Have been building a design tool for Spatial Computing [0] Me and my co-founder struggled for over a decade working in XR and wanted to simplify the design process for us and everyone else. We've been focused on reducing steps between design iterations by as much as humanly possible. So the tool works live, multi-user, in real-time and immediately across all compatible devices.

Here's a recent example of whats possible from one of our users [1], and a recent project I made for fun that you can try on your iOS [2] or Meta Quest [3] device.

[0]: https://ordinary.space

[1]: https://www.linkedin.com/posts/matt-rice-sennep_mixedreality...

[2]: https://app.ordinary.space/#/share/b2d3d7

[3]: https://app.ordinary.space/#/share/96b9cf

I've been slowly building https://www.hamradiolog.net/

As part of that, I made an ADIF (ham radio logs) parser to learn go. It's more than 2x faster than parsing the same data in json format with the go standard library.

https://github.com/hamradiolog-net/adif

Late to the game here, but I'm working on Basic Memory (https://memory.basicmachines.co/docs/introduction), a knowledge management system for the Model Context Protocol (MCP).

What makes it different:

* Claude (and other MCP AIs) can both read from and write to your local markdown files

* Creates a connected network of notes that Claude can navigate between

* All data stays as markdown files on your computer

* When you chat with Claude, it automatically builds structure with simple patterns

* You can start a new chat and just say "Let's continue discussing X" without uploading files or copy/pasting

* Files are available locally, so you can edit them in and editor, like Obsidian, VS Code, etc.

I built this because I was tired of repeating myself to AI assistants and wanted my conversations to accumulate into something useful over time. It's basically a way to give Claude persistent memory while keeping your data local and be easily readable and editable my humans.

Some people are using it to maintain project context across sessions, document systems, and build topic maps without having to manually organize everything.

Demo video: https://basicmachines.co/images/Claude-Obsidian-Demo.mp4 GitHub: https://github.com/basicmachines-co/basic-memory

Writing a book on my unique theory on human psychology based on cynicism, military theory, and evolution.

Is has helped me to address all of my problems, from mental health to productivity to learning across all domains like economics, writing, coding, marketing.

Writing daily blog posts, and then piecing together everything into the book. https://www.moderncynicism.com/

Working on an embedded DSL for writing typed LLM workflows in Haskell: https://github.com/outervation/promptyped . It handles the "LLM in a loop" structuring for e.g. forcing an LLM to keep making changes in a loop until unit tests pass, and custom validation so the LLM is forced to retry a task if the validation fails (validation can include using a LLM to check the result, or plain Haskell function, or e.g. running a compiler/unit tests). It also allows structured context management, allowing the user to specify which files are initially provided as context to a task (which may itself be the result of a LLM query), as well as providing the LLM tools to open files it deems relevant, and prompting it to close the least important file when it has too many open (and compressing non-recently-modified source files when many are open).

Currently heavily WIP though and only has a working Go compile/test backend (Go seems particularly easy for smaller LLMs like o3-mini to work with due to being a relatively non-complex language).

Busy building some personal infrastructure around information. Think mix of scrapping and filtering, scoring and summarization.

Clearly all of the info space is getting ever more polluted and I just don’t trust anyone else (with their own agenda) to manage and filter that for me. If one is to abdicate that sort of responsibility to a system wholesale then I think it has to be fully under one’s control, own data, own design, self hosted etc

We are working on a fast reading font which works by using just opentype features (no server or other script required)

https://github.com/Born2Root/Fast-Font

We also created some emoji fonts: https://github.com/Born2Root/Feature-Fonts

Writing a science fiction book this year - after a year of planning (while working on other projects).

Also hoping to find some time to add a feature or two to my Video Hub App

https://videohubapp.com/ & https://github.com/whyboris/Video-Hub-App

I have been filling my brain.

A long time ago I played around with neural net stuff and had some fun making tiny little things. To give an idea of time frame, this was before people were using ReLU.

Going back to it after the recent advances was incredible seeing how much has happened. So many times I'd see something and wondered how I could have missed it the first time only to realise it hadn't been invented yet when I did things last time.

It feels like there is a much higher focus on statistical mathematics now in a way that it permeates everything. That in itself requires a whole lot of new learning to get to grips with, but I also feel like there might be some value in looking at a lot of these things from a different perspective. I think I tend to look at things from a more geometric point of view.

In that vein I have been looking at some transformers using unit n-sphere embeddings with V values as geodesics, just to see what happens.

As I learn new things, I keep finding fun new ideas to muck around with, I'm just an amateur, so I'm not really restricted by areas I look at. Today I'm wondering about whether Wasserstein distance could be quickly approximated by a learnable method (especially if the inputs had access to parts of the ml components that generated the things being Wasserstein compared).

I'm almost certainly treading ground well explored by others, but my way of learning seems to be to rapidly jump between many different things picking up a small understanding of each as I go until I just seem to know things that I didn't before. Focusing on a topic and pushing in that direction never seemed to work for me so much. This is probably why I am an amateur :-)

RubyExamples.com [1]

Got inspired by Go by Example [1] while learning Go. Realised there's nothing for Ruby like that and decided to build.

Goal is to have simple urls for one-click navigation for each topic where the page covers a single topic briefly with examples, with relevant links and historic artifacts (for example, it links to the "Programming with Nothing" talk in procs/lamdba page [3]).

It's still a work in progress and I'm not rushing it.

The examples are all my own. It's easy to do with AI, but I'm not going that way. I'm explaining things based on my own 12+ years of ruby experience.

Like GoByExample, this is also desktop only, but mobile-friendly is on the roadmap. The CSS also will change to be someting like RailsGuides. Might also add a video for each topic explaining the code.

[1] - https://rubyexamples.com/ [2] - https://gobyexample.com/ [3] - https://rubyexamples.com/p_and_l