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) …
Deep learning can screen social media behaviour on Twitter, Facebook and additional news stories to connect data points and make predictions. To figure this out, in 2014 the NASA, the Universities Space Research Association and Google joint the Quantum Artificial Intelligence Lab. Eurekahedge, an independent data provider and alternative investment research firm that specialises in hedge fund databases, stated that their own Eurekahedge AI/Machine Learning Hedge Fund Index has outperformed both traditional quant and more generalized hedge funds since 2010. The Guardian: Google's DeepMind makes AI program that can learn like a human
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Driving this surge of machine-learning development is a wave of data generated by mobile phones, sensors, and video cameras. As a result, we expect machine learning will become the next great commodity. Released as a free, open-source operating system in 1991, it now powers nearly all the world's supercomputers, most of the servers behind the Internet, and the majority of financial trades worldwide – not to mention tens of millions of Android mobile phones and consumer devices. A director at Intel Capital, Sanjit Dang drives investments in user computing across the consumer and enterprise sectors.
Each TPU has four chips that delivers 180 trillion of floating points performance per second, if this was not enough Google combined 64 of these TPUs together using patented high speed network to create machine learning supercomputer called TPU pod. Remember, Google's real innovation has been on hardware patents in high end cloud computing, chips, servers, networking for its own data centers. Google has been unsuccessful in social media space, but is now using machine learning to help users share photos, even suggesting whom to share it with. Google has search data, complete email conversation data, photos, and location data.
There is an effort underway to standardize and improve access across all layers of the machine learning stack, including specialized chipsets, scalable computing platforms, software frameworks, tools and ML algorithms. "Just like cloud computing ushered in the current explosion in startup … machine learning platforms will likely power the next generation of consumer and business tools." This is where public cloud services such as Amazon Web Services (AWS), Google Cloud Platform, Microsoft Azure and others come in. Just like cloud computing ushered in the current explosion in startups, the ongoing build-out of machine learning platforms will likely power the next generation of consumer and business tools.
Until recently, big companies focused on adding AI capabilities to their own products -- think about your smartphone transcribing your voice and Facebook identifying the faces in your photos. Tests show that these chips can execute machine learning code up to 30 times faster than conventional computer chips. Amazon currently leads the cloud computing market with its Amazon Web Services, and it is offering developers a rival suite of machine learning tools. Because in their rush to win the cloud computing war, these technology giants are making more and more powerful AI capabilities available to anyone who wants to use them.
With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo @ThingsExpo, June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA. Join Cloud Expo / @ThingsExpo conference chair Roger Strukhoff (@IoT2040), June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA for three days of intense Enterprise Cloud and'Digital Transformation' discussion and focus, including Big Data's indispensable role in IoT, Smart Grids and (IIoT) Industrial Internet of Things, Wearables and Consumer IoT, as well as (new) Digital Transformation in Vertical Markets. Accordingly, attendees at the upcoming 20th Cloud Expo / @ThingsExpo June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA will find fresh new content in a new track called FinTech, which will incorporate machine learning, artificial intelligence, deep learning, and blockchain into one track. The upcoming 20th International @CloudExpo @ThingsExpo, June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA announces that its Call For Papers for speaking opportunities is open.
In other words, he hopes the new chip and the new service will set Google's cloud business apart from services offered by its main rivals, including Amazon and Microsoft, the unnamed competitive threat underlying his I/O keynote. Between its two AI labs--Google Brain, based at company headquarters in Silicon Valley, and DeepMind, a London AI startup Google purchased a little more than three years ago--Google is leading the new wave of artificial intelligence research and development so rapidly changing entire industries and economies. But the company believes cloud computing--where computing power is rented over the internet to businesses and software developers--could one day bring in far more. Google built its new chip as a better way of serving its own AI services, most notably Google Translate, says Jeff Dean, the uber-engineer who oversees Google Brain, the company's main AI lab.
Dubbed TPU 2.0 or the Cloud TPU, the new chip is a sequel to a custom-built processor that has helped drive Google's own AI services, including its image recognition and machine translation tools, for more than two years. Amazon and Microsoft offer GPU processing via their own cloud services, but they don't offer bespoke AI chips for both training and executing neural networks. Companies and developers undertake this training with help from GPUs, sometimes thousands of them, running inside the massive computer data centers that underpin the world's internet services. Training on traditional CPU processors--the generalist chips inside the computer servers that drive online software--just takes too much time and electrical power.
But recently it has become a more widely circulated buzzword, with virtually all recent technological advancements involving some aspect of machine learning. The remarkable growth in sophistication and applications of machine learning will define the technological trends of 2017. A recent advancement called sentiment analysis involves considering the impact of social media and news trends on commodities prices. The hedge fund trades entirely independent of human interaction and uses probabilistic logic to analyse and interpret the daily market data, news and social media, making predictions and deciding on the best course of action.