can we create abundance using state machines

my thesis is abundance will be created by our ability to achieve exponential growth in physical industries using AI (manufacturing, energy, supply chain, etc.)

physical industries' growth, towards whatever metric (throughput, revenue, profit, etc.) comes from their decisions. decisions, functionally, are where they choose to allocate their assets. for example, a manufacturing company's transition from window panes to bottles involves investing in time to train employees, repurpose equipment, changes in clientele, etc. all of which can be quantified.

models, in theory, can view a larger decision space - they are just missing a way to model an allocation of assets, or a state, as verifiable ground truths. past that, continuously improving models are, and will be, able to infer its decision space and attached outcomes.

thus, we reach the state machine. my thesis on how to give models the potential to drastically increase margins, and achieve abundance in physical industries through optimization.

next I will be:

• finding the best way to embed this context shape,
• post-training a model to understand it, and
• learning how to evaluate and deploy it.