cross-posted to pan narrans Why rationalists should care (more) about free software especially if you want to upload your brain > In the limit condition freedom of compute is freedom of thought. As we offload more of our cognition to our computational devices we expose a new threat surface for...
Let us represent our beliefs as nodes in a network. Most nodes in your network of beliefs have dependencies, they are connected to other beliefs the truth value of which they are contingent on. Picture a subset of your network of beliefs, let us take a simplified section that looks...
The lack of good population genetic information in animal models and deep phenotyping of complex behavioral traits is probably one of the biggest impediments to robust animal testing of this general approach.
(For people reading this thread who want an intro to finemapping this lecture is a great place to start for a high level overview https://www.youtube.com/watch?v=pglYf7wocSI)
Kind of, there are many ways that changed in isolation get you a bit more oxygen but many of them act through the same mechanism so you change 1000 things that get you +1 oxygen on their own but in combination only get you +500.
To use a software analogy imagine an object with two methods where if you call either of them a property of an object is set to true, it doesn't matter if you call both methods or if you have a bunch of functions that call those methods you still just get true. Calling either method or any function that calls them is going to be slightly correlated with... (read more)
I'm curious about the basis on which you are assigning a probability of causality without a method like mendelian randomisation, or something that tries to assign a probability of an effect based on interpreting the biology like a coding of the output of something like SnpEff to an approximate probability of effect.
The logic of 30% of its effect based on 30% chance it's causal only seems like it will be pretty high variance and only work out over a pretty large number of edits. It is also assuming no unexpected effects of the edits to SNPs that are non-causal for whatever trait you are targeting but might do something else when edited.
Could you expand on what sense you have 'taken this into account' in your models? What are you expecting to achieve by editing non-causal SNPs?
The first paper I linked is about epistasic effects on the additivity of a QTLs for quantitative trait, specifically heading date in rice, so this is evidence for this sort of effect on such a trait.
The general problem is without a robust causal understanding of what an edit does it is very hard to predict what shorts of problem might arise from novel combinations of variants in a haplotype. That's just the nature of complex systems, a single incorrect base in the wrong place may have no effect... (read more)
There are a couple of major problems with naively intervening to edit sites associated with some phenotype in a GWAS or polygenic risk score.
The SNP itself is (usually) not causal
Genotyping arrays select SNPs the genotype of which is correlated with a region around the SNP, they are said to be in linkage with this region as this region tends to be inherited together when recombination happens in meiosis. This is a matter of degree and linkage scores allow thresholds to be set for how indicative a SNP is about the genotype a given region.
If it is not the SNP but rather something with which the SNP is in linkage that is causing
I have a reading list and recommendations for sources of ongoing news in the longevity/immortality/life extension space in the show notes for the recent special episode of my podcast where my co-host Michael and I discuss ageing and immortality. We are both biology PhDs, my background is in the epigenetics of ageing and Michael's bone stem cells.
https://www.xenothesis.com/53_xenogenesis_ageing_and_immortality_special/
I should add "Immune: a Journey into the Mysterious System that Keeps You Alive" to that list actually.
In particular from that list I recommend these for 'coming at biology from a physics perspective':
To clarify it's the ability to lock you're bootloader that I'm saying is better protection from 3rd parties not the propriety nature of many of the current locks. The HEADs tools for example which allows you to verify the integrity of your boot image in coreboot would be a FOSS alternative that provides analogous protection. Indeed it's not real security if it's not out there in the open for everyone to hammer with full knowledge of how it works and some nice big bug bounties (intentional or unintentional) on the other side to incentivise some scrutiny.
Thanks for the link. The problem of how to have a cryptographic root of trust for an uploaded person and how to maintain an on going state of trusted operation is a tricky one that I'm aware people have discussed. Though it's mostly well over my cryptography pay grade. The main point I was trying to get at was not primarily about uploaded brains. I'm using them as an anchor at the extreme end of a distribution that I'm arguing we are already on. The problems of being able to trust its own cognition that an uploaded brain has we are already beginning to experience in the aspects of our cognition that we... (read more)
cross-posted to pan narrans
especially if you want to upload your brain
In the limit condition freedom of compute is freedom of thought.
As we offload more of our cognition to our computational devices we expose a new threat surface for attacks on our ability to think free of malign or otherwise misaligned influence. The parties who control the computational systems to which you have outsourced your cognition have a vector by which to influence your thinking. This may be a problem for you if their interests are not aligned with your own as they can use this power to manipulate you in service of their goals and against your... (read 1286 more words →)
Let us represent our beliefs as nodes in a network. Most nodes in your network of beliefs have dependencies, they are connected to other beliefs the truth value of which they are contingent on.
Picture a subset of your network of beliefs, let us take a simplified section that looks like a tree, stripping away the complex interconnections to aid in visualization.
Beliefs B and C are predicated on belief A, beliefs D and E on belief B, and beliefs F and G on belief C. Thus belief A is need for beliefs B and C, belief B for D and E, and C for F and G. (see the figure)
The One: Apples... (read 686 more words →)
GeneSmith gave some more details about his background in this episode of the Bayesian Conspiracy podcast: https://www.thebayesianconspiracy.com/2025/02/231-superbabies-with-gene-smith/