Somewhat unrelated to the main point of your post, but; How close are you to solving the wanting-to-look-good problem?
I run a startup in a completely different industry, and we've invested significant resources in trying to get an LLM to interact with a customer, explain and make dynamic recommendations based on their preferences. This is a more high-touch business, so traditionally this was done by a human operator. The major problem we've encountered is that it's almost impossible to have an LLM to admit ignorance when it doesn't have the information. It's not outright hallucinating, so much as deliberately misinterpreting instructions so it can give us a substantial answer, whether or not one is warranted.
We've put a lot of resources in this, and it's reached the point where I'm thinking of winding down the entire project. I'm of the opinion that it's not possible with current models, and I don't want to gamble any more resources on a new model that solves the problem for us. AI was never our core competency, and what we do in a more traditional space definitely works, so it's not like we'd be pivoting to a completely untested idea like most LLM-wrapper startups would have to do.
I thought I'd ask here, since if the problem is definitely solvable for you with current models, I know it's a problem with our approach and/or team. Right now we might be banging our heads against a wall, hoping it will fall, when it's really the cliffside of a mountain range a hundred kilometers thick.
I'm a layman, but the "Hulk Sperm" method seems the most plausible EC-bypass method to me, and EC-bypass generally seems a more plausible route than EC-making. After reading the paper, it seems like any of the routes to EC-making seem either speculative, or very prone to failure (while also being hard to verify as a failure).
an issue with spermatogonial transplant into testicles is that GV (e.g. edited) spermatogonia are likely to be stressed and imperfectly maintained, and therefore are likely to be outcompeted by normal spermatogonia and die out
If the problem is a concern with competitiveness after re-transplantation, is there a way to create an environment where the stressed spermatogonia has either reduced competition, or is more competitive relative to its unedited counterparts?
Off the top of my head this might look like locally "sterilizing" just the spermatogonia tissue after a biopsy somehow, without damaging the machinery that leads to functional spermatozoon development and paternal imprinting. I'm not sure if this sort of targeted wiping is possible though, but at least with two testicles, the option of sterilizing one from spermatogonia tissue wouldn't necessarily lead to complete sterilization. Or even if our only option here was complete spermatogonia sterilization, sperm preservation is relatively easy, so it still might be tolerable.
Alternatively, rather than just editing in a fluorescent reporter, you might also edit in a gene that makes the edited sperm more competitive in an environment that can be artificially induced in vivo. With just a fluorescent reporter, such a change arising naturally would naturally lead to the sperm being outcompeted and dying out (or if it as a completely neutral adaptation maybe not?), but if we induce conditions that are more favorable to spermatogonia with a specific tolerance induced by an inserted gene, they may have enough of a competitive advantage to persist in meaningful numbers. Off the top of my head I would consider higher temperature tolerance (with higher temperatures induced with a willy-warmer or something), or perhaps resistance to a chemical that's normally harmful to spermatozoon? No idea what this could be though.
Also, would a fluorescent reporter gene edited into spermatogonia and present in spermatozoon persist into the zygote, and therefore into all the descended cells of the eventual mature organism? I think it would be hilarious and incredibly fitting if a side effect of making supermen is that they literally glow.
Don't prediction markets also serve as a tool for actually valuing a prediction? Without a clear metric to judge the likelihood of a prediction at the time it was made (as is the case with these one-off real world predictions like elections or what a politician will do), I'm liable to consider the guy who predicted the sun will come up tomorrow, and the guy who predicted the market will drop 8% last week as having an equal success rate.
We need something to judge a prediction against, otherwise people would just go for easy predictions that might sound complicated in hindsight, and when they get them right most of the time, tout their "impressive" prediction record. If we can instead say "The market was already predicting this was going to happen with a 95% certainty when you predicted it", we can know their prediction wasn't at all unordinary, or valuable. Likewise, if the market predicted something with a lower certainty, say 50%, and our predictor predicted with a 95% certainty, and was right, and this happened consistently, we could consider their predictions as more valuable than chance, with high alpha.
Maybe there's some political commentator out there who analyzes Trump's claims and expectations clearly, assigns accurate probabilities better than the market (and bets on them), then we can choose to rely on that commenter in the future as far as predicting Trump's actions, "beating" the market. We couldn't find that person without the market in the first place, so even if the market itself doesn't communicate much information about the underlying probability, it can communicate information about who is better than the market at estimating it.