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Apple's Core ML frameworks provide a standardized -- if limited -- way to embed machine learning into Mac and iOS apps
Serverless architecture and function-as-a-service platforms open a whole new world of simplicity, speed, and flexibility for developers
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