NEWS

Organizations are only scratching the surface when it comes to automation

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New report suggests organizations are missing a huge opportunity in automation by focusing on operational benefits over top-line growth.

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NEWS

Europe embraces emerging technologies

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By 2020, nearly 40 percent of European organisations plan to deploy artificial intelligence and blockchain-enabled technologies.

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NEWS

Cloud Technology Solutions eyes growing European market with Qlouder merger

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Cloud Technology Solutions (CTS) has merged with application development and machine learning specialist Qlouder in a deal that creates the largest dedicated Google Cloud practice in Europe.

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NEWS

Customer experience is now the top priority for quality assurance

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Capgemini's World Quality Report 2018 shows that customer experience is the top priority for quality assurance activities for the very first time, with automation and AI set to accelerate in the coming years.

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NEWS

AI and related technologies could create around 90 million more jobs in China

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Around 26% of existing jobs in China could be automated over the next 20 years, but this is projected to be more than offset by job creation of 38%, giving an estimated net gain of 12%.

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Organisations will need to overcome challenges to scale the technology.
Almost half of HR leaders say predictive analytics and machine learning would improve their HR...
Platform helps enterprises fully operationalize AI quickly and is key building block of Infor’s...
GigaSpaces' InsightEdge has been selected by Magic Software Enterprises to power their Magic xpi...
Collaboration speeds up critical functions such as image recognition and inferencing at the edge.
International Data Corporation (IDC)has publishd its worldwide information technology (IT) industry...
Latest Video

LinkedIn Automates All of the Easy Things, and Makes all of the Hard Things Easy

Hear LinkedIn’s senior SRE, Todd Palino, share how the company continually improves the state of its infrastructure, so that the developers who are rolling out applications have a framework that they can do it within, and they can do it safely. LinkedIn currently generates over 50 terabytes a day of unique metrics on applications. No human is going to look at 50 terabytes a day of data and get anything useful out of it, so LinkedIn relies on systems give them some useful signal out of all that noise. By moving down the road of machine learning, LinkedIn can now do anomaly detection using machine learning models.

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