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) …
Fox News Flash top entertainment and celebrity headlines for Sept. 22 are here. Check out what's clicking today in entertainment. Aron Eisenberg, an actor whose most widely known role was "Nog" on the 1990s science-fiction adventure series "Star Trek: Deep Space Nine," died Saturday at age 50. Eisenberg's death was announced in a Facebook post by his wife, Malissa Longo. "It is with extreme regret and sadness to announce that my love and best friend, Aron Eisenberg, passed away earlier today," Longo wrote.
In this simple 4x3 grid-world, Q-learning agent learns by trial and error from interactions with the environment. Agent starts the episode in the bottom left corner of the maze. The goal of the agent is to maximize its total (future) reward. It does this by learning which action is optimal for each state. The action that is optimal for each state is the action that has the highest long-term reward.
This concept can best be understood with an example. Imagine the "simple" problem of trying to determine whether or not an image contains a cat. While this is rather easy for a human to figure out, it is much more difficult to train a computer to identify a cat in an image using classical methods. Considering the diverse possibilities of how a cat may look in a picture, writing code to account for every scenario is almost impossible. But using machine learning, and more specifically neural networks, the program can use a generalized approach to understanding the content in an image.
After filling out its wireless Formation lineup, Bowers & Wilkins is turning its attention back to headphones. The British manufacturer -- best known for its decadent home speakers -- unveiled four options today including a successor to the PX, its much-loved and most premium wireless headphones, and two sets of neckbuds focused on noise cancelling and high-end sound respectively. None of them are cheap (no surprise there), but the company hopes that its signature quality, combined with a new brand motto called "emotion, amplified," can expand its marketshare and pull customers away from competitors such as Bose, Sennheiser and Sony. But what exactly has changed? You won't find any touch controls on these headphones, or a voice assistant (yet) that can control your tunes and retrieve useful information.
If you're one of the 4.5 billion people connected to the internet today, you use a search engine to find, purchase, or learn about pretty much anything that comes to mind. Consumer search engines provide a seamless way for us to make sense of our complex world. And consumers are used to a search experience that is fast, accurate, and constantly improving. But when those same people try to search within their CRM at work, the experience is painfully underwhelming: too many clicks to find what you're looking for and an interface that confuses more than it helps. This shouldn't be the case today.
Before long, the rideshares we summon with our phones may come without drivers. Though that's not a ride many would accept just yet, a number of companies are nearing launch phase on driverless robotaxi vehicles. Alphabet subsidiary Waymo launched the first limited commercial robotaxi service last December in Phoenix, and existing ride-hailing services like Uber and Lyft have partnerships and pilot projects in development in various test cities (mostly those with great weather and little traffic). GM's self-driving subsidiary, Cruise, has postponed its 2019 launch plans but continues testing in San Francisco using the electric Chevy Bolt. And dozens of other robotaxi projects are in various phases of development, including an ambitious plan by Elon Musk to encourage Tesla owners to allow their idle electric vehicles to "gig away" when idle and join other company-owned vehicles in a robotaxi fleet.
Almost two years ago, Dennis Degray sent an unusual text message to his friend. "You are holding in your hand the very first text message ever sent from the neurons of one mind to the mobile device of another," he recalls it read. Degray, 66, has been paralysed from the collarbones down since an unlucky fall over a decade ago. He was able to send the message because in 2016 he had two tiny squares of silicon with protruding metal electrodes surgically implanted in his motor cortex, the part of the brain that controls movement. By imagining moving a joystick with his hand, he is able to move a cursor to select letters on a screen.
AI (artificial intelligence) will help improve many aspects of fleet management and maintenance, from reducing unplanned downtime to increasing efficiency throughout the maintenance and repair process and improving fuel economy. Machine learning and AI can provide fleet operators with critical data that can be used to optimize operations, as well as predictive analytics to enable better decisionmaking in the future based on the analysis of past fleet activities. Drivers too can benefit from IoT (Internet of Things)-enabled data. For instance, realtime data about what's going on outside on the roadways, such as weather conditions, road conditions, and traffic, can help fleet drivers get where they're going faster and with fewer hiccups along the way. Fleet managers can similarly use this data to track vehicles and make informed decisions about dispatching, eliminating much of the guesswork involved in fleet logistics.
The term Artificial Intelligence was coined in 1956, but AI has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage. In the 1960s, the US Department of Defense took interest in this type of work and began training computers to mimic basic human reasoning. For example, the Defense Advanced Research Projects Agency (DARPA) completed street mapping projects in the 1970s. And DARPA produced intelligent personal assistants in 2003, long before Siri, Alexa or Cortana were household names. This early work paved the way for the automation and formal reasoning that we see in computers today, including decision support systems and smart search systems that can be designed to complement and augment human abilities.
Imagine a world where killer robots, powered by artificial intelligence (AI), have the ability to decide who lives and who dies on the basis of deep learning and algorithms, without any human intervention. This scenario has been criticised by naysayers as alarmist. But experts, including United Nations Secretary-General Antonio Guterres and Tesla co-founder Elon Musk, have warned of the risk that AI can be put to nefarious use in the wrong hands. Please subscribe or log in to continue reading the full article.