The Age of Machine Learning As Code Has Arrived

honestly? ML as code isn't some magic bullet; it's just better plumbing for messy repos. we're spending time setting up pipelines instead of actually building novel models. it smooths out the integration headache, which is a huge win for teams that actually ship things, rather than just playing with Jupyter notebooks.

it just means the infrastructure layer is finally catching up to the actual complexity of deploying and iterating on LLMs. stop treating ML development like artisanal craft and start treating it like production software.