Goto

Collaborating Authors

AI vs. Machine Learning vs. Deep Learning

#artificialintelligence

Since before the dawn of the computer age, scientists have been captivated by the idea of creating machines that could behave like humans. But only in the last decade has technology enabled some forms of artificial intelligence (AI) to become a reality. Interest in putting AI to work has skyrocketed, with burgeoning array of AI use cases. Many surveys have found upwards of 90 percent of enterprises are either already using AI in their operations today or plan to in the near future. Eager to capitalize on this trend, software vendors – both established AI companies and AI startups – have rushed to bring AI capabilities to market.


12 Artificial Intelligence Terms You Need to Know - InformationWeek

@machinelearnbot

Suddenly, artificial intelligence (AI) is everywhere. For decades, the dream of creating machines that can think and learn like humans seemed like it would be perpetually out of reach, but now artificial intelligence is embedded in the phones we carry everywhere, the websites we use every day and, in some cases, even in the appliances we use around our homes. The market researchers at IDC have predicted that companies will spend $12.5 billion on cognitive and AI systems in 2017, 59.3% more than they spent last year. And by 2020, total AI revenues could top $46 billion. In many cases, AI has crept into our lives and our work without us realizing it.


Artificial Intelligence vs. Machine Learning: What's the Difference?

#artificialintelligence

During the past few years, the terms artificial intelligence and machine learning have begun showing up frequently in technology news and websites. Often the two are used as synonyms, but many experts argue that they have subtle but real differences. And of course, the experts sometimes disagree among themselves about what those differences are. In general, however, two things seem clear: first, the term artificial intelligence (AI) is older than the term machine learning (ML), and second, most people consider machine learning to be a subset of artificial intelligence. One of the best graphic representations of this relationship comes from Nvidia's blog.


Artificial Intelligence vs. Machine Learning: What's the Difference? - Datamation

#artificialintelligence

During the past few years, the terms artificial intelligence and machine learning have begun showing up frequently in technology news and websites. Often the two are used as synonyms, but many experts argue that they have subtle but real differences. And of course, the experts sometimes disagree among themselves about what those differences are. In general, however, two things seem clear: first, the term artificial intelligence (AI) is older than the term machine learning (ML), and second, most people consider machine learning to be a subset of artificial intelligence. One of the best graphic representations of this relationship comes from Nvidia's blog.


Everything you need to know about narrow AI

#artificialintelligence

In 1956, a group of scientists led by John McCarthy, a young assistant-professor of mathematics, gathered at the Dartmouth College, NH, for an ambitious six-week project: Creating computers that could "use language, form abstractions, and concepts, solve kinds of problems now reserved for humans, and improve themselves." The project kickstarted the field that has become known as artificial intelligence (AI). At the time, the scientists thought that a "2-month, 10-man study of artificial intelligence" would solve the biggest part of the AI equation. "We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer," the first AI proposal read. We still don't have thinking machines that can think and solve problems like a human child, let alone an adult.