To clear up some misunderstandings before HN's web developer crowd gets too excited and starts throwing around scientifically inaccurate speculations: - Accura

To clear up some misunderstandings before HN's web developer crowd gets too excited and starts throwing around scientifically inaccurate speculations: - Accurate and precise CRISPR-based, human non-germline in vivo cell editing at scale still has some ways to go. We are not at the stage (yet) where a couple injections will be able to completely rewrite your genome. Accuracy and precision has room for improvement. In vivo needs more research (the ethics concerns and controversies is a huge barrier for this). And finally scale, which I will address below. - A quick explanation of germline vs non-germline gene editing. Non-germline: change just the genes in the affected area. Germline: change the genes in the sex cells (or their product, the zygote) so that the change will be perpetuated. The Stanford professor's controversial editing of the Chinese twins was germline based. Non-germline is hard because you have many many cells and right now CRISPR is still not perfectly precise. Delivering CRISPR to every part of the organ/afflicted area is still not yet well understood. There was an article on HN a couple days ago on this. It was sensationalised and exaggerated but the point made is largely correct: https://news.ycombinator.com/item?id=25096386 https://news.ycombinator.com/item?id=25096386 https://news.ycombinator.com/item?id=25096982 https://news.ycombinator.com/item?id=25096982 - The technology that finally makes it to market may not be CRISPR at all. With the announcement two days ago by Deepmind, the field of proteomics, and by proxy biology, has been fundamentally changed. The impact to computational biology is akin to ImageNet overshadowing the Lisp/Prolog based expert systems, and their successors' decision trees. History has been written. The repercussions of that blog post is greater for humanity than the moon landing. You often see on HN people complaining how top minds and talent are now working on better ads systems and recognising cat photos instead of real hard tech. The cat photo recognition people just wrote their names in the biology textbooks of the future. Silicon valley loves anti-aging research. That Deep Mind blog post alone possibly added decades to our lifespan than any past effort by Aubrey De Grey et al. or the Methuselah Foundation. Biotech startups might actually be profitable now (hahaha)