I don't really understand what's the point here, other than a somewhat inserting playing with LLMs. What does this tell us that's in any way applicable or points to further research? Genuinely asking

Regarding tiny packages, I don't think they affect the size of shipped bundle at all. They only bloat your local dev environment.

Bloat is mostly added by package authors, not website authors. And they can't know who's running it and can't look at the metrics. I doubt many website authors directly use isEven or polyfills.

What's wrong with a well protected VM? Especially compared to something where the security selling point is "no one uses it" (according to your argument; I don't know how secure this actually is)

Nothing, but "there are already working options" does not necessarily mean we shouldn't try new (and sometimes weird) things

Yeah but GP was answering to a comment saying "you don't want to run code in a well protected VM". Which is of course complete non sense to say and GP was right to question it.

GP says "You don't want to just run that code in ... even a very well protected VM." Why?

Because unless you can fund several teams - kernel, firmware(bios,etc), GPU drivers, qemu, KVM, extra hardening(eg. qemu runs under something like bpfilter) + a red team, security through obscurity is cheaper. The attack surface area is just too large.

What is this "security through obscurity" you're talking about? We're talking about running linux in a VM running in a browser. That has just as much attack surface (and in some ways, more) as running linux in a hypervisor.

Sure, by your own argument, you should somehow increase the price of people telling other people what to avoid spending money on

Regarding safety, no benchmark showed 0% misalignment. The best we had was "safest model so far" marketing speech.

Regarding predicting the future (in general, but also around AI), I'm not sure why would anyone think anything is certain, or why would you trust anyone who thinks that.

Humanity is a complex system which doesn't always have predictable output given some input (like AI advancing). And here even the input is very uncertain (we may reach "AGI" in 2 years or in 100).

I guess that it generally has 50/50 chance of drive/walk, but some prompts nudge it toward one or the other.

Btw explanations don't matter that much. Since it writes the answer first, the only thing that matters is what it will decide for the first token. If first token is "walk" (or "wa" or however it's split), it has no choice but to make up an explanation to defend the answer.

If I had to choose between a large organization and a single person vibe coded app, I'd choose large organization.

Can one solution be always doing two scans, N months apart, before drawing any conclusions (excluding things that can be reliably detected from a single scan)? Initial scan could affect N (if you find something potentially aggressive, you can schedule the second scan sooner). And then do a follow up every M years.

That should exclude benign or very slowing growing things

The question is how can you know if it needs treatment or not. I guess you either need to do a biopsy, or check if it's grown after N months (leaving patient scared and anxious during that time). Neither are great if most cases end up not needing treatment.

If the test provides you zero information about whether it needs treating then it was never a useful test. Presumably it's more like "there's a X% chance this needs treatment". In which case you just set reasonable thresholds for X. E.g. if it's 5% you monitor it, 10% you do a biopsy, 70% you operate, etc.

This is much more sensible than just not testing at all and letting people die from cancer.

> leaving patient scared and anxious during that time

This seems to be the actual motivation. We don't want to scare people with test results so we're just not going to test them. I think that should be up to the patient.

> This is much more sensible than just not testing at all and letting people die from cancer.

This is not what happens. You're assuming that if the cancer does not get detected by the screening then it never gets detected. What actually happens is that the test gives information that might actually be redundant and obtainable in less risky way. What the studies are showing is that waiting until there are other, more specific signs and symptoms of the prostate cancer results in the same survival rates.

Interesting. Do you have a source for that?

See https://pubmed.ncbi.nlm.nih.gov/38926075/. I was not aware of the ERSPC which came out late last year and gives better outcomes for screening, but overall the evidence is not super clear yet. There are possibly certain groups that can benefit from PSA screening more than others. Also, modern, more effective treatments might allow for later diagnosis with the same clinical results.