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) …
Giving up control and selling the sales team represent some of the biggest challenges to implementing machine learning into email marketing. Or so say Jennifer Muse, Senior Director, Email Product Marketing, Lifescript Jon Weiss, Director, Email Marketing Operations, Sirius XM Radio Inc.to moderator Chris Marriott, Senior Vice President of Strategic Partnerships, CertainSource at last week's Email Insider Summit. For the complete video of this and other sessions from MediaPost's Email Insider Summit, go to the event agenda.
A 1969 McKinsey article claimed that computers were so dumb that they were not capable of making any decisions. In fact they said, it was human intelligence that drives the dumb machine. Alas, this claim has become a bit of a "joke" over the years, as the modern computers are gradually replacing skilled practitioners in fields across many industries such as architecture, medicine, geology, and education. Artificial Intelligence, Machine Learning, Data Science, and Deep Learning are pushing these changes in ways that are only just being understood. In the current scenario, many buzzwords are being employed in the evolving IT industry, especially in the various research areas around and within Data Science.
Machine learning technologies can learn from historical data, and make predictions or decisions, rather than following strictly static program instructions. They can dynamically adapt to a changing situation and enhance their own intelligence with by learning from new data. This approach has been successful in many applications and area. It also has potential in the network technology area. It can be used to intelligently learn the various environments of networks and react to dynamic situations better than a fixed algorithm.
To pitch its cloud storage business, Google is leaning on its artificial intelligence features. Amazon, the market leader, is too. Now Amazon has recruited a leading expert in the field to up its game. Alex Smola, a top machine learning scientist at Carnegie Mellon University (CMU) and research alum of Google and Yahoo, is moving over to run the "Cloud Machine Learning Platform" at AWS, he wrote in a post. Leaving CMU - Dear Friends, As some of you may have already heard, I'm leaving CMU to join Amazon.
Google announced in a blog post on Thursday that it has set up a new AI research group in Europe to focus on machine learning (ML). Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Google Research, Europe -- as the group is known -- is based out of Google's office in Zurich, Switzerland, which is home to Google's largest engineering office outside the US. Google said the group, which is expected to grow to over 100 people in the coming years, will focus on three key areas: machine intelligence, natural language processing and understanding, and machine perception. Companies like Amazon, Facebook, and Microsoft are all investing heavily in these areas as they look to make their platforms and services more intelligent.
FILE - In this Dec. 2, 2015 file photo, Germany's Kuka Robotics Co.'s robot LBR iiwa demonstrates a flower arrangement at the International Robot exhibition in Tokyo. Chinese appliance maker Midea has promised that German industrial robot maker Kuka will remain independent, as it seeks to allay fears about its takeover bid for the company. Midea's chairman said Thursday, June 16, 2016 that it doesn't intend to "dominate Kuka or delist the business" as it released more details about the share offer announced last month.
Many of us who want to get in shape would love to hire a personal trainer, but the cost is simply too high. Imagine your own virtual fitness coach inside your headphones cheering you on and pushing you forward when you exercise. After creating products for the Israeli air force and brands like Samsung and Under Armour, Israeli wearable tech company LifeBEAM is now making its own product – wireless, artificially intelligent headphones, or as many call them, "hearables," headphones that can learn about you as you workout. LifeBEAM's newest product Vi will tell you if you are running behind your usual pace on a familiar run and ask you politely if you want to speed it up. Or if your heart rate is getting too high, Vi will sense that and advise you to slow down.
As new technologies and creativity emerges, heralding the beginning of the fourth industrial revolution, what does this new era mean for the future of making things and our lives in a world of finite resources, and will progress be interpreted as a good or bad thing? Previous revolutions have had the most profound effect on'blue collar' workers. Now computers herald industrial revolution 4.0. What will be the impact on the'white collar' workers of today? This session explains what this new era means for the future of making things and our lives in a world of finite resources.
Now, researchers from Google DeepMind and Stanford University have updated a theory originally developed to explain how humans and other animals learn. "The evidence seems compelling that the brain has these two kinds of learning systems, and the complementary learning systems theory explains how they complement each other to provide a powerful solution to a key learning problem that faces the brain," explained James McClelland, lead author of the 1995 paper from Stanford University. Components of the neural network architecture that succeeded in achieving human-level performance in a variety of computer games like Space Invaders and Breakout were inspired by complementary learning systems theory. According to DeepMind co-founder Demis Hassabis, "the extended version of the complementary learning systems theory is likely to continue to provide a framework for future research not only in neuroscience but also in the quest to develop Artificial General Intelligence -- our goal at Google DeepMind."
Researchers including one of Indian-origin have provided a fresh insight into how human learning can foster smarter artificial intelligence (AI). Recent breakthroughs in creating artificial systems that outplay humans in a diverse array of challenging games have their roots in neural networks inspired by information processing in the brain. Now, researchers from Google DeepMind and Stanford University have updated a theory originally developed to explain how humans and other animals learn. First published in 1995, the theory states that learning is the product of two complementary learning systems in the brain. The first system gradually acquires knowledge and skills from exposure to experiences, and the second stores specific experiences so that these can be replayed to allow their effective integration into the first system.