancy ultrasounds, together with a list of indications to look at, which can identify the gender. Therefore, these set of instructions that were implemented, will then be taught into the ML program and will be able to conduct this for future results.
Even though there are multiple differences between AI and ML, although they are closely connected. AI and ML are often viewed as the body and the brain when both implemented into the algorithm. The body collects information and the brain process it. Therefore, the body collects the information and the ML processes that information.