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.
TSM-6: Simplifying Lisp with Homoiconic C — All You Need is FOLD
Lisp has long been revered as the Platonic ideal of programming languages, its minimalist design where code and data share the same structure—lists—grants Lisp unmatched power and flexibility. But for all its elegance, Lisp’s strength also breeds complexity. Despite its simple syntax and aversion to assignment, Lisp still relies on a variety of special forms—like... Continue Reading →
TSM-5: Homoiconic C (HC) Syntax Cheat Sheet
Homoiconic C ("HC") is a minimalist and highly expressive alternative to traditional programming languages. It eschews traditional grammar, keywords, and reserved words, focusing instead on a single type of object called a Frame. HC's syntax is a thin veneer over its robust semantics, which are centered around ubiquitous scope, consistent evaluation, and homoiconicity (symmetry between code and data). This cheat sheet provides an overview of HC's key syntactical elements.
TSM-4: Total Computing with Pres — The Future of Safe, Expressive Software
For decades, Turing-complete computing has been the bedrock of modern programming. While this has empowered developers to create powerful, general-purpose systems, it has also forced us to accept a troubling reality: bugs, crashes, and unpredictable behavior are often seen as inevitable. These issues are typically viewed as the price we pay for the flexibility and... Continue Reading →
TSM-3: Sigma Calculus and the PEACE Monad
The Sigma Calculus is a formal system for deterministic stateful computation, acting as both a generalization and simplification of the Lambda Calculus. It defines a system of Monads and Symbols for a computational framework closed under left-to-right evaluation.
TSM-2: Alan Turing versus The Shannon Machine
### Alan Turing Here’s a simple breakdown: **Shannon Machines:** - Start with data structures, with computation as secondary. - Focus on associative memory and managing state. - Use binary operators and bit transforms for math simulation. **Turing Machines:** - Start with basic arithmetic and build up to computation. - Provide a theoretical framework, independent of practical implementation. - Use algorithms to simulate any computing process.
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.
The Fractor Model: Precise Shared Mutable State Management for Systems Programming
The Fractor Model, inspired by BitC and Jonathan Shapiro, refines the Actor paradigm for better control over shared mutable state. Fractors offer explicit state and effect handling, ideal for low-level concurrent programming. The key innovation is fractal-like, fine-grained control over mutable state at the method level, improving programmer ergonomics and enabling automated type-checking.
Abstract: X-JEPA – Mimicking Human/Cultural Cognition via Multi-Stage Semantic Mapping
The X-JEPA model introduces a multi-stage approach to semantic mapping, advancing the foundational principles established by eXtending the Joint Embedding Predictive Architecture (JEPA). This new architecture aims to develop cultured AI by mimicking human cognition through a layered structure that progressively builds on JEPA's semantic maps.
How to Build LightDash from Source
LightDash is a super-cool Open Source business intelligence tool built on top of DBT (which I think of as node for SQL). While it is distributed as open source, the usual way to deploy it locally is by simply running a docker container. If you want to actually built lightdash directly from source yourself, you... Continue Reading →
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