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Tag: scaling

Dogged Determination: How Trupanion Pulled AI Across the Finish Line

Oct 14, 2019 |

David Jaw had reason to be excited. As a data scientist at Trupanion, Jaw had just put the finishing touches on the prototype of a machine learning model that could replicate the actions of a human claims adjuster with a high degree of accuracy. Read more…

Uber’s Training Tool Shares Ride for Deep Learning

Dec 13, 2018 |

A Linux Foundation project focused on AI development is expanding with the addition of a deep learning training tool based on an Uber-sponsored project.

Launch by the ride-sharing specialist, the Horovod project is a distributed training framework for Keras, PyTorch and TensorFlow. Read more…

AtScale Revs ‘Universal Layer’ to Keep Data ‘Big’

Oct 4, 2017 |

Keeping the “big” in big data is the mission of a four-year-old startup launched by Hadoop and business intelligence veterans with the aim of bridging the gap between users, their favorite tools and underlying Hadoop data platforms that are no longer scaling. Read more…

HP Diving Deeper into R Parallelization

Feb 20, 2013 |Despite R’s popularity as a statistical tool, its single-threaded nature might be a short-coming in scaling its use as a tool for big data applications. Not if they can help it, says HP. Read more…

Big Data – Scale Up or Scale Out or Both

Sep 17, 2012 |The “Big Data” term is generally used to describe datasets that are too large or complex to be analyzed with standard database management systems. When a dataset is considered to be a “Big Data” is a moving target, since the amount of data created each year grows, as do the tools (soft-ware) and hardware (speed and capacity) to make sense of the information. Many use the terms volume (amount of data), velocity (speed of data in and out) and variety of data to describe “Big Data”. Read more…
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