Final answer:
Machine Learning (ML) is the subset of AI that uses statistical techniques for computers to 'learn' from data. ML relies on programs that can infer patterns and make predictions without explicit instructions, and the technology is used in a variety of applications from genetics to self-driving cars.
Step-by-step explanation:
The technology that is a subset of AI (Artificial Intelligence) and uses statistical techniques to enable computers to 'learn' from collected data is called Machine Learning (ML). In machine learning, algorithms are employed to analyze large sets of data, learn from this data, and make predictions or decisions without being explicitly programmed to perform the task. This approach is akin to data research or in silico research, where the exponential growth of data necessitates methods that can automatically adapt to and extract valuable insights from the information available.
ML is fundamentally based on inferential statistics, where a machine can infer patterns and make knowledge-based predictions. Various sectors utilize ML, from medical applications like analyzing DNA sequences for genetic research to sophisticated systems like self-driving cars. It's essential to understand that AI, especially ML, can be categorized into strong and weak AI, with the latter specializing in performing primarily one task.