LN 040: The venerable hyperlink

Decades after hyperlinks transformed humanity's information and text into a densely-linked graph, mainstream OSs have yet to afford users their benefits in personal computing.

<i>Webstrates</i>: Shareable Dynamic Media

Shareable Dynamic Media is our vision for an interactive computing environment that blurs the distinction between documents and applications, characterized by three key properties: malleability, so that users can appropriate and repurpose media in ...

Hello, Operator!

Part of the WonderOS project, this is presented as the operating manual that would come with the reader’s first machine running WonderOS. It is an exercise in exploring how people familiar with mainstream personal computing devices and systems would become computer literate in an itemized environment. It is written as though the reader is familiar with today’s mainstream operating systems, and is exploring their first itemized OS.

Compiling Models to Megakernels

Fine-grained synchronization, deep pipelines, and zero kernel launch overheads, automatically.

The Topos of Programming | Yon

A topos-oriented programming language. Native via MLIR and LLVM, with a content-addressed heap on the Leech lattice.

MICROCOSM: An Open Hypermedia Environment for Information Integration.

This report examines open hypermedia systems, and argues that such systems provide users with richer and more diverse ways to access and integrate information from large and dynamic data sets in a distributed, heterogeneous environment. In particular, the enhanced Microcosm model for open hypermedia is examined, and the ways in which it provides such an environment are discussed. The paper continues by investigating the advantages and the short comings of this model and identifies areas in which further work must be completed before such systems can become widely adopted, in particular the granularity of link anchors, editing, and version control. Possible solutions to these problems are presented and discussed.

Plan B: an operating system for ubiquitous computing environments

The conventional approach for building pervasive environments relies on middleware to integrate different systems. Instead, we have built a system that can deal with these environments by exporting system resources through distributed virtual file systems. This requires no middleware, simplifies interoperation, and permits applying general purpose tools to any system resource. A constraint-based file system import mechanism allows the system to adapt to changes in the environment and permits users to customize the environment and tailor adaptation according to their needs. The system has been in use for over a year to carry out our daily work and is underlying the smart space that we built for our department

The Open Source Definition (Annotated)

The sections below appear as annotations to the Open Source Definition (OSD) and are not a part of the OSD. A plain version of the OSD without annotations can be found here. Introduction Open sourc…

How notebook.link Scales Without Backends

Notebook.link combines WebAssembly and the conda ecosystem to deliver scalable, serverless computing environments that run entirely in the browser. No backend. No scaling headaches. Just instant, collaborative scientific computing for everyone.

flo-bit - Repositories

building things for the web svelte/threlte/threejs/astro/atproto - flo-bit

Between Principle and Pragmatism: Reflections on Prototyping Computational Media with Webstrates

Computational media describes a vision of software, which, in contrast to application-centric software, is (1) malleable, so users can modify existing functionality, (2) computable, so users can run custom code, (3) distributable, so users can open documents across different devices, and (4) shareable, so users can easily share and collaborate on documents. Over the last ten years, the Webstrates and Codestrates projects aimed at realizing this vision of computational media. Webstrates is a server application that synchronizes the DOM of websites. Codestrates builds on top of Webstrates and adds an authoring environment, which blurs the use and development of applications. Grounded in a chronology of the development of Webstrates and Codestrates, we present eight tensions that we needed to balance during their development. We use these tensions as an analytical lens in three case studies and a game challenge in which participants created games using Codestrates. We discuss the results of the game challenge based on these tensions and present key takeaways for six of them. Finally, we present six lessons learned from our endeavor to realize the vision of computational media, demonstrating the balancing act of weighing the vision against the pragmatics of implementing a working system.

A Tale of Three WebAssembly Runtimes

Walking through the implementation of three different WebAssembly runtimes from scratch

MercuryWorkshop/anuraOS

A web "OS" and development environment with full linux emulation

WiCER: Wiki-memory Compile, Evaluate, Refine Iterative Knowledge Compilation for LLM Wiki Systems

The LLM Wiki pattern, to compile and provide domain knowledge into a persistent artifact and serve it to LLMs via KV cache inference, promises context access at sub-second latency with zero retrieval failure. Realizing this requires solving the compilation gap: LLM compilation distilling raw documents into a wiki without catastrophically discarding critical facts. We characterize this gap across 17 RepLiQA domains (6,800 questions): we observe that full context KV cache inference outperforms RAG on curated knowledge (4.38 vs. 4.08 out of 5, 7.3 faster TTFT) but degrades below RAG at scale due to attention dilution, and blind compilation fails entirely (2.14 to 2.32 vs. 3.46, 53 to 60% catastrophic failure rate). To address the compilation gap, we propose WiCER (Wiki-memory Compile, Evaluate, Refine), an iterative algorithm inspired by counterexample-guided abstraction refinement (CEGAR) that closes this gap. WiCER evaluates compiled wikis against diagnostic probes, identifies dropped facts, and forces their preservation in subsequent compilations. One to two iterations recover 80% of lost quality (mean 3.24 vs. 3.47 for raw full-context across the 15 topics with baselines), reducing catastrophic failures by 55% relative. An ablation across all 17 topics confirms that targeted diagnosis (+0.95), not generic pinning (+0.16), drives the gains. All code and benchmarks are released for reproducible research.