jryb

Doors no, couch yes (if it fits). I wouldn’t get one unless you see value in having 80% of your home vacuumed once a day. For me that’s still a huge improvement and spending a few minutes spot vacuuming every two weeks or so is all I need to handle the corner cases.

No one will touch this guy with a ten foot pole. Nothing he did technically was novel - it was just that everyone who had the skills to edit an embryo was unwilling and uninterested in doing so. Having him as part of your organization basically broadcasts to the world that you’re going to be doing wildly unethical things. Not a great path to commercialization of any therapeutic.

I don’t understand how this achieves a higher density. Won’t taller towers cast larger shadows, thus requiring towers to be spaced further apart?

fwiw, upgrading from rx580 to rtx5070 solved all of my performance problems (both on windows and Linux) for a number of games.

I’m not so sure. When pharma companies are flush with cash they tend to get more experimental. Lilly’s gene editing group is one of the few that’s doing well (last I heard anyway) and they recently acquired Verve. I can’t imagine that would happen without GLP-1 profits bankrolling everything. Rare disease is effectively charity and the money has to come from somewhere.

You’re not seeing all the other candidate treatments that made things worse. If it just gives everyone a heart attack immediately the question would be, why didn’t you try this out on mice first?

Many misconceptions here, let's clear them up:

> if there are other genes between the ends that are cut

I think what you're saying is that if two sites on the same chromosome are cut, then everything in between is deleted. However, this isn't going to happen in practice. DNA repair systems will rejoin the cut DNA ends rapidly, just erroneously (with maybe a few dozen missing/incorrect bases typically). If the cut site is in the protein coding region, it will usually disrupt the sequence to make the protein nonfunctional. Sometimes this is the desired effect, but for most gene therapies you'll probably use base or prime editing, which don't create double strand breaks.

> we'd need to sequence the patient's genes...to make sure that any patterns don't appear anywhere else

While sequencing an individual patient's genome isn't going to happen in practice, the FDA does require gene editing companies to do in silico off-target prediction, where you scan the genome for sites that have similar sequences to the target. You then have to show that none of the off-targets are in dangerous regions (e.g. DNA repair genes), and also show experimentally whether those sites are cut at all (they usually aren't, fortunately, as there are thousands within reasonable thresholds).

The reason you don't need to sequence individual patients is because you just assume that any patient could have any variant that has ever been catalogued (there are databases with thousands of individuals and the differences between them and the reference genome). You then have to show that none of those variants could induce a new target in a dangerous region.

> then come up with an iterative process, probably using AI, to catalog and repair all major genetic disorders.

I don't know what AI would do for you here. Figuring out the change you need to make to revert a genetic disorder is trivial. The hard part is making it safe and effective, and proving to regulators that it's safe and effective.

> Then it's probably 5-10 years before gene editing is a solved problem.

Not even close. Ironically, while the technologies are pretty good in general, every edit requires a ton of engineering work. CRISPR systems are notoriously idiosyncratic - they might edit one target in 80% of cells, and 0% at another target, for no apparent reason. There are definitely open problems with base and prime editing, and those will probably get more-or-less solved in 5-10 years, but I'm reasonably sure there will be genetic disorders for which there is no treatment for decades.

It doesn't help that the one approved therapy isn't really making much money: https://www.biopharmadive.com/news/sickle-cell-gene-therapy-...

See also: https://blog.genesmindsmachines.com/p/we-still-cant-predict-...

If we're thinking about the same youtuber, I found that experimental design to be really poor. They said they were lactose intolerant as a child, but they didn't confirm that they still were (decades?) later. I was lactose intolerant until I was six and then it just resolved on its own (perhaps this wasn't even lactose intolerance but a reaction to something associated with lactose).

What they should have done was eat a pizza before the treatment, gotten sick, then taken the treatment and shown that the same pizza had no effect afterwards.

Good catch, thanks!

Many (most?) of these are achievable with neovim and tree-sitter (a plugin that gives you access to the AST), and surely many other editors. I have plugins installed right now that do several of the things that are mocked up here. Many more are done with virtual text and not color, but I don’t see why you couldn’t use highlighting instead.

I agree with the broader point of the article that color is underused, but the state of the art has moved way past what the author’s tools are currently configured to provide.

Not all statements should be interpreted literally.

The Alters

My approach is to understand the topic one level deeper than is needed to satisfy my immediate needs. It’s not always enough but it usually exposes any obvious traps you’d run into with only a surface level understanding, or at least lets you know if the thing really is too complex to not understand deeply and still succeed.

It is maddening, but you can just ask your doctor to prescribe it. There are plenty of ways for them to justify it.

mRNA is a natural molecule produced by every living organism. All it does it cause a protein to be made. Where's the nightmare?

Just one personal anecdote: I definitely find contradictions or gaps in my thinking/knowledge when I write. Finding and resolving those deficiencies is what I point to when I say "writing is thinking".

I take most of your points except the last one. The feedback would come in the form of publications, definitely from academia and to a lesser degree industry (admittedly a slow iteration time). Also just public discourse - there was no dearth of very specific, highly technical feedback for any of the releases of alphafold on twitter, for example.

But I can’t use this at all at work (a pharma company) because it would leak confidential information. So anything they learn from usage data is systematically excluding (the vast majority of?) people working on therapeutics.

Just inverting the canonical example fails: queen - woman + man = drone

I’d speculate they convinced themselves that their startup was fundamentally great and they just needed more time for it to attain its full potential. The fake users were just a way to show JPM the company they’d eventually have, so nobody was really going to lose (in their minds).

The problem is that biology is such a huge and complex field, and there's simply no way to make progress without incremental work like this that has no immediate payoff. To even contemplate whether something like this could cure cancer means that the article completely misrepresented its value.

I think the problem is that you're viewing things as either "cures for cancer", or "not cures for cancer". I would suggest instead framing things as, "how on Earth could we possibly cure cancer when human bodies have trillions of moving parts and we only understand half of them?" It's like trying to fix a broken car and not even knowing what internal combustion is.

I think it would help to explicitly reframe this question as: “where can we find the millions of dollars needed to pay for however many full time software engineers are needed to develop a modern browser?”

They emit water vapor, not liquid water. Gasoline-fueled cars emit roughly the same amount of water as a hydrogen-powered vehicle, so we already know this isn't an issue.

Morality doesn't stop applying just because you agreed to accept money in exchange for hurting people.

The sorting functionality seems to be broken.

I'm using something similar to Heisig, and I can already tell that while I can list all of the radicals and components in a character, I have no memory of their relative positions. I'm also not trying to learn them and I only using a pinyin input method, but I can't imagine really needing to be able to write by hand ever.

I used to, but it basically showed that no one ever gave away my email address to spammers, or at least if they did, the spam filter caught it. It's not worth it.

Yes, but while animals are a black box to some extent, the outcomes of the experiments are not. And you don't have to worry about whether your results are an artifact of your simulation.

Your instincts are good - if we could simulate people in silico we could basically understand and cure every disease - but the scale of such a simulation is literally (not figuratively!) astronomical. Biological systems are way, way, way more complex than they appear and our computers are (currently) hopelessly inadequate.

Suppose your fancy new robot is wildly successful and can let me examine 2-3 orders of magnitude more sequences - that's still an infinitesimal fraction of all possible proteins with the same function, and now my DNA synthesis and sequencing costs are also 2-3 orders of magnitude higher - that's really non-trivial, and given that your company isn't selling a lot of these robots (who even needs this scale?), they aren't going to be cheap either.

How do I justify spending all this money? I need some theory of why this search is going to give me anything other than incremental improvements in activity or whatever metric I care about, but rational design can only take me so far. Generative models aren't going to give me a step change in activity. Why am I confident that the set of proteins I'm testing have megabucks of potential?

So sure, limitations in automation are an obstacle to bigger scale, but we often can't use the scale that's already achievable. There's certainly room for improvement in the automation space, but unlocking scale is not the only problem you need to solve.

I just saw it being discussed in the wild, I didn't notice that it was from 2019.

I find the swift keyboard is better than the regular one, but good lord is the autocomplete terrible. It adds 's to words so often even when my finger never went close to the S key, it suggests "ang" as often as "and", and I'll often have something entered correctly, but then adding a word will cause the word three positions back to change. I could go on. I really don't get why it's so bad when my android from a decade ago basically always entered what I was thinking.