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Socially aware systems
How an intelligent system should notice context, relationships, and ambiguity instead of acting like perception alone is enough.
Shybot
Shybot is a research and prototype effort for understanding how minds hold, miss, revise, and anticipate unfolding situations. It sits at the edge of human interaction, temporal reasoning, and cognitive style — especially where autism, ADHD, time structure, memory, and attention shape lived experience.
Core ideas
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How an intelligent system should notice context, relationships, and ambiguity instead of acting like perception alone is enough.
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How events accumulate across moments, how memory stays coherent or breaks, and how an agent reasons about what might happen next.
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How autism, ADHD, and different forms of temporal experience may require different models of attention, structure, and interpretation.
Current work
Real media enters the system through uploads, queues, handoffs, and structured jobs.
Object state, event memory, and possible or impossible next events become explicit system behavior.
Theory and language develop around time, memory, neurodivergence, and lived temporal structure.
Media workflows keep the project tied to concrete observations rather than abstractions alone.
Prototype work turns the ideas into mechanisms, memory, prediction, and inspection loops.
Research gives the project a vocabulary for explaining what temporal experience feels like and why it matters.
Reference
The name Shybot originally comes from MIT Media Lab work on socially aware human-robot interaction for children living with autism.
Read the original MIT Media Lab paper ↗Direction
shybot.org is the public front door for the project: a place to show the core ideas, the active prototypes, and the research language growing around them.