NEWS

Spherica launches Synaptek, a new Intelligent Automation division

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Synaptek is a new Digital Innovation Division dedicated to enabling better ways of working through intelligent automation.

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NEWS

Mphasis launches AI solutions on the AWS Marketplace

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Mphasis has announced the availability of new Deep Learning algorithms on Amazon Web Services (AWS) Marketplace for Machine Learning. The on-demand solutions target practical enterprise use cases such as influence analytics, insurance claims analysis, payment card fraud, and image analytics for supply chain and logistics.

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NEWS

HEMA selects JDA

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Leading European retailer selects JDA for a supply chain transformation fueled by Blue Yonder-enabled AI/ML technologies.

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NEWS

Cortex Labs launches decentralized AI and Machine Learning network

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The first globally decentralized deep learning and AI network has been launched.

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NEWS

University of Oxford spin-out Mind Foundry launches machine learning platform

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Platform makes machine learning simple to deploy and augments knowledge and skillsets of business problem owners.

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NEWS

Machine learning will enhance our profession, say HR leaders

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Almost half of HR leaders say predictive analytics and machine learning would improve their HR function, according to a Censuswide survey commissioned by MHR Analytics.

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Platform makes machine learning simple to deploy and augments knowledge and skillsets of business...
Calligo launches 'world’s first' managed service to make machine learning accessible to any...
Ziften’s endpoint protection platform uses proprietary machine learning in all phases of the...
Acquisition takes first step in building GitLab’s Applied Machine Learning for DevOps .
Data science, machine learning, and AI experts highlight the top AI and ML trends they expect to...
Democratisation of Machine Learning makes operational experts more flexible to improve and predict...
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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