This was perhaps an understandable viewpoint to hold in June when the best publicly available IQ predictor from the EA4 study only correlated with actual IQ at .3 in the general population (and less within family, which is what matters for embryo selection).

I happened to have spoken with some of the people from Herasight at the time and knew they had a predictor that performed quite a bit better than what was publicly available, which is where my optimism was coming from.

In October they finally published their validation white paper so now I can point to something other than private conversations to show you really can get as big of a boost as claimed.

Some people are still skeptical. Sasha Gusev for example has claimed that Herasight applied a “fudge factor” to get to 20% of variance explained by adjusting adjusting for the noisiness of the UKBB and ABCD cohorts. This is based on the fact that their raw predictor explained 13.7% of the within-family variance, and they applied an "adjustment factor" to that based on the fact that the test they validated on only has a test-retest correlation of .61.

I don't find the critique all that convincing, though my knowledge in the reliability of different psychometric methods is still pretty limited so take my opinion with a grain of salt. It's well known that UKBB's fluid intelligence test is pretty noisy, and the method they used to correct for that (disattenuation) seems pretty bog-standard.

They also published a follow-up in which they used another method, latent variable modeling, which produced similar results.

All that being said, it would be better if there were third-party benchmarks like we have in the AI field to evaluate the relative strength of all these different predictors.

I think it's probably about time to create or fund an org to do this kind of thing. We need something like METR or MLPerf for genetic predictors. No such benchmarks exist right now.

This is actually a real problem. No dataset exists right now that we can guarantee hasn't been used in the training of these models. And while I basically believe that most of these companies have done their evaluations honestly (with the possible exception of Nucleus), relying on companies honestly reporting predictor performance when they have an economic incentive to exaggerate or cheat is not ideal.

I think you could actuallly start out with an incredibly small dataset. Even just 100 samples would be enough to make a binary "bullshit" or "plausible" validation set on continuous value predictors like height or IQ.

Yes, please DM!

I'm thinking about writing a practical guide to having polygenically screened children (AKA superbabies) in 2025. You can now increase your kids IQ by about 4-10 points and/or decrease their risk of some pretty serious diseases by doing IVF and picking an embryo with better genetic predispositions.

There's a bunch of little shit almost no one knows that can have a pretty significant impact on the success rates of the process like how to find a good clinic, what kinds of questions to ask your physician, how to get meds cheaply, how to get the most euploid embryos per dollar, which polygenic embryo selection company to pick etc.

Would anyone find this useful?

Do you think head transplants on to repeatedly cloned bodies could work as life extension? Even without genetic improvements to increase longevity, I can imagine switching bodies every 20-50 years becoming mundane with nearly modern surgical techniques provided we can reconnect the nervous system.

Yes, I think head transplants could extend lifespan pretty significantly if you can do them safely (they're currently super dangerous), but I don't think it would extend lifespan indefinitely. The brain itself ages, so unless you have a means of gradually replacing brain tissue a la Jean Hebert, you're not going to get to indefinite lifespan extension.

Related to this, do you think parabiosis would work without all the body switching?

I mean... would you WANT your circulatory system hooked up to that of someone else? Sounds gross, weird and extremely inconvenient to me, even if you're the one benefitting.

I can see blood transfusions if you can make artificial blood. But I can't see parabiosis ever being a thing unless it's in some exceptional circumstances.

There's another interesting question related to this one which has to do with creating a gene edited clone of yourself.

If we can make an embryo from one of your stem cells, we could potentially do substantial editing of it to enhance it in various ways (perhaps to reduce disease risk or increase intelligence).

How many edits would one need to make before it is no longer really a clone of you?

What if instead we grew a genetically enhanced replacement body for you with no knee issues and better cardiovascular performance? Are you still you with a new body?

There are all kinds of interesting questions that arise with sufficiently powerful biotech. Most people don't spend much time thining about them because the tech to make them relevant is a ways off.

I'd appreciate if you could provide links to "clear evidence of its writing style across all of these surfaces, and the entire.. vibe of the campaign feels like it was completely synthesized by 4o"

I understand it may be hard to definitively show this but anything you can show would be helpful.

It's fine, I wouldn't expect you to read all the comment.

There are only a few hundred IQ-related genes, and they're found through a correlation in over 240k people, so it's not necessary that you can just edit all these genes to set them on a "more IQ" version in a specific genome, and get maximum IQ. www.southampton.ac.uk/news/2018/03/genes-intelligence.page

There have been quite a few more genetic variants linked to IQ since this study was published in 2018. Herasight has the best IQ predictor I know of, which can explain over twice as much variance as the best predictors we had in 2018.

Of course it's correct that in most cases we aren't highly certain which one of a cluster of variants is actually causing the effect we observe.

But we don't need to know. We just need reasonably good odds. Then we can edit variants with the highest combined probability of causality * effect size. That's how we came up with the graph in the post: we didn't falsely assume we know which of the variants are causal.

By editing more nucleotide sequences, you will only increase the risks of breaking the genome's reading, replication, expression and other mechanisms, killing the cell. DNA isn't merely a line of text that encodes proteins, it's full of commands for enzymes to work with it. As a tip of the iceberg: there are 20k genes that encode 100-1000k proteins in human body, because 1 gene contains several exons (and introns), which, during transcription, are combined in different ways to encode several proteins.

Yes, that's true if you're doing single shot editing, which is one of the limitations for the kind of germline engineering we're currently pursuing. But the more advanced editing protocols don't rely on single shot editing. They use iterated CRISPR, as explained in the post, and that in turn uses multiple rounds of editing. In each round, you're selecting cells that not only received many edits, but didn't contain any deal-breaker mutations.

So at least in theory, there is no reason why adding more edits would break essential genomic functions.

In practice, there are a lot of headaches here: base editors result in bystander edits, prime editors result in indels, and each cell division carries a certain risk of copying errors and chromosomal abnormalities. None of these are insurmountable, but overcoming them will require a decent bit of engineering.

Do you have a link to the Habr article? I'm curious to read what people are saying.

Subtle dig at Balaji from Bannon? Interesting.

Anyone have insights into whether this is a genuine offer that could be taken up by members of the administration if they have the right attitude vs a simple power play by China to try to get more support from potential allies?

Trying to gauge how cynical to be here.

As someone who works in genetics and has been told for years he is a "eugenicist" who doesn't care about minorities, I understand your pain.

It's just part of the tax we have to pay for doing something that isn't the same as everyone else.

If you continue down this path, it will get easier to deal with these sorts of criticisms over time. You'll develop little mental techniques that make these interactions less painful. You'll find friends who go through the same thing. And the sheer repetitiveness will make these criticisms less emotionally difficult.

And I hope you do continue because the work you're doing is very important. When new technology causes some kind of change, people look around for the nearest narrative that suits their biases. The narratives in leftist spaces right now are insane. AI is not a concern because it uses too much water. It's not a concern because it is biased against minorities (if anything it is a little biased in favor of them!)

There is one narrative that I think would play well in leftist spaces which comes pretty close to the truth, and isn't yet popular:

AI companies are risking all of our lives in a race for profits

Simply getting this idea out there and more broadly known in leftist spaces is incredibly valuable work.

So I hope you keep going.