Читать книгу Informatics and Machine Learning. From Martingales to Metaheuristics онлайн

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The Nanoscope example can also be considered as a case study for device “smartening,” whereby device state is tracked in terms of easily measured device characteristics, such as the ambient device “noise.” A familiar example of this would be the sound of your car engine. In essence, you could eventually have an artificial intelligence (AI) listening to the sound of your engine to similarly track state and issue warnings like an expert mechanic with that car, without the need for sensors, or to supplement sensors (reducing expense, providing secondary fail‐safe). Such an AI might even offer predictive fault detection.

ML provides a solution to the “Big Data” problem, whereby a vast amount of data is distilled down to its information essence. The ML solution sought is usually required to perform some task on the raw data, such as classification (of images) or translation of text from one language to another. In doing so, ML solutions are strongly favored where a clear elucidation of the features used in the classification are also revealed. This then allows a more standard engineering design cycle to be accessed, where the stronger features thereby identified may play a stronger role, or guide the refinement of related strong features, to arrive at an improved classifier. This is what is accomplished with the previously mentioned SSA Protocol.