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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 was developed to support Health Systems Thinking & Learning Events using the systems dynamics modelling approach.
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.
Use a bathtub model to investigate the manner in which inflows and outflows govern the quantity of a stock. Extend the structure to create and investigate the relationships of a goal seeking balancing loop.
Il modello dinamico di Baranyi e Roberts per la curva di crescita di microrganismi (Baranyi, J., Roberts, T. (1994). A dynamic approach to predicting bacterial growth in food International journal of food microbiology 23(), 1 - 18).
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E' un modello dinamico che assume che la fase lag sia dovuto all'accumulo di un composto essenziale (la cui quantità iniziale riflette lo stato iniziale delle cellule nell'ambiente E1, da cui provengono), secondo una cinetica di primo ordine, ad una velocità che dipende dall'ambiente E2. Il modello è lievemente modificato rispetto all'originale, per evitare che la quantità del prodotto essenziale tenda all'infinito.
My model simulates Ukraine's changing population from 2026 to 2126. The population increases through births and immigration, and decreases through deaths, emigration, and conflict. Deaths, immigration, and emigration are determined by their pre-war rates for simplicity. Birth rate is initially at its value during the war to reflect the declining fertility, but increases to an estimated "rebound" rate post-war (assumed to be the year 2030 as conflict is still ongoing). "Conflict" is represented by a static, yearly decline in population from 2026 to 2030 to reflect a combination of civilian/military deaths, increased emigration, decreased immigration, refugee movement, etc. Carrying capacity is an estimate assuming that wartime conditions such as destroyed infrastructure and decreased production will eventually rebound.
Projected Density-Dependent Population of Ukraine from 2026 to 2126
