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Five examples where GPU databases are bringing ‘real-time’ to IoT analytics

By Michele Nemschoff | July 7, 2017

If your organization manages large volumes of streaming IoT data, you’ll no doubt be familiar with some of the challenges of getting value and insight from these high volume, moving datasets. Many companies have turned to Hadoop and other open source technologies to store and manage these IoT data feeds. This may typically involve “duct…

Kinetica Secures Series A Investment of $50 Million

By Amit Vij & Nima Negahban | June 29, 2017

Today we’re pleased to announce that Kinetica has closed a $50M Series A funding round. With the increased investment, we seek to further expand our solution capabilities while broadening the adoption of Kinetica – a next-generation database platform for analytics and AI accelerated by GPUs. Kinetica remains uniquely positioned to support global enterprises as they…

Bring Your Own Compute (BYOC) – How In-database Analytics on the GPU Unlocks the Potential of Machine Intelligence in Finance

By Karthik Lalithraj | June 21, 2017

Compute analytics in financial services have evolved over the past decade. Popular tools for forecasting and assessing risk like statistical functions involving linear regression, logistic regression have given way to more sophisticated models. Classic decision tree or regression tree algorithms have evolved to modern variations like random forest techniques and gradient boosted trees. Fraud detection…

TensorFlow bundled with Kinetica – Distributed deep learning now available to the enterprise

By Manan Goel | June 13, 2017

Today, we’re excited to announce that TensorFlow™ — the industry’s leading open-source library for machine intelligence — now comes bundled with Kinetica. This will make it easier for enterprises to take advantage of distributed deep-learning as part of a cohesive database solution. TensorFlow is rapidly becoming the go-to open-source library for machine intelligence and deep…

How Does a GPU Database Play in Your Machine Learning Stack?

By Ben Campbell | May 12, 2017

Machine learning (ML) has become one of the hottest areas in data, with computational systems now able to learn patterns in data and act on that information. The applications are wide-ranging: from autonomous robots, to image recognition, drug discovery, fraud detection, etc. At the cutting edge is deep learning, which draws its inspiration from the…

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