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Go to:While artificial intelligence and machine learning give corporations the ability to act faster with fewer employees than ever before, companies take on a new kind of unprecedented risk, as well. AI and ML algorithms are only as good as the data they learn from. If they are trained to make decisions using a data set…
We’re very excited to announce the integration of Kinetica and RAPIDS! Customers have been using the Kinetica Active Analytics Platform to do large-scale data preparation, as well as model inferencing and audit (square & circle, below). With the integration with RAPIDS, we can now accelerate the whole end-to-end machine learning pipeline (including triangle, above). Companies…
The Internet of Things (IoT) is generating an ocean of raw data at the edge, driving the potential for massive industry change through data generation. Whether it be 5G network rollout, autonomous vehicles, smart vending machines, or the proliferation of sensor data such as smart meters, motion detectors, or infrastructure monitors, the opportunity for using…
As we reach a point where every business is responsible not just for what they produce or the services they provide, but also for the effectiveness of their data analysis, it’s essential to understand the active analytics process. Combining continuous analysis of streaming and historical data, location analysis, and predictive analytics using AI and machine…
5 strategies for leveraging edge computing for enterprise applications Every discussion of edge computing ought to start with a definition, because to date, just as with the early conversations about the cloud, there is no collective agreement on what, exactly, edge computing is. Some people think “the edge” is smartphones, some people think it’s raspberry…
In the press
