Читать книгу The Innovation Ultimatum - Steve Brown - Страница 25

Artificial intelligence and traditional digital computers are complementary. Importantly, AI solves problems that are costly or impossible for traditional computers to solve. The two technologies will coexist and work side-by-side, each solving a different set of problems. For a language translation app on a smartphone, traditional computing presents an attractive interface, while AI handles voice recognition and language translation functions.

AI solves problems using a radically different approach from traditional computers. Traditional computers are programmed to solve problems. Programs apply a set of rules to data and compute results. Said another way, they take rules and data as input, and output results. AI solves problems without using preprogrammed rules. Machine learning, a popular form of AI, takes data and results as its input and infers rules as its output. Through a complex training process, AI finds patterns and associations between data and results and divines its own rules for how they connect. This trait lets us solve entirely new problems with AI. It's why AI can seem so magical: It solves problems we don't know how to solve ourselves.

To find complex associations in data and build rules, AIs must be trained with thousands or sometimes millions of examples. Today's AIs are not like human brains. While some of the organizing principles are the same, human children learning about the world don't have to see a million automobiles before they can recognize one and adorably yell the word “car.”