Make a pattern recognizable
A Tale can begin with a photograph, a scene, a diagram, or a short video. Human context is part of the explanation, not a decoration around an equation.
A Yāska Labs project · Concept development
Stories you can
touch, question,
and change.
ModelTale explores a new medium for human expression: small, interactive models that make relationships and consequences visible.
Watch it. Touch it. Ask why.
A bridge from everyday experience to mathematical reasoning.
Interactive concept illustration
The rush arrives.
What happens to the queue?
A simplified café with a steady flow of orders.
12orders arriving / minute
10orders served / minute
20 additional orders waiting
After 10 minutes under these assumptions.
Why?
Each person can serve 5 orders per minute. Two people can serve 10. If 12 orders arrive each minute, 2 remain waiting. Over 10 minutes, the queue grows by 20 orders.
Queue growth = max(0, arrivals − people × 5) × 10
Assumptions & limits
Assumed: a constant arrival rate, identical staff capacity of 5 orders per minute, no starting queue, and a ten-minute interval.
Calculated: service capacity and additional queued orders. No values here are measured operating data.
Not represented: varying order complexity, breaks, teamwork, equipment limits, fatigue, or random arrivals. This is an explanatory toy model, not a staffing forecast.
This small website illustration demonstrates the idea. It is not the ModelTale platform or evidence of product effectiveness.
The medium
A Tale is a small
living model of a situation.
Start with a recognizable experience. Change something. See what follows. Open the deeper explanation when curiosity creates a reason to learn.
Explore a meaningful change
Adjust a variable or assumption and see how the model responds. Prediction can be one interaction, introduced after the viewer understands the situation.
Ask why, then go deeper
Reveal the relationships, evidence, uncertainty, and mathematics behind the result. Formal notation appears when it helps the viewer understand.
The proposed Studio
Build from something
you already understand.
The intended creator experience starts with situations, images, and relationships, then progressively exposes formal structure.
Everyday expression, with an inspectable model.
A creator could describe a situation, arrange variables and relationships, use photos as model elements, or start from a reusable Tale format. Equation entry and imports are longer-term authoring directions.
The goal is to make modeling accessible to people who do not identify as mathematical, while preserving a path to functions, equations, proofs, and more rigorous reasoning.
Possible subjects range from budgets and daily routines to ecological relationships, group dynamics, and scientific explanations.
Story SurfaceThe scene people encounter.
ModelThe relationships underneath.
InteractionWhat someone can change.
LandingA readable consequence.
WhyExplanation on demand.
LimitWhere the claim stops.
Video Tales
The person tells the story.
The Tale captions the system.
A proposed Video Tale uses timed overlays and a meaningful interaction to reveal the relationships inside a short video.
Show the system as the story unfolds
A creator describes a late night. Captions connect sleep, energy, and the next day’s workload. The viewer can inspect the proposed relationship and its limitations.
Create a reason to ask why
After orientation, a video pauses at a new decision. The viewer predicts an outcome, then explores the model’s explanation. Predictions are intended to be private by default.
Same scene. Different attention.
A single video can support multiple perspectives, such as customer, employee, and manager. The model makes the differences in assumptions and attention explicit.
Explore a different path
Prerecorded branches can illustrate different choices or model conditions. The first prototype need not depend on generated video or automatic object tracking.
The Why & Limit layers
An attractive model
still needs an honest claim.
ModelTale is intended to make assumptions and boundaries visible. A model’s output is not automatically a fact about the world.
What was observed?
Show the data, its source, and the population or context it describes. Distinguish evidence from an author’s interpretation.
What did the author choose?
Expose the causal structure, values, simplifications, and conditions on which the model depends.
What follows from the model?
Show the result as a consequence of the stated inputs and relationships, including uncertainty or unsupported regions where applicable.
Perspective, recognition, and structural remix
Some Tales express a personal perspective rather than an externally testable prediction. Recognition reactions such as “That’s me,” “Partly,” and “Not my experience” are proposed ways to respond; agreement is not proof.
Structural remix is a central design direction: change a factor or relationship and show how the alternative behaves. Model changes should remain visible, so disagreement becomes something people can examine.
A future path for researchers and scientific communication
Simple models could run within a bounded native system. More complex models could remain in a researcher’s existing environment and expose a controlled response surface, with source links, scope, uncertainty, and checks of approximation fidelity.
The longer-term vision includes interest groups, researcher profiles, conference explanations, journals, and institutional publishing partnerships. These are future possibilities, not an existing peer-review service or publisher network.
What we need to learn
First, prove
the medium is useful.
The initial research question is whether people want to explore models presented as media—and whether that interaction improves understanding.
One situation, one interaction
Build a narrow still-image Tale and a short Video Tale with a Why layer and explicit limits. Keep the first creation and viewing experience simple.
Compare the experience
Compare static explanations, video with ordinary captions, and interactive Tales. Study comprehension, delayed recall, curiosity, and willingness to create or share.
A social and creator ecosystem
Explore structural remix, groups, adaptive mathematical learning, and professional model publishing after the core experience demonstrates value.
Business and creator-economy directions
Potential future models include creator tools, premium learning experiences, institutional access, and partnerships around research communication. In-app rewards and creator incentives have been explored as concepts, but no currency, payout system, or paid publishing service is launched here.
These directions need user research, sustainable economics, and appropriate moderation before becoming product commitments. The platform remains named ModelTale while naming alternatives are evaluated.
Investors · collaborators · founding builders
Help make reasoning
a medium people want to use.
We welcome mathematicians, interaction designers, engineers, educators, creators, researchers in learning and social systems, and investors interested in testing a new form of expression.
Start with your area of expertise, a relevant project or paper, and one small contribution you would like to explore. Collaboration scope, time commitment, and any compensation or equity terms are discussed individually.