The Amazing Ways Tesla Is Using Artificial Intelligence And Big Data


Tesla has become a household name as a leader and pioneer in the electric vehicle market, but it also manufactures and sells advanced battery and solar panel technology. As a tech pioneer with a significant interest in the race to build and market autonomous vehicles, it makes sense that today they...

Machine learning and data are fueling a new kind of car, brought to you by Intel


The automobile is being dismantled, reimagined, and rebuilt in Silicon Valley. Intel's proposed $15.3 billion acquisition of Mobileye, an Israeli company that supplies carmakers with a computer-vision technology and advanced driver assistance systems, offers a chance to measure the scale of this rebuild. In particular, it shows how valuable on-the-road data is likely to be in the evolution of automated driving. While the price tag might seem steep, especially with so many players in automated driving today, Mobileye has some key technological strengths and strategic advantages. It's also developing new technologies that could help solidify this position.

No reason to fear the robot revolution - TechCentral


Basically, machine learning uses algorithms that iteratively learn from data, meaning that it enables computers to find hidden insights without being explicitly programmed where to look. However, where data mining extracts information for human comprehension, machine learning uses it to detect patterns in data and to adjust its program actions accordingly. Incredibly, it's a science that is not new; it is one that was, in fact, predicted nearly 70 years ago by Alan Turing, widely considered the father of theoretical computer science and artificial intelligence. For starters, it is applicable to healthcare, as machine learning algorithms can process more information and spot more patterns than humans can, by several orders of magnitude.

Using artificial intelligence to teach computers to see


Creating a self-driving car should not be difficult, but it's taking a while. Autonomous vehicles have been making headlines for years now, yet few of us have ever been in one or even seen one. We know that flying planes is more difficult than driving cars, yet pilots have enjoyed autopilot for decades. The answer is clear, or more precisely, clear vision. Pilots have used autopilot for decades in clear, open skies.

Machine learning is making self-driving cars smarter, but it can also make their workings more mysterious


Two recent accidents involving Tesla's Autopilot system may raise questions about how computer systems based on learning should be validated and investigated when something goes wrong. But machine learning techniques are increasingly used to train automotive systems, especially to recognize visual information. For example, a deep learning neural network can be trained to recognize dogs in photographs or video footage with remarkable accuracy provided it sees enough examples. A team at Princeton designed an automated driving system based largely on deep learning.

The First Person to Hack the iPhone Built a Self-Driving Car. In His Garage.


He drives through San Francisco's Potrero Hill neighborhood and then onto Interstate 280. The technology he's building represents an end run on much more expensive systems being designed by Google, Uber, the major automakers, and, if persistent rumors and numerous news reports are true, Apple. More short term, he thinks he can challenge Mobileye, the Israeli company that supplies Tesla Motors, BMW, Ford Motor, General Motors, and others with their current driver-assist technology. At 14, he was a finalist in the prestigious Intel International Science & Engineering Fair for building a robot that could scan a room and figure out its dimensions.