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jekude

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justinkennedy.com

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The abstract implies that strictly local updates are a hinderance to high res, however i would have thought there would be an interesting way to get speed up gains from neighbor-only traffic on GPUs CAM-style. am i making that up?

Insulin is lethal at higher dosages, so there is definitely an argument. My counter would be that someone who has to self administer this drug 5+ times a day should have the right to make determinations about dosing

Technically there is unsanctioned access (someone reverse engineered the real-time APIs [1] which I ported to Go). I think the FDA does not want easy access to real-time values so that folks can't easily recommend insulin dosing without oversight. I am personally of the opinion that it is our right to have programmatic access to the real-time data and do with it what we please.

Would love to get in touch to hear more about your long-term vision for the project!

[1] https://github.com/gagebenne/pydexcom

Recently diagnosed with Type 1 Diabetes, and learnt quickly that calculating insulin doses sucks (and you have to do it 4+ times a day). BolusGPT is a ChatGPT plugin that translates meal descriptions into nutrition information that is fed into an insulin dosing algorithm. Also hooks up to Dexcom CGMs. Happy to answer any questions!

Is it only academia and Google Research that is funding these kind of artificial life passion papers? Wondering if anyone knows of real-world applications / companies working on them.

Reading Permutation City changed the way I think, and I’ve been loving working my way through everything Greg Egan. It’s almost as if its a new literary genre - Computer Science Fiction.

Darwin Machines 2 years ago

I’ve been noodling on how to combine neural networks with evolution for a while. I’ve always thought that to do this, you need some sort of evolvable genetic/functional units, and have had trouble fitting traditional artificial neurons w backprop into that picture.

My current rabbit hole is using Combinatory Logic as the genetic material, and have been trying to evolve combinators, etc (there is some active research in this area).

Only slightly related to the author’s idea, its cool that others are interested in this space as well.

Rye looks great (i've also really enjoyed using Poetry as well). But man, do I have respect for Go's quality of out-of-the-box tooling. Feels like every time I start a Python project I need to re-learn the state-of-the-art wrt dependency/venv management.

While it is an interesting quirk of history that we mainly think about computability hand-in-hand with the "halting" problem instead of Turing's symbol-printing, there are so many more interesting nuggets in the 1936 paper (like computational universality, the first ever programming bugs, etc). I do think the paper linked gets the nuances of attribution here correct.

I wrote up a little guide to Turing's paper a while back [0] if anyone is interested in reading it but needs help like I did.

[0] https://github.com/planetlambert/turing/blob/main/GUIDE.md

Would anyone happen to have a recommendation for someone hoping to make Gödel's incompleteness theorem "click"? It feels like every time I reapproach it, I have to start the intuition building all over again.