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Google, Microsoft, and Mozilla already support the performance-boostig technology in their browser engines
Rapidly advancing software frameworks, dedicated silicon, Spark integrations, and higher level APIs aim to put deep learning within reach
New capabilities include the GraphQL API, project boards, and API rate limiting
Effective machine learning and predictive analytics depend on vast amounts of relevant data and continuous learning
Other languages on the move include R, Hack, and Rust, while Python cements its position as the king of there dynamically typed languages
Microsoft’s Windows Server strategy is about to change, with faster updates, a lot of Linux love, and a devops focus
Graph-based machine learning is the next wave of digital disruption
The template method design pattern allows you to define the skeleton of an algorithm in a base class and defer the details to subclasses
If you’re confused about exactly what it means from an IT and business perspective, you’re not alone
Citing the need for cross-browser compatibility, Google chooses WebAssembly for running native code in Chrome