If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
In a market that is primarily dominated by four major companies – Google, Microsoft, Amazon, and IBM – AI could possibly disrupt the current dynamic. The current AI-cloud landscape can essentially be categorized into two groups: AI cloud services and cloud machine learning platforms. Example of AI cloud services involve technologies such as Microsoft Cognitive Services, Google Cloud Vision, and IBM Watson. Azure Machine Learning and AWS Machine Learning are examples of cloud machine learning platforms.
The company has been developing the technology for the past year and has been testing it on the streets of Pittsburgh. The National Highway Traffic Safety Administration is currently investigating that accident (see "Tesla Crash Will Shape the Future of Automated Cars"). RajunathanRajkumar, a professor at CMU who is collaborating with General Motors on automated vehicle technology, says the Pittsburgh experiment will raise public awareness about how driverless systems work. But Rajkumar cautions that both the Singapore and Pittsburgh trials may highlight the remaining challenges for automated vehicles.
While the world has been fixated on following the soap opera of financial markets, a more profound and ubiquitous development has been taking place worldwide - the rapid development in artificial intelligence and the fourth industrial revolution, which we think will mark an endless wave of disruptions. We believe artificial intelligence (AI) is almost ready for wider adoption by businesses, in turn providing opportunities, but also risks for investors. With corporate longevity already on the decline - according to McKinsey, one in five listed companies in the US may not last beyond the next five years - the integration of AI into business applications will have significant investment implications in the years to come. Similar to how companies with no core assets could become leaders in their industries today, AI companies have the potential to become tomorrow's industry leaders. As noted by Mr Tom Goodwin of the French media group Havas, who would have imagined just a few years back that the world's largest taxi firm (Uber) would own no vehicles, the world's largest accommodation provider (Airbnb) would operate no rooms, while the world's most valuable media company (Facebook) would create no content?
Deep learning is a somewhat new approach to machine learning and artificial intelligence that has caught fire over the past few years thanks to companies such as [company]Google[/company], [company]Facebook[/company], [company]Microsoft[/company] and Baidu, and a handful of prominent researchers (some of whom now work for those companies). The field draws a lot of comparisons to the workings of the human brain because deep learning systems use artificial neural network algorithms, although "inspired by the brain" might be a more accurate description than "modeled after the brain." Essentially, the stacks of neural networks that comprise deep learning models are very good at recognizing patterns and features of the data they're trained on, which has led to some huge advances in computer vision, speech recognition, text analysis, machine listening and even video-game playing in the past few years. You can learn more about the field at our Structure Data conference later this month, which includes deep learning and artificial intelligence experts from Facebook, Microsoft, Yahoo, Enlitic and other companies.