Remove word

rajutkarsh07 · Jan 13, 2017 · e78124a · e78124a
1 parent 704601d
commit e78124a
Showing 1 changed file with 1 addition and 1 deletion.
diff --git a/FAQ.md b/FAQ.md
@@ -166,7 +166,7 @@ To better support numeric computing, standards bodies can do the following:
 
 1. Add support for [value types][typed-objects-explainer]. Value types allow for creating custom types and enabling compiler optimizations. As with [typed objects][typed-objects-proposal], complex numbers are a prime example where value types are valuable, due to value comparison via structural equivalence.
 
-1. Add support for [operator overloading][operator-overloading]. Assuming [typed objects][typed-objects-proposal] and [value types][typed-objects-explainer], a natural extension is [operator overloading][operator-overloading]. Currently, element-wise vector operations and use cases such as matrix multiplication require either verbose OOP semantics (e.g., `M1.mul( M2 )` ) or functional equivalents requiring internal argument validation (e.g., `mul( M1, M2 )`. Contrast JavaScript to languages such as MATLAB or Julia which allow for compact expressions (e.g., `M1 .* M2`). The ability to write compact, and yet expressive, code would significantly broaden the appeal of using JavaScript for numeric computing.
+1. Add support for [operator overloading][operator-overloading]. Assuming [typed objects][typed-objects-proposal] and [value types][typed-objects-explainer], a natural extension is [operator overloading][operator-overloading]. Currently, element-wise vector operations and use cases such as matrix multiplication require either verbose OOP semantics (e.g., `M1.mul( M2 )` ) or functional equivalents requiring internal argument validation (e.g., `mul( M1, M2 )`. Contrast JavaScript to languages such as MATLAB or Julia which allow for compact expressions (e.g., `M1 .* M2`). The ability to write compact, and yet expressive, code would significantly broaden the appeal of JavaScript for numeric computing.
 
 1. Add support for big [integers][julia-bigint], [rationals][golang-big], and [floats][julia-bigfloat]. In addition to cryptography and computing irrational numbers, arbitrary precision arithmetic is useful for algorithms involving double-precision floating-point numbers. Currently, lack of efficient, and relatively performant, big number support limits the scope and types of implemented algorithms, including for basic transcendental functions.