Tag: technology

TSM-10.1: HLIR – Homoiconic, High-Level Intermediate Representation

instructions in a homoiconic form. It represents a novel synthesis in compiler design by bridging the gap between human and machine representations of programs. By combining monadic composition with homoiconic structure, HLIR allows developers to express computational intent with minimal syntax while maintaining direct mappings to MLIR's powerful optimization framework. This marriage of high-level semantics with low-level compilation produces a uniquely ergonomic intermediate representation - one where code is data, transformations are first-class citizens, and optimization becomes natural rather than imposed. The result is a language that is both easy for humans to reason about and efficient for compilers to transform, potentially setting a new standard for intermediate representations in modern compiler design.

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Littoral Governance: A New Politics for the Age of AI

Littoral Governance represents the next evolution in political systems—one that mirrors the co-evolution of AI and human systems in Littoral Science. It responds to the complexity and speed of the AI-driven world by embracing decentralization, distributed decision-making, and collaborative governance.

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The Quilt Platform: Version Zero of the Littoral Toolbox

The Quilt Platform serves as a robust starting point for building the Littoral Toolbox, aligning closely with the goals of Littoral Science—collaborative, AI-powered, interdisciplinary research. With features like data versioning, cloud integration, verifiable data packaging, and metadata management, Quilt provides the essential building blocks for the Littoral Toolbox’s v0.

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The Littoral University: Redesigning Higher Education for the Age of AI

Prompt: What would a Littoral University designed from first principles around abundant computational intelligence differ from what we have today? The emergence of a Littoral University, grounded in AI-driven, interdisciplinary research and lifelong learning, would profoundly disrupt the traditional funding models of higher education. Tuition would move from degree-based payments to subscription and modular learning, catering to a diverse range of learners over their lifetimes. Research grants would shift from discipline-specific funding to problem-oriented and global collaborations, supported by AI’s ability to facilitate efficient, cross-disciplinary projects.

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TSM-7: From Aristotle to Newton — Towards a Scientific Theory of Computation

Since the dawn of computer science, our understanding of computation has been shaped by mathematical theories, from Aristotle's logic to Turing's formalization of algorithms. Turing Machines, with their elegant abstraction of computation into discrete steps on an infinite tape, have become a cornerstone of computational theory. However, this mathematical approach, while powerful, lacks a crucial element: empirical testability.

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TSM-1: The Shannon Machine — Better Than Turing Complete?

The Shannon Machine is a decider computational system which uses bit-level word operations (rather than high-level computation) to perform arithmetric. The goal is model practical computation in a way that is more realistic -- but still as formal -- as the Linear Bounded Automoton, which has a similar level of computational power.

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