NEWS

Automotive industry set to accelerate smart factories investment

Auto industry plans to make 44% of its factories smart in next five years – but companies must also invest in skills and systems to take full advantage.

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NEWS

Deep crisis for deep learning?

83% of AI decision-makers believe deep learning skills shortage is impacting their business’s ability to compete.

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NEWS

Call for machine learning open standards

Defining open standards is essential for deploying and governing machine learning models at scale for enterprise businesses.

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NEWS

Supercomputer aids machine learning

AI analytics leader enhances scale, develops new capabilities with new deployment.

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NEWS

Artificial Intelligence algorithm can learn the laws of quantum mechanics and speed up drug delivery

Deep machine learning method can predict molecular wave functions and electronic properties of molecules.

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NEWS

End-to-end ITSM and ITOM platform powered by AI/ML

Unified platform for ITSM and ITOM to discover, monitor, service, remediate, and optimize IT landscape, enriched with pervasive intelligence to turn unknowns to knowns, and deliver a consumer grade experience to the enterprise.

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Automation enables agility, increases speed, and drives top-line revenue while freeing up resources...
International Data Corporation (IDC)has publishd its worldwide information technology (IT) industry...
Cloud Technology Solutions (CTS) has merged with application development and machine learning...
CSPs across North America, Europe, Latin America, EMEA and APAC disclose plans for automation.
ThoughtSpot launches support for Databricks allowing users to run search and AI-driven analytics...
Around 26% of existing jobs in China could be automated over the next 20 years, but this is...
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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