onsdag 10 januari 2018

The 10 most important breakthroughs in Artificial Intelligence

Switching to statistics

Though neural networks had existed as a concept for some time (see above!), it wasn’t until the late 1980s when there was a big shift amongst AI researchers from a “rules based” approach to one instead based on statistics - or machine learning. This means that rather than try to build systems that imitate intelligence by attempting to divine the rules by which humans operate, instead taking a trial-and-error approach and adjusting the probabilities based on feedback is a much better way to teach machines to think. This is a big deal - as it is this concept that underpins the amazing things that AI can do today.

Gil Press at Forbes argues that this switch was heralded in 1988, as IBM’s TJ Watson Research Center published a paper called “A statistical approach to language translation”, which is specifically talking about using machine learning to do exactly what Google Translate works today.

Read more....