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) …
A team of scientists has developed "robot flies" about the size of a quarter that can perch on almost any surface. The flies were developed at Harvard's Microbiotics Laboratory, where researchers look to Mother Nature for design inspiration. For years, they have been working on fly-sized drones that could be deployed in groups. The drones could, in theory, be outfitted with cameras and provide multiple vantage-points of a disaster, or link up to make an improvised communications network. They currently get power from wires attached to the ground, according to a paper in the journal Science.
SoftBank will still use its Naoqi operating system to control Pepper's hardware -- Android will only run on its chest-strapped tablet. The company isn't saying what sort of business deal it's struck, but Google typically takes a 30 percent cut from Android app revenues. We also don't know how much the robot will be able to take advantage of Android's features. The recently announced Google Assistant AI could actually be useful in a humanoid robot that can move on its own. SoftBank is still trying to figure out a purpose for Pepper, hence the need for more developer interest.
In other words, then, the company wants to be the platform that helps you throughout the entire cooking process -- starting from the food you have in your fridge, helping you to prepare it and then finally cooking it in a way that delivers perfect results every time. That's a tall order, especially considering all the variables involved, including the size and shape of different foods and the fact that not everyone knows how to cook. But thanks to some machine learning smarts and a variety of high-tech sensors, Innit believes its system is up to the task. It all starts with food storage. Using cameras and sensors, Innit is able to show you exactly what you have in your fridge, with the help of a companion app.
Flapping two tiny wings, the small, thin robot wobbles its way towards the underside of a leaf, bumps into the surface and latches on, perching motionless above the ground. Moments later, its wings begin to flap once more and it jiggles off on its way. The little flying machine, dubbed a "RoboBee", has been designed to perch on a host of different surfaces, opening up new possibilities for the use of drones in providing a bird's-eye view of the world, scientists say. Know as micro aerial vehicles, such robots could be invaluable in reconnaissance of disaster zones or to form impromptu communication networks. But there is a hitch: flying takes energy, so the time these robots can spend in the air is limited by the size of the battery pack they can carry.
The Exponential Organization Executive (ExO) of the future will not just be the CIO, CISO, or VP of IT. ExOs will be business leaders who understand how to take advantage of information in their businesses. They will understand Data (big data) both within and with their cloud providers. They will understand that IP intellectual property of this data can be exposed, developed, segmented, etc. by using APIs, Algorithms, Machine Learning, Deep Learning, and Artificial Intelligence. ExO Executives who "grock" this will apply significant advantage personally and to their businesses.
During today's Google I/O 2016 keynote, the company focuses on its efforts in machine learning and AI, to help improve efforts in robotics, medicine and more The machine learning segment was the last part of the keynote, which was presented by Google CEO Sundar Pichai. He stated that the company has open-sourced part of its machine learning platform, TensorFlow, as well as parts of its Cloud Platform APIs. This will allow for developers to access its computer vision APIs and specialized hardware. Google has also started building customized machine learning hardware, called Tensor Processing Units (TPUs). That hardware was used to power AlphaGo, a version of the classic game Go.
There have been plenty of announcements coming out of Google I/O this week, and yesterday, Google said that one of its projects that was created years ago is helping it accomplish its own custom accelerators for machine learning applications. The result of that project is called a Tensor Processing Unit (TPU), which is a custom ASIC that was built by Google just for machine learning. TPUs run inside Google data centers and have been for more than a year, according to a Google blog post by Norm Jouppi, a hardware engineer at Google. The company found that TPUs deliver better-optimized performance per watt for machine learning. The chip requires fewer transistors per operation, meaning Google can squeeze more operations per second into the silicon, according to Jouppi.