Paving The Way For Software 2.0 With Kotlin
Our work with differentiable programming, which enables programs to optimize themselves, is part of Facebook AI’s broader efforts to build more advanced tools for machine learning (ML) programming. That’s why we’re extending the Kotlin compiler to make differentiability a first-class feature of the Kotlin language, as well as developing a system for tensor typing. Our work enables developers to explore Software 2.0, where software essentially writes itself, via: Seamless differentiation through primitives, data structures, and control flow Tensor typing for static, compile-time shape inference and checking Compile-time errors for differentiable functions and tensor shapes A performant library providing a Tensor class…
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