How AI helped build hreflang XML sitemaps at scale

Learn how iterative prompting, Python, and Google Colab helped turn a multilingual hreflang mapping project into a scalable workflow.

I've reviewed every PDF editor out there - then I had ChatGPT build me a better one

The smartest way to use AI may not be letting it interact with your files, but asking it to write software that handles them ...
IEEE

Pymoo: Multi-Objective Optimization in Python

Abstract: Python has become the programming language of choice for research and industry projects related to data science, machine learning, and deep learning. Since optimization is an inherent part ...
VentureBeat

Adaptive6 emerges from stealth to reduce enterprise cloud waste (and it's already optimizing Ticketmaster)

Credit: VentureBeat made with Nano Banana Pro via Fal.ai The generative AI era has sped everything up for most enterprises we talk to, especially development cycles (thanks to "vibe coding" and ...
GitHub

PyBADS: Bayesian Adaptive Direct Search in Python

PyBADS is a Python implementation of the Bayesian Adaptive Direct Search (BADS) algorithm for solving difficult and mildly expensive optimization problems, originally implemented in MATLAB. BADS has ...
GitHub

mlrose: Machine Learning, Randomized Optimization and SEarch

mlrose is a Python package for applying some of the most common randomized optimization and search algorithms to a range of different optimization problems, over both discrete- and continuous-valued ...
InfoWorld

Making Python faster won’t be easy, but it’ll be worth it

Python users have long addressed this problem by performing end runs around it. Want faster math? Use a math library like NumPy or Numba, or compile your code to C with Cython. These external ...