As with most recent developments in AI, the web erupted with outlandish storylines. Many described the move as bold despite the fact that (Torch), which is maintained by Ronan Collobert of Facebook AI Research, already offers categorically similar open-source deep learning tools and that Yoshua Bengio's lab has long maintained Theano, the revolutionary software package which pioneered the category in the first place, making deep learning easy for the masses. In an article at Wired, Cade Metz described TensorFlow as Google's "Artificial Intelligence Engine". Even this headline stands out as hyperbolic for an article describing an open-source library for performing linear algebra and taking derivatives. A number of other news outlets marveled that Google made the code open source.

The next, 17th ICAISC will take place in Zakopane in June 3-7, 2018, http://icaisc2018.icaisc.eu/

In my world of customer experience design, there is a lot of talk currently around Chat Bots and conversational user interface experience. Leading global powerhouses are currently directing energy and resources toward experimenting with specific Chat Bot experiences for different user groups. However, because they are effectively just an intelligent technical interaction, customers are not actually engaging with a real person. Whether customers prefer to talk to a robot or a human (and if they actually even notice), and how this affects the customer experience has been a debatable issue. Some companies and commentators are dead set against the idea -- they wholeheartedly believe that speaking with a robot is undesirable and the chat equivalent of talking to voice prompts on the phone (you know, the ones that inevitably end up repeating -- 'I'm sorry, I didn't get that.

A few weeks ago I attended a summit on artificial intelligence at New York University's Skirball Center for the Performing Arts. For a layman like me, some of the content was hard to follow, while some was easy to understand, specifically around the understanding and nuances of AI. The message was artificial intelligence, and machine learning is going to be awesome, but we are not there yet. The other main takeaway I got from the summit is that simplicity is the ultimate sophistication. Below, with my novice eyes, I will try to provide some essential insights and opinions on where we are with AI/ML and where it could be heading. The summit was fantastic especially for someone like me who is very interested in the space and how it will impact all of our lives.

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Google believes that the best way to improve artificial intelligence is new hardware technology. The search giant debuted a new microchip on Wednesday tailored for certain types of artificial intelligence projects that require crunching enormous amounts of data. Google CEO Sundar Pichai announced the new chip during the annual Google I/O conference for developers in Mountain View, Calif. The so-called Tensor Processing Unit, or TPU, is the latest version of a similar chip Google (goog) announced at last year's Google I/O event. Google does not plan to manufacture and sell the chip like Intel (intc) or AMD (amd), but instead will let companies rent access to the chip via Google's cloud computing service.

As the rise of massively distributed computing power, decreased cost of data storage, and a proliferation of open-source frameworks turn conventional computing paradigms on their head, new and lucrative opportunities are being created to develop innovative artificial intelligence applications, writes Ed Chater, COO, Adbrain. Research from Accenture suggests that AI technologies could double the economic growth rate in 12 developed countries and boost labor productivity up to 40% by 2035. The increasing importance of AI, signalled by strategic acquisitions by Google, Amazon, Apple, and Microsoft, has significant implications for businesses across all sectors and verticals. AI has the potential to transform industries as diverse as healthcare, finance, insurance, and entertainment. The term'artificial intelligence' doesn't refer to a single technology, but rather a group of technologies.

Security software designed to prevent bank fraud has been fooled by a BBC reporter and his twin. BBC Click reporter Dan Simmons set up an HSBC account and signed up to the bank's voice ID authentication service. HSBC says the system is secure because each person's voice is "unique". But the bank let Dan Simmons' non-identical twin, Joe, access the account via the telephone after he mimicked his brother's voice. HSBC introduced the voice-based security in 2016, saying it measured 100 different characteristics of the human voice to verify a user's identity.

Google just made a major move to expand its revenue beyond the realm of digital advertising. At the keynote address of this year's I/O developer conference, Google's CEO announced that the company will be selling AI computer chips, called Cloud Tensor Processing Units (TPUs), via Google Cloud service. Urs Hölzle, Google's veteran technical chief, told Bloomberg that the chip is "basically a supercomputer for machine learning. The field is rapidly evolving. For us, it's very important to advance machine learning for our own purposes and to be the best cloud." Machine learning is, in essence, a form of artificial intelligence that allows programs to change, adapt and (namely) learn from new data, without requiring additional programming effort and human intervention.

This is the Part II of my blog series that simply distils the key terminology of Big Data (see Part I here). These are the remaining 16 key concepts that you should understand if you want to learn more about Big Data. Structured data is data that can be arranged neatly into charts and tables consisting of rows, columns or multi-dimensioned matrixes. This is traditionally the way that computers have stored data, and information in this format can be easily and simply processed and mined for insights. Data gathered from machines is often a good example of structured data, where various data points--speed, temperature, rate of failure, RPM, etc.--can be neatly recorded and tabulated for analysis.