NEWS

UK - bottom of the class for AI?

Companies in the UK are lagging behind their global counterparts when it comes to artificial intelligence (AI) and machine learning (ML) implementation, with just one in ten organisations (10%) able to boast mature capabilities – compared to one in six (17%) worldwide.

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NEWS

AI solving real-world problems and AI ethics among top trends for 2021

Data science, machine learning, and AI experts highlight the top AI and ML trends they expect to shape the data science industry in 2021.

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NEWS

MInd the learning gap

Rackspace Technology has published the results of a global survey that reveals that the majority of organizations globally lack the internal resources to support critical artificial intelligence (AI) and machine learning (ML) initiatives.

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NEWS

Alteryx partners with Snowflake

New innovations and integrated offering provide organizations Alteryx automated analytics and machine learning on Snowflake.

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NEWS

Machine learning via managed service

Calligo launches 'world’s first' managed service to make machine learning accessible to any business.

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NEWS

IEEE highlights importance of AI, ML, 5G and IoT

Chief information officers and chief technology officers surveyed on 2021 opportunities, challenges and key technology trends.

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By 2020, nearly 40 percent of European organisations plan to deploy artificial intelligence and...
Almost half of HR leaders say predictive analytics and machine learning would improve their HR...
Celonis has introduced the Celonis Intelligent Business Cloud. The Celonis Intelligent Business...
Analytics Intelligence partners with Tealium to provide frontline business users with a simple and...
Cloud Technology Solutions (CTS) has merged with application development and machine learning...
GigaSpaces' InsightEdge has been selected by Magic Software Enterprises to power their Magic xpi...
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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