C) not smart enough to be a self-taught bio-hacker
Everyone hears "AI is going to cure disease" and pictures some cure-all pill from a bio lab which is what I feel this paper is hinting at is missingb but that's the top of the funnel; I'm at the bottom where patients live and that is where AI is already quietly working. Its just not being benchmarked.
I built https://crohns.ai. I set out to make an AI-native clinical-trial manager with a feedback loop (DDP) and ended up somewhere completely different: instead of chasing a new "drug" which is totally out of my grasp; financially, intellectually etc... I used it to codify a care protocol that helped me avoid a flare after I got laid off, lost my insurance, and lost access to Skyrizi.
If given the chance, I might go back on it because my protocol can be a little strict at times but either way I do see a significant shift to tools like this given the state of the US Healthcare system.
cool. i like what you've done here with a virtual panel that can answer questions ... i have similar ideas for kabuki syndrome (currently: https://www.thekabukipapers.org). talk? marstall at gmail.
i like what you've done here with a virtual panel that can answer questions
Thats the main thing. I think that Ai-native governance by domain experts is how AI reaches its full potential. Not in theory but in terms of the value it delivers to populations via outcomes.
AI-native Governance is like irrigation for the outcomes populations want to achieve, starts with intents; executed on by programs that use protocols as guardrails. This is a gross oversimplification of the process but based what i see from your work you will get the abstract.
Each codify.* is a PDA [Public Domain Agent] - that gets delegated intents per request and has to manage its own "deal" - its also managed democratically via ontology and downline policies set by the experts in said field and has feedback loop to verify/optimize policy outcomes.
This concept applies to everything IMO, and I cannot say I fully understand it but im absolutely obsessed with the exploration of the idea; again - in practice not theory. I have real outcomes in healthcare, education and housing.
how do you define the specialists? a prompt? what do you mean by using protocols as guardrails? Also, can you give me a TLDR on how these voice interfaces work? What kinds of problems are you solving, and how, in an ELI5 way. I might be a lot dumber than you give me credit for!
Comments
I think the real win here is for idiots like me:
A) no education
B) no resources
C) not smart enough to be a self-taught bio-hacker
Everyone hears "AI is going to cure disease" and pictures some cure-all pill from a bio lab which is what I feel this paper is hinting at is missingb but that's the top of the funnel; I'm at the bottom where patients live and that is where AI is already quietly working. Its just not being benchmarked.
I built https://crohns.ai. I set out to make an AI-native clinical-trial manager with a feedback loop (DDP) and ended up somewhere completely different: instead of chasing a new "drug" which is totally out of my grasp; financially, intellectually etc... I used it to codify a care protocol that helped me avoid a flare after I got laid off, lost my insurance, and lost access to Skyrizi.
How are those biologics? Did you have to visit the doctor to get injections frequently?
Hands down the best drug I have been on EVER; but its 11k a month with no insurance.
The 1st 2 injections where done by a nurse that came to my home, the others were done as self injections using their njection kits.
Ironically, now I have several people that are on it tracking their infusions etc...
Intent: https://wiki.crohns.ai/agent/posts/ibd-biologic-switch-decis...
Program: https://crohns.ai/program/71168-biologic-therapy-initiation
Protocol: https://crohns.ai/protocol/71168
If given the chance, I might go back on it because my protocol can be a little strict at times but either way I do see a significant shift to tools like this given the state of the US Healthcare system.
cool. i like what you've done here with a virtual panel that can answer questions ... i have similar ideas for kabuki syndrome (currently: https://www.thekabukipapers.org). talk? marstall at gmail.
Thats the main thing. I think that Ai-native governance by domain experts is how AI reaches its full potential. Not in theory but in terms of the value it delivers to populations via outcomes.
AI-native Governance is like irrigation for the outcomes populations want to achieve, starts with intents; executed on by programs that use protocols as guardrails. This is a gross oversimplification of the process but based what i see from your work you will get the abstract.
Examples -
dietmanager.com - RDN governance
crohns.ai - AGA (MD/GI) governance
<city>.us.codify.city - City council Governance
Even applies to YC: https://openyc.orgEach codify.* is a PDA [Public Domain Agent] - that gets delegated intents per request and has to manage its own "deal" - its also managed democratically via ontology and downline policies set by the experts in said field and has feedback loop to verify/optimize policy outcomes.
This concept applies to everything IMO, and I cannot say I fully understand it but im absolutely obsessed with the exploration of the idea; again - in practice not theory. I have real outcomes in healthcare, education and housing.
I just fixed Crohn's AI council, it's now all members of the AGA but i'm having serious issues keeping it all up.
The jobs to harvest the corpus needed to create each agent is not scaling well.
Note: crohns.ai: 3,948 gastroenterologists, dietmanager.com: 1,752 RDNs
how do you define the specialists? a prompt? what do you mean by using protocols as guardrails? Also, can you give me a TLDR on how these voice interfaces work? What kinds of problems are you solving, and how, in an ELI5 way. I might be a lot dumber than you give me credit for!