numpy-ts 1.2.0: Achieving NumPy Parity in TypeScript with float16 Support and Bit-for-Bit RNG Matching

numpy-ts 1.2.0: Achieving NumPy Parity in TypeScript with float16 Support and Bit-for-Bit RNG Matching The Pain Point: NumPy in JavaScript Land If you've ever tried to port numerical Python code to TypeScript or Node.js, you've felt the pain. You're working with data science code that's been battle-tested in NumPy, but when you try to reproduce those same computations in JavaScript, you hit a wall of incompatibilities. The random number sequences don't match. Float16 operations silently fail or produce nonsensical results. You can't even trust that your RNG will produce identical outputs to Python, making reproducibility—one of the core tenets of scientific computing—impossible. I experienced this frustration firsthand while building numpy-ts, a TypeScript implementation of NumPy's core functionality. And I'm happy to say that with version 1.2.0, we've closed a major gap: bit-for-bit identical RNG sequences and full float16 support. But why does this matter so much? Let me explain. Und