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Tackling our world's hardest problems with machine learning

You’ve probably heard artificial intelligence (AI) and machine learning described in a number of ways, so let’s take a step back and review their exact definitions:

Artificial intelligence (AI) is a way to describe any system that can replicate tasks that previously required human intelligence. Almost always, this is related to some kind of complex decision-making task where human judgment would normally be required. Most use cases for AI are looking for a probabilistic outcome—making predictions, classifications, or decisions with a high degree of certainty and in ways that are similar to human judgment.

Almost all AI systems today are created using machine learning. Machine learning uses large amounts of data to create and validate decision logic. This is known as a model. The AI system feeds input data into that model, and then the model outputs human-like predictions or classifications. Essentially, machine learning is the underlying technology that powers intelligent systems. 


 

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