Researcher / engineer
Tibor Sloboda
AI has been my passion since high school. So has science. The interesting part is finding out how things work, then doing something useful with that understanding.
Watching Stargate SG-1, I was fascinated by Samantha Carter: a scientist who could understand an unfamiliar problem and work out what to do with it. The idea of a personal AI assistant helping with everyday life and research stayed with me too. I wanted to understand how something like that could work.
That curiosity became research and engineering. I work across models, data, software, and hardware, with experience in domains from chemistry and medicine to production LLM systems. I have led teams, made technical decisions, built prototypes, and helped turn them into production software. Understanding the business is part of that work: what someone needs to achieve determines what is worth building.
AI is bigger than the current conversation
I find the sudden abundance of “AI experts” frustrating, especially when AI gets reduced to LLMs. There are applications in imaging, scientific analysis, prediction, audio, and hardware that could make people’s work easier, and many people never hear about them.
I want to help people discover what is useful for them. Sometimes that means building an AI system. Sometimes it means explaining why their problem has a simpler solution. I would rather tell a company that AI is not worth its time than sell it software it does not need.
What I am building
Alongside my consulting and PhD research, I run aleph0, a separate venture developing low-level software for AI on heterogeneous hardware, particularly at the edge. The work includes hardware-specific compiled models, a single-binary runtime, and model optimization for compatibility and lower power use. It is in development, intended for open source, and has no users yet.
Outside client work
Rust, Lean and constructive mathematics, NPUs, Linux, graphics, audio ML, game systems, and odd software experiments all belong here. I like following a problem into the layers underneath it, including the ones I did not initially expect to need.
The lab is for experiments; essays and rants are where I work through ideas and technical opinions. You can call me Jack.