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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BLOG

Key Trends Framing the State of AI and ML

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

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NEWS

ADE plans divided between immediate investments and the future

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

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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Almost 5,000 knowledge workers and business decision makers share their insight on how RPA is...
Calligo launches 'world’s first' managed service to make machine learning accessible to any...
AI experts at CognitionX and Peltarion release new report on where the value in Deep Learning (DL)...
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...
Defining open standards is essential for deploying and governing machine learning models at scale...
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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