NEWS

Dataiku available in the Microsoft Azure Marketplace

Microsoft Azure customers worldwide now gain access to Dataiku, giving companies large and small an easy way to leverage the power of AI.

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NEWS

ThoughtSpot and Databricks partner

ThoughtSpot launches support for Databricks allowing users to run search and AI-driven analytics directly on the Databricks Lakehouse Platform, powered by Delta Lake.

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NEWS

Putting AI and ML in expert hands

Democratisation of Machine Learning makes operational experts more flexible to improve and predict process and asset performance.

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NEWS

Majority of organisations plan automation investment

New survey reveals that 48% accelerated automation projects as a result of the pandemic, with cost savings, customer satisfaction, and employee productivity as primary drivers.

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NEWS

Accelerating Machine Learning and hyperscale computing infrastructure

Switchtec PFX PCIe Gen 5 high performance switches double the data rate of PCIe Gen 4.0 solutions while delivering ultra-low latency and advanced diagnostics.

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Companies in the UK are lagging behind their global counterparts when it comes to artificial...
By 2020, nearly 40 percent of European organisations plan to deploy artificial intelligence and...
Databricks has introduced Model Registry, a new capability within MLflow, an open-source platform...
Mphasis has announced the availability of new Deep Learning algorithms on Amazon Web Services (AWS)...
Alfresco Software has unveiled the immediate availability of a new Intelligence Services for its...
Deep machine learning method can predict molecular wave functions and electronic properties of...
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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