Tag: TensorFlow

Presto Use Surges, Qubole Finds

Apr 18, 2018 |

Don’t look now, but Presto, the SQL engine developed by Facebook as a follow-on to Hive, is starting to catch on in a big way. According to a new survey of big data-as-a-service customers by Qubole, Presto logged impressive usage gains during 2017, and outgrew Hive and Spark across many metrics. Read more…

ParallelM Aims to Close the Gap in ML Operationalization

Feb 21, 2018 |

A startup named ParallelM today unveiled new software aimed at alleviating data scientists from the burden of manually deploying, monitoring, and managing machine learning pipelines in production.

Dubbed MLOps, ParallelM‘s software helps to automate many of the operational tasks required to turn a machine learning model from a promising piece of code running nn Spark, Flink, TensorFlow, or PyTorch processing engines into a secure, governed, and production-ready machine learning system. Read more…

Snowflake Taps Qubole for Deep Machine Learning in the Cloud

Feb 13, 2018 |

Organizations storing big data in Snowflake’s cloud data warehouse can now run machine learning and deep learning algorithms against that data thanks to a new partnership with Qubole.

The two companies today announced a partnership that will allow Qubole’s big data processing engines, including Apache Spark and TensorFlow, to read and write data to Snowflake’s data warehouse. Read more…

How to Make Deep Learning Easy

Nov 9, 2017 |

Deep learning has emerged as a cutting-edge tool for training computers to automatically perform activities like identifying stop signs, detecting a person’s emotional state, and spotting fraud. However, the level of technological complexity inherent in deep learning is quite daunting. Read more…

TensorFlow to Hadoop By Way of Datameer

Jun 28, 2017 |

Companies that want to use TensorFlow to execute deep learning models on big data stored in Hadoop may want to check out the new SmartAI offering unveiled by Datameer today. Read more…

Spark’s New Deep Learning Tricks

Jun 7, 2017 |

Imagine being able to use your Apache Spark skills to build and execute deep learning workflows to analyze images or otherwise crunch vast reams of unstructured data. That’s the gist behind Deep Learning Pipelines, a new open source package unveiled yesterday by Databricks. Read more…

Nvidia’s Huang Sees AI ‘Cambrian Explosion’

May 24, 2017 |

The processing power and cloud access to developer tools used to train machine-learning models are making artificial intelligence ubiquitous across computing platforms and data framework, insists Nvidia CEO Jensen Huang. Read more…

Big Data’s Relentless Pace Exposes Old Tensions and New Risks in the Enterprise

Mar 22, 2017 |

Over the past two weeks, we’ve explored some of the difficulties that enterprises have experienced in trying to adopt the Hadoop stack of big data technologies. One area that demands further attention is how the rapid pace of development of open source data science technology in general, and the new business opportunities it unlocks, is simultaneously exposing old fault lines between business and IT while opening them to new risks. Read more…

Kinetica Aims to Broaden Appeal of GPU Computing

Jan 24, 2017 |

Kinetica today unveiled a new iteration of its in-memory, GPU-accelerated database that it says will help to democratize data science and traditional business intelligence by simultaneously running SQL-based queries and machine learning/deep learning workloads on the same data. Read more…

Spark ML Runs 10x Faster on GPUs, Databricks Says

Oct 27, 2016 |

Apache Spark machine learning workloads can run up to 10x faster by moving them to a deep learning paradigm on GPUs, according to Databricks, which today announced that its hosted Spark service on Amazon’s new GPU cloud. Read more…