Bonjour

I'm Kaelan Donatella, and welcome to my personal website!

I am a researcher in physics-based computing. My dream (and of anyone in that field, I believe) is to find a way to build an artificial brain, a.k.a. a self-learning machine. One would feed data into this machine, and the machine would learn general skills from this data, as a child does. Another thing I am personally quite fascinated about (and that is related to the self-learning machine) is understanding the fundamental limits to intelligence in terms of hardware requirements and energy consumption: something like a limit on performance of a chosen benchmark such as ARC-AGI per Watt.
For a bit of background: I was trained in physics (because isn't it just the best field to study at university?), and worked at the intersection of quantum computing/physics and machine learning during my PhD. I was initially excited by quantum computing and in its synergy with ML before I realised that quantum computers were a bit too far ahead (10 years? 20 years?) to continue working on them. Mostly because it appeared to me that there are two paths to improve quantum computers: improve the qubit and gate quality, or improve error-correcting codes, and these things I was not particularly fond of. I then joined Normal Computing to pioneer new hardware, coined thermodynamic hardware whose purpose is to accelerate and optimise. linear algebraic and ML workloads.
You can find my publications here and my open-source contributions here on this website. Don't hesitate to write to me at kaelandonatella -at- gmail -dot- com if you want to chat about something.