Left my job to focus 100% on math, CS and ML for a while. Haven't got a precise end goal in mind at the moment but I think something will emerge. Here's the stuff I am learning, learning process, etc:
1/n
I’ve wanted to do this for a decade.
But I never did - I refuse to give any company my DNA.
It is me.
So this week I sequenced my genome entirely at home. Literally on my kitchen table.
I never exposed my DNA sequence to the internet. Not at any point.
I used a MinION to do the sequencing (it’s smaller + weighs less than an iPhone).
I used open-source DNA models for the analysis (Evo2 and AlphaGenome) running locally on a DGX Spark and Mac Studio.
I traced mechanisms behind my family’s multigenerational autoimmune conditions that no clinician has been able to understand.
When I set out to do this I didn’t know if it would actually work. It does.
Your genome is the most private data you will ever have. You probably shouldn’t let it leave your house.
Science begins with myths becuase by the standards of the consensus "best current theory" which defines what we think of as "real" any deviation will appear like fantasy
Top centaur-era skill = leveraging massive search. How fast can you spam attempts in parallel and trial and error your way to success. Make trials as fast+cheap as possible, learn from failure, apply computational approaches creatively to domains people aren't using them
Daily progress #6
+ utilisation rate is going up, the goblin is satisfied
- but more can be done
- the big unlock is going to be increasing walkaway time so I can run overnight with 100% confidence
Daily progress #5
+ made a script to track what % of the day our workcell is running
+ my sole aim is to make number go up
+ had fun benchmarking claude against himself at colour mixing optimisation
+ the system feels robust enough to leave running overnight 💪
Daily progress #4
- declared victory too soon w/ opencv well detector, it struggles with colours
- thx @ZECTBynmo@Willqyu@dnbt777, gave me great ideas to fix
- testing bioreactor dispensing w/ liquid handler pipetting
- ready to cook some yeast i think lads
Daily progress #2
- got the gripper to place microplate lids back on plates
- this is one of the trickier lab tasks because plates have quite unforgiving clearances
- uses the same visual servo + CAD offset tricks from yesterday to make placement accurate
I spent a decade hoarding facts and ideas into a collection of 30,000 flashcards cards that I reviewed obsessively with spaced repetition algorithms. The great thing about these systems is that they get you to learn all kinds of fuzzy heuristics for what you value.
1/5
I wonder if we could create synthetic re-discovery tasks for AI systems? Could we ablate certain concepts and see how much longer it takes to find the solution to problems? What might it tell us about knowledge itself?
Full article here: https://t.co/DH4R6NIJZJ
5/5
It suggests that one of the ways you can value a golden nugget is in how well it reduces the search space for problems you haven't encountered yet.
4/5