Why Catalase?
"So it's a hangover cure then?", said Brendan.
Well, uh, no, that wasn't why I called my company after the enzyme Catalase. I had other reasons.
Catalase
SeqQuests is a new collection of bioinformatics software. It is at an early stage.
Catalase explores organizing principles in engineered and biological systems - patterns that repeat across scales and domains.
To learn more contact: [email protected]
I founded my company, Catalase Systems Ltd, in 1999. It's a solo-entrepreneurship, a company structure that allows me to work freelance and move between work in different companies.
The insight behind the company was that with a careful choice of hardware and bespoke software, ordinary PCs could handle very large problems efficiently. Sorting, searching and comparison are the foundations of extracting insight from data. Catalase was founded to do that.
Working in Ireland, companies wanted other things too. I've worked on validating software for the SOHO and ISO satellites. These missions were an ESA/NASA project to study the Sun. I've worked on high speed data converters for telcos, EDA tools for FPGAs, broadcast television graphics. I've written software for analyzing images to understand cells.
AI has materially shifted the kinds of things Catalase now works on. With careful use of AI, I can now build software that would have taken too much time to write before. I'm harnessing that new 'superpower' to find ways to organise information that will make a difference for the better.
In the posts below, I cover topics such as why the company is called Catalase, how come there is 'low hanging fruit' in terms of science that is not yet widely known, and why we need to be extremely careful about AI.
To make it real, I also provide MIT licensed software, the SeqQuests software linked at the top of the page.
"So it's a hangover cure then?", said Brendan.
Well, uh, no, that wasn't why I called my company after the enzyme Catalase. I had other reasons.
Barbara McClintock's 1940s observations on transposable elements were dismissed for decades. Her 'jumping genes' were unthinkable. She eventually received the Nobel Prize in 1983. The prevailing mindset was wrong, not her science.
In time the unthinkable became mainstream. Let us identify what's unthinkable today, but that will be taken as a given tomorrow.
AI is enabling advances in science, technology and engineering. The problem is that as we get better at working with knowledge, we gain more power. This really is a significant problem.
Greater power from STEM advances will bring very good and very bad things. We can't stop these bad things by 'stopping AI'. An AI pause will just push AI into the hands of the people most hungry for power. We have an alternative. We can collectively make sure more of the good things happen, bring the good things into reality sooner, and we should.