Systems theory holds a simple truth: every part of a system influences the rest. No action is isolated. No choice is neutral. Change ripples. AI is a ripple in systems, but if the system is not healthy, AI will not help.
IBM explains AI, machine learning, deep learning, and neural networks in a way that highlights how each layer exists in relationship. Adjust the input and the model changes. Adjust the model and behavior shifts. Adjust the behavior and outcomes follow.
Work and life operate the same way. Input leads to output.
A sabbatical is not a pause. It is a causal intervention. Remove routine and perception changes. Change perception and motivation shifts. Realize motivation and decisions improve. What looks like a break is actually a reset that alters system perception.
All things relate. Even rest.
IBM link to:
AI vs. machine learning vs. deep learning vs. neural networks: What’s the difference?
See my LinkedIn profile for Sabbatical Day 7 post.