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Explore What Others Are Building
Here is a sample of public Insights made by Insight Maker users. This list is auto-generated and updated daily.
This model simulates the tradeoff between AI costs in resources and the benefits of increased efficiency and effectiveness over time, using adaptive learning principles. It demonstrates how AI development evolves through different stages early, growth, and mature -with changing rates of investment, efficiency gains, and resource utilization.
The model tracks how AI systems stabilize over time as efficiency gains become harder to achieve, leading to a more mature and balanced system of investment and performance. It aims to provide insights into real-world AI dynamics, showing how resources translate into efficiency improvements and how diminishing returns, learning saturation, and reinforcement learning affect long-term growth.
Simple macroalgal uptake, erosion and mussel grazing model using nitrogen (DIN = dissolved inorganic N and PON = particulate organic N) as the limiting nutrient.
Often times there are a number of parameters in a model you want to set to specific values and run the model to demonstrate a particular behavior. When there are several variables involved remembering the setup is often difficult and takes time. And can you demonstrate the behavior when you're not there? Developing scenarios with Button scripts is a quick way to overcome these difficulties.
WIP SD representation of Ch11 of their 2007 Monetary Economics book, as suggested by Adam K. Plan is to do a top down simple money flow SFC mmt model and successively split sectors. See also essence of MMT IM and simpler version Ch3 IM