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Oracle Yields GraphPipe

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OSS
  • Oracle open sources Graphpipe to standardize machine learning model deployment

    Oracle, a company not exactly known for having the best relationship with the open source community, is releasing a new open source tool today called Graphpipe, which is designed to simplify and standardize the deployment of machine learning models.

    The tool consists of a set of libraries and tools for following the standard.

  • Oracle open-sources Graphpipe to make it easier to deploy machine learning models

    Oracle today open-sourced Graphpipe, a tool created to make it easy to serve machine learning models in the cloud made by popular frameworks like TensorFlow, MXNet, Caffe2, and PyTorch. Graphpipe was designed to simplify the deployment of machine learning for use on mobile apps and IoT devices, as well as web services for end users or AI for internal use at companies.

    “Graphpipe is an attempt to standardize the protocol by which you speak to a remotely deployed machine learning model, and it includes some reference servers that allow you to deploy machine learning models from existing frameworks very easily in an efficient way,” Oracle cloud architect Vish Abrams told VentureBeat in a phone interview. Prior to joining Oracle, Abrams led efforts at NASA to open-source the OpenStack cloud computing platform.

  • Oracle open sources GraphPipe, a new standard for machine learning models

    Machine learning is expected to transform industries. However, its adoption in the enterprise has been slower than some might expect because it's difficult for organizations to deploy and manage machine learning technology on their own. Part of the challenge is that machine learning models are often trained and deployed using bespoke techniques, making it difficult to deploy models across servers or within different departments.

  • Oracle offers GraphPipe spec for machine learning data transmission

    Oracle has developed an open source specification for transmitting tensor data, which the company wants to become a standard for machine learning.

    Called GraphPipe, the specification provides a protocol for network data transmission. GraphPipe is intended to bring the efficiency of a binary, memory-mapped format while being simple and light on dependencies. There also are clients and servers for deploying and querying machine learning models from any framework.

  • Oracle releases GraphPipe, an open-source tool for deploying AI models

    Major tech firms regularly open-source internal software projects, but it’s not often that Oracle Corp.’s name comes up in this context. Today marked one of those occasions.

    The database giant this morning released GraphPipe, a tool for easing the deployment of machine learning models. Development on the project was led by Oracle cloud architect Vish Abrams, an open-source veteran who previously worked at NASA as part of the team that created the OpenStack data center operating system.

  • Oracle Open Sources GraphPipe for 'Dead Simple' Machine Learning Deployment

Belated Coverage

  • Oracle puts GraphPipe into open source to standardize and deploy machine learning

    Oracle released a new tool, which is called GraphPipe, into open source in order to speed up real-world deployments of machine learning.

    GraphPipe, which Oracle has put into open source via GitHub, was designed to standardize and clarify machine learning models in order to scale out services and applications to customers.

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