This approach is known as symbolic AI, and it was the dominant paradigm in AI from the 1950s to the late 1980s. For a fairly long time, many experts believed that human-level artificial intelligence could be achieved by having programmers handcraft a sufficiently large set of explicit rules for manipulating knowledge. Early chess programs, for instance, only involved hardcoded rules crafted by programmers, and didn’t qualify as machine learning. As such, AI is a general field that encompasses machine learning and deep learning, but that also includes many more approaches that don’t involve any learning. A concise definition of the field would be as follows: the effort to automate intellectual tasks normally performed by humans. Artificial intelligence was born in the 1950s, when a handful of pioneers from the nascent field of computer science started asking whether computers could be made to “think”-a question whose ramifications we’re still exploring today.
0 Comments
Leave a Reply. |