Kinetica in Motion
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 …Read More
Today, we’re excited to unveil Kinetica database v6.0.1, which bundles TensorFlow™, the industry’s leading open-source library for machine intelligence, to bring distributed deep learning to the enterprise.
TensorFlow is rapidly becoming the go-to open-source library for machine intelligence and …Read More
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 …Read More
This week, over 500 technologists – from enterprises such as BNY Mellon, Goldman Sachs, Google, ING, Target and many more – came together at Kafka Summit to learn and share tips in working with and getting value from high-speed data. …Read More
Forrester, as a guest of Kinetica, held a webinar this month about how digital business is driving rapid expansion and sophistication of data and insight, and why it’s necessary to augment traditional CPU-bound analytics with GPUs, in-memory processing, and machine …Read More
GPU-accelerated computing is one of the hottest trends among technology companies here in Silicon Valley. Companies including Google and Facebook are building out huge data centers leveraging parallel compute for machine learning, deep learning, and accelerated compute. Being able to …Read More