NEWS

UK workers don't fear automation

Organisations will need to overcome challenges to scale the technology.

Read More

NEWS

SAS partners with NVIDIA on deep learning and computer vision

Collaboration speeds up critical functions such as image recognition and inferencing at the edge.

Read More

NEWS

Fewer than 50% of enterprises have deployed intelligent automation technology

86% of IT executives surveyed believe human work, AI systems, and robotic automation must be well-integrated by 2020 -- but only 12% said their companies do this really well today.

Read More

NEWS

Ziften expands its use of proprietary machine learning

Ziften’s endpoint protection platform uses proprietary machine learning in all phases of the endpoint security continuum simplifying endpoint protection across the enterprise.

Read More

NEWS

Harnessing the benefits of machine learning

Analytics Intelligence partners with Tealium to provide frontline business users with a simple and effective way to standardise, enrich, distribute, and activate customer data in real time.

Read More

NEWS

Global financial services industry bullish towards disruptive technology

Two thirds of financial services executives say disruptive technologies will have a positive impact on their business .

Read More

By 2020, nearly 40 percent of European organisations plan to deploy artificial intelligence and...
Research from Blue Yonder, a JDA Company, in collaboration with Microsoft finds vast majority of...
83% of AI decision-makers believe deep learning skills shortage is impacting their business’s...
Bonquiqui and Sheniqua to support staff in enhancing the service it offers to its insurance...
Calligo launches 'world’s first' managed service to make machine learning accessible to any...
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.

Read more