Artificial Intelligence and Deep Learning For the Extremely Confused

By STEPHEN BORSTELMANN, MD Artificial Intelligence is at peak buzzword: it elicits either the euphoria of a technological paradise with anthropomorphic robots to tidy up after us, or fears of hostile machines breaking the human spirit in a world without hope. Both are fiction. The Artificial Intelligences of our reality are those of Machine Learning and Deep Learning. Let’s make it simple: both are AI – but not the AI of fiction. Instead, these are limited intelligences capable of only the task they are created for: “weak” or “narrow” AI. Machine Learning is essentially applied Statistics, excellently explained in Hastie and Tibshirani’s Introduction to Statistical Learning. Machine Learning is a more mature field, with more practitioners, and a deeper body of evidence and experience. Deep Learning is a different animal – a hybrid of Computer Science and Statistics, using networks defined in computer code. Deep Learning isn’t entirely new – Yann LeCun’s 1998 LeNet network was used for optically recognizing 10% of US checks.   But the compute power necessary for other image recognition tasks would require an additional decade. Sensationalism by overly optimistic press releases co-exists with establishment inertia and claims of “black box” opacity. For the non-practitioner, it is very difficult to know what to believe, with confusion the rule. A game of chance Inspiration is found in an unlikely place – the carnival sideshow where one can fin...
Source: The Health Care Blog - Category: Consumer Health News Authors: Tags: Uncategorized Source Type: blogs