NEWS

Machine learning via managed service

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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

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

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BLOG

Key Trends Framing the State of AI and ML

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By Rachel Roumeliotis, VP of Data and AI at O’Reilly.

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NEWS

What happens next?

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International Data Corporation (IDC)has publishd its worldwide information technology (IT) industry predictions for 2021 and beyond.

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NEWS

ADE plans divided between immediate investments and the future

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Respondents around the world highlight the immediate need for data to drive decision-making for greater efficiency, while future plans are focused on investments for agility.

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NEWS

AI and ML tools target advanced threats

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Micro Focus has published the 2020 State of Security Operations report, which reveals that security operations centres (SOCs) across the globe are most concerned with advanced threat detection and are increasingly looking to artificial intelligence (AI) and machine learning (ML) technologies to proactively safeguard the enterprise.

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Data Science Platform boosts infrastructure behind NetApp’s Active IQ solution, responding in...
Almost 5,000 knowledge workers and business decision makers share their insight on how RPA is...
86% of IT executives surveyed believe human work, AI systems, and robotic automation must be...
Announces first commercial availability of key technologies from Project Debater.
Amadeus Ventures will invest in the travel tech startup which uses machine learning to help...
Calligo launches 'world’s first' managed service to make machine learning accessible to any...
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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