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I find myself unreasonably excited for the work that Taalas is doing.

I just gave a talk at DEVx giving a very early alpha preview of poprocks, a module providing simple golang primitives for building and working with Firecracker microvms.

Coding agents are amazing - sure.

For the past few months I’ve been working for the ARC Prize - a non profit organization built around the idea of an Abstract and Reasoning Corpus - a set of reasoning games that are easy for humans to quickly and efficiently figure out, play, and solve -…

Just released threadsafe_datastore, a simple, convenient thread-safe data store for Python.

Right off the bat I had users asking for salary negotiation as a feature on HiredCoach.

About five years ago (ok, that hurt to type.

I’ve long been a fan of task runners within projects - I find they’re practically required once you have a project or group operating beyond a certain level of complexity.

Just released structured-parse, a multi-language parser for block labeled LLM output.

Just pushed a pretty significant update to docker-harness.

Recently I took on a contract job to fill the coffers a bit while HiredCoach handles its initial launch.

tl;dr I talk about the ideas behind and efforts expended to build my AI framework, arkaine.

If I had the budget/compute power and time to research anything at the moment, this is what I would try researching.

tldr; A paper caught my eye, proposing a way to treat individual agent calls in multi-turn agent training as individual steps.

I recently gave a talk on DeepSeek V3 training improvements and the fascinating ideas behind GRM and SPCT.

It’s certaintly a fascinating time for robotics.

I’ve seen dozens and dozens of open source robotic arm projects; probably because of my own addiction to mechanical automatons paired with my unending desire (despite a lack of need) for a robotic arm of my own.

As I’ve mentioned before, I’ve been trying to learn to draw lately, initially inspired by a desire to be able to properly convey the headaches with pictures in my head to on-paper representations.

Recently, I gave a talk on several of DeepSeek’s innovations, which were as extensive as they were complicated.

Currently I’m going through the struggles of learning to draw from a very poor foundation of sub-stick figure talent and primarily spurred on by the desire to convert the vague ideas in my head to actual designed physical objects, this video spoke to me.

Back when I was working on coppermind at the heyday of GPT3.5’s initial world shattering release, I had… difficulty finding good ways to deal with parsing the stochastic LLM outputs.

Did some work on eli5equation, cleaning up and fully deploying prior one day project.

I have been busy due to a flood of inspiration to work on projects.

Given my recent weekend foray into Replit, I wanted to try a simple solo project to “kick the wheels” and test drive Replit a bit more.

This past weekend I participated in the Replit Hackathon held by SDx.

I am a reserved and ultimately shy individual, dealing with his own life is a way that best suits me.

I’ve long since embraced AI integrations into my AI, and I’ve experimented with several of the new app builders.

DeepSeek released another cool paper expanding on reinforcement learning for LLM alignment.

One of the great parts of building out tools like arkaine is that it allows me to sit down and just build for a bit to test the framework.

Version 0.0.21 of arkaine is out, including the finalized format for the text to speech tooling, equivalent speech to text tooling (though, admittingly, I currently lack a locally hosted option for this), and the think tool I mentioned earlier.

I simply love when simple ideas get tested and proven to be quite effective.

Inspired by OpenAI’s newest text to speech models, I decided to finally take a crack at text to speech on arkaine.

My framework arkaine, which I quickly presented a bit ago, finally has some nice documentation for it.

The paper club I host will be covering BitNet b1.58 Reloaded: State-of-the-art Performance Also on Smaller Networks!

I picked up David Bessis' Mathematica on a whim.

tldr I recently gave a talk at the SDx paper club which I run on the paper DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Last night Adam gave a great presentation at the SDx paper club.

A few weeks ago I gave a talk at an SDx paper club covering the DeepSeek R1 Paper.

I’ve been working on arkaine’s OCr service all weekend, and need a break.

Today I attended a mini-hackathon via SDx.

Here’s an ingenious set of hacks to cheaply modify the behavior of existing LLMs to reason better.

We’re kicking off 2025’s paper club series via SDx again on February 18th @ 6:30 pm.

I found myself looking into the effects of censorship removal from LLMs - particularly the recent popular kid on the block Deepseek R-1.

I recently gave (an unfortunately rushed) talk about arkaine - a maker-focused agentic AI framework I’ve been spending most of my time building.

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tl;dr Google DeepMind released a paper claiming that, without search, a transformer architecture can be utilized to achieve grandmaster level play in chess.

tl;dr A recent paper studied large language model’s (LLM) reactions to stimuli in a manner similar to neuroscience, revealing an enticing tool for controlling and understanding LLMs.

tl;dr I got nerd sniped by a problem and wrote a solver for it.

tl;dr For my Master’s capstone project, I demonstrated that not only can LLMs be used to drive robotic task planning for complex tasks given a set of natural language objectives, but also demonstrate some contextual understanding that goes beyond in…

Melvin Conway has a law that I’ve heard thrown about throughout my career building applications and backend systems.