Software 2.0 (SW2.0) describes the concept of machine-written programs to reach an operator- or human-set goal (eg, win a game of chess).
Using machine learning (ML), neural networks span a search space within a possible program space to test, iterate, and identify the most efficient program to reach a goal.
As key component of SW2.0, techniques such as MLOps facilitate the development and deployment of ML models at scale; Similar to DevOps for traditional software development, MLOps combines infrastructure, tools and workflows to provide faster and more reliable ML pipelines.
