In the early days, programming involved creating detailed algorithms and following explicit rules using languages like C, Java, and Python.
With the advent of machine learning, programming shifted towards teaching machines using examples and patterns rather than explicit instructions.
Today, programming is a collaborative effort between humans and machines, with machines processing large amounts of data, adapting to new contexts, and freeing up humans for creative problem-solving.
Challenges in this evolution include biases in training data, the complexity of modern systems, and ethical implications, but hybrid models and new tools are emerging to address these challenges.