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Hi, I'm @kafonek (Matt Kafonek) 👋

My first career was as a domain expert in the intelligence community. I fell into it as a young enlisted USAF linguist, and kept working in the field for almost twenty years as a geolocation specialist and technical analyst with VaST. I began learning Python around 2010 to help automate some day-to-day tasks. As I shared what I learned with other analysts, using tools like Jupyter, I developed a passion for empowering domain experts. One part of that is providing "no-code" / "low-code" tools, but an underserved need is giving them the right opportunity to begin learning and using code themselves.

My second career as a software engineer started with Noteable, a managed Notebook platform to make data accessible to all. I learned countless valuable lessons developing and deploying features for a production application. Our backend stack was Python (FastAPI) and CockroachDB (async SQLAlchemy), with the Kernel compute orchestrated through a Kubernetes Operator and custom resource definitions. We home-rolled RBAC and real-time synchronization 😬. When ChatGPT announced the plugin store, and later custom GPTs, we were in a unique position to be first-to-market with a Notebook/coding plugin, which landed on the initial "popular" store. I have seen what happens when a startup catches lightning in a bottle, and it is freaking cool.

My current interests are twofold: learning Rust and becoming more comfortable applying practical AI. I am excited about Rust because its syntax, build tools, and ecosystem are approachable. It's also blazing fast and compact. I believe the future of performant Python is Rust. Deploying apps to the browser with web-assembly has a lot of promise, and Rust has a tremendous story there. As far as AI goes, the experience with Noteable was "magical" but we were effectively just interacting with OpenAI APIs, whether it was ChatGPT making calls to us or our app making calls to OpenAI. I'm looking for opportunities to utilize local models, work with multi-modal models, and learn about deploying and optimizing models in production.

Outside of work I spend my time solving programming puzzles, playing video games, rock climbing with my wife, and taking care of our two young boys.

Matt Kafonek's Projects

burn icon burn

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

crossroads icon crossroads

Dabbling with trading algorithms for steam game crossroads inn

dangermode icon dangermode

Dangermode is a ChatGPT Plugin written with Python and FastAPI that allows users to execute code snippets in an IPython session.

demo-evcxr-sidecar icon demo-evcxr-sidecar

Demo of how to test sending Jupyter protocol spec messages to evcxr with kernel-sidecar

elk_compose icon elk_compose

ELK stack with APM server launched with docker-compose

euler icon euler

Repository for ipython notebook on project Euler puzzles

gridthings icon gridthings

Python library for doing things with Grid-like structures

httpx_ic icon httpx_ic

An "internal client" build on top of the amazing httpx Python library

img2dataset icon img2dataset

Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.

ipython_blocking icon ipython_blocking

A Python library that offers a context manager to turn on cell execution capture/blocking in Jupyter notebooks/IPykernel. Useful when you need a "blocking widget"

kafonek icon kafonek

Config files for my GitHub profile.

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