Goto

Collaborating Authors

Understanding the differences between AI, machine learning, and deep learning - TechRepublic

#artificialintelligence

With huge strides in AI--from advances in the driverless vehicle realm, to mastering games such as poker and Go, to automating customer service interactions--this advanced technology is poised to revolutionize businesses. But the terms AI, machine learning, and deep learning are often used haphazardly and interchangeably, when there are key differences between each type of technology. Here's a guide to the differences between these three tools to help you master machine intelligence. SEE: Inside Amazon's clickworker platform: How half a million people are being paid pennies to train AI (PDF download) (TechRepublic) AI is the broadest way to think about advanced, computer intelligence. In 1956 at the Dartmouth Artificial Intelligence Conference, the technology was described as such: "Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it."


Artificial intelligence: The 3 big trends to watch in 2017 - TechRepublic

#artificialintelligence

In 2016, the White House recognized the importance of AI at its Frontiers Conference. The concept of driverless cars became a reality, with Uber's self-driving fleet in Pittsburgh and Tesla's new models equipped with the hardware for full autonomy. Google's DeepMind platform, AlphaGo, beat the world champion of the game--10 years ahead of predictions. "Increasing use of machine learning and knowledge-based modeling methods" are major trends to watch in 2017, said Marie desJardins, associate dean and professor of computer science at the University of Maryland, Baltimore County. How will this play out?


Artificial intelligence: The 3 big trends to watch in 2017 - TechRepublic

#artificialintelligence

In 2016, the White House recognized the importance of AI at its Frontiers Conference. The concept of driverless cars became a reality, with Uber's self-driving fleet in Pittsburgh and Tesla's new models equipped with the hardware for full autonomy. Google's DeepMind platform, AlphaGo, beat the world champion of the game--10 years ahead of predictions. "Increasing use of machine learning and knowledge-based modeling methods" are major trends to watch in 2017, said Marie desJardins, associate dean and professor of computer science at the University of Maryland, Baltimore County. How will this play out?


Understanding the differences between AI, machine learning, and deep learning - TechRepublic

#artificialintelligence

With huge strides in AI--from advances in the driverless vehicle realm, to mastering games such as poker and Go, to automating customer service interactions--this advanced technology is poised to revolutionize businesses. But the terms AI, machine learning, and deep learning are often used haphazardly and interchangeably, when there are key differences between each type of technology. Here's a guide to the differences between these three tools to help you master machine intelligence. SEE: Inside Amazon's clickworker platform: How half a million people are being paid pennies to train AI (PDF download) (TechRepublic) AI is the broadest way to think about advanced, computer intelligence. In 1956 at the Dartmouth Artificial Intelligence Conference, the technology was described as such: "Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it."


How Tesla Autopilot drove a man with a blood clot to the hospital, and expanded the autonomous car debate - TechRepublic

#artificialintelligence

When Joshua Neally left his office in Springfield, MO, climbed into his Tesla Model X, and merged onto the highway to head home, he did what many Tesla drivers do--he switched on Autopilot mode. Neally, who reportedly pays close attention while driving Autopilot, following Tesla's guidelines for use, may have expected the advanced driving feature to kick in, braking if a vehicle crossed its path or alerting him if a nearby car slid too close into his lane. But, when Neally began experiencing tightness in his chest and, after calling his wife, realized he needed to get to the hospital, he used Autopilot in a way he probably never expected: To rush him straight to the hospital. SEE: Tesla's Autopilot: The smart person's guide (TechRepublic) The tightness in his chest turned out to be caused by a pulmonary embolism, and Neally was able to make a full recovery. "I don't really think I could have [made the drive without Autopilot]," Neally told CBS.