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Red Hat: ‘Hybrid Cloud’, University of Alabama, Red Hat Upgrades Ansible and Expectations

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More on Red Hat today

  • Red Hat Inc. Reveals 37% Increase In Q2 Profit
  • [Reposted] Red Hat Announces Broad Expansion to Open Source Patent Promise
  • Red Hat expands their patent promise

    Red Hat, Inc. has announced a significant revision of its Patent Promise. That promise, originating in 2002, was based on their intention not to enforce its patents against free and open source software. The new version significantly expands and extends Red Hat’s promise, helping to protect open innovation.

    In its original Patent Promise, Red Hat explained that its patent portfolio was intended to discourage patent aggression against free and open source software. The expanded version published today reaffirms this intention and extends the zone of non-enforcement. It applies to all of Red Hat’s patents, and all software licensed under well-recognized open source licenses.

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Cloudgizer: An introduction to a new open source web development tool

Cloudgizer is a free open source tool for building web applications. It combines the ease of scripting languages with the performance of C, helping manage the development effort and run-time resources for cloud applications. Cloudgizer works on Red Hat/CentOS Linux with the Apache web server and MariaDB database. It is licensed under Apache License version 2. Read more

James Bottomley on Linux, Containers, and the Leading Edge

It’s no secret that Linux is basically the operating system of containers, and containers are the future of the cloud, says James Bottomley, Distinguished Engineer at IBM Research and Linux kernel developer. Bottomley, who can often be seen at open source events in his signature bow tie, is focused these days on security systems like the Trusted Platform Module and the fundamentals of container technology. Read more

TransmogrifAI From Salesforce

  • Salesforce plans to open-source the technology behind its Einstein machine-learning services
    Salesforce is open-sourcing the method it has developed for using machine-learning techniques at scale — without mixing valuable customer data — in hopes other companies struggling with data science problems can benefit from its work. The company plans to announce Thursday that TransmogrifAI, which is a key part of the Einstein machine-learning services that it believes are the future of its flagship Sales Cloud and related services, will be available for anyone to use in their software-as-a-service applications. Consisting of less than 10 lines of code written on top of the widely used Apache Spark open-source project, it is the result of years of work on training machine-learning models to predict customer behavior without dumping all of that data into a common training ground, said Shubha Nabar, senior director of data science for Salesforce Einstein.
  • Salesforce open-sources TransmogrifAI, the machine learning library that powers Einstein
    Machine learning models — artificial intelligence (AI) that identifies relationships among hundreds, thousands, or even millions of data points — are rarely easy to architect. Data scientists spend weeks and months not only preprocessing the data on which the models are to be trained, but extracting useful features (i.e., the data types) from that data, narrowing down algorithms, and ultimately building (or attempting to build) a system that performs well not just within the confines of a lab, but in the real world.