A website dedicated to promoting LASIK says the surgery “boasts a success rate of at least 96%”, and a satisfaction rate of 95%. “Long-term or chronic dry eye affects only a small minority (about 4%)” while cases requiring follow-up treatments are “typically under 5%”.
These numbers have never been particularly reassuring to me.
I've recently been test driving SPR[1] which is a security-oriented distro for Wi-Fi routers. The team behind it are serious about Wi-Fi security and have a research lab[2] that has been credited with several CVEs in the likes of Apple's network stack. The headline feature is strong device isolation for semi-trusted guest and home automation devices, and the software stack is based around containerized and audited Go daemons.
It ran pretty well for me as a travel router I cobbled together from a Raspberry Pi and Netgear A7500 USB dongle for a stay in a short-term rental where the infrastructure network was shared with other units. More recently I have been trialing their CM5-based model with Wi-Fi 7 and 2.5GbE PoE for use as primary home Wi-Fi.
I've been using Podman on Mac and Linux for 3 years, and unfortunately, I have found this to be perennially true. I am willing to doggedly pursue the root cause and file bugs, but for many people it will just seem broken.
Most recently: Netavark doesn't match Docker's behavior with accepting broadcast traffic on a published port.
I've successfully tinkered with USB/IP with Apple containers, but it does require loading a custom kernel (which they make pretty easy, thankfully). On the host side, macOS also doesn't make it easy to unload a driver that attaches automatically.
I have only seen The Girl with the Dragon Tattoo (2011) once, but fifteen years on I distinctly remember a scene where Daniel Craig is trying to use a Mac and accidentally drags Safari off the Dock. https://www.youtube.com/watch?v=W84AhBMRNOY#t=1m25s
Apple Vision Pro's hand tracking was first alluded to in a section of their first machine learning research publication. It was about using GANs to add realistic sensor noise to synthetic datasets. The bulk of the article is about eye tracking.
I appreciate that the post was short and to the point, but it is, like so much content submitted to HN now, heavily filtered through an LLM's voice, if not completely written by one.
> Writing things down generally helps me build my own clarity and I hope to get the same out of this particular write up. Hopefully I achieve this clarity sooner rather than later.
There exist many underwater vehicles that can withstand ocean pressures. The REMUS 6000 for example can reach depths of 6000m.
As the article describes, these are gliders:
> A glider is a small robot that slowly changes its buoyancy, becoming slightly heavier to sink and lighter to rise.
It doesn’t need battery power to endlessly spin a prop. With little energy expenditure it can inflate or deflate a bladder; changing volume changes buoyancy and therefore vertical motion in the water column. The vehicle’s design allows it to “soar” as it does so. The tradeoff is control.
There was a charming reality TV show in the 2000s called "Airline"[0] in which a camera crew followed around Southwest ground operations, cabin crew, and passengers. There was a British series that aired around the same time about Heathrow, unsurprisingly called "Airport".
In high school I had the TI-89 Titanium. Like everyone here, I got into programming it using some USB adapter I could attach to my iMac G5 and the TI Connect app[0].
One day, vexed by something, I vented my frustration by composing a profanity-laced rant into the Feedback window of the TI Connect app. (I don't recall the proximate cause, but I remember complaining that the product itself, which is still $110 today, is a total ripoff.)
I was certainly surprised when the (sole?) TI Connect developer responded by e-mail taking umbrage at my complaints.
It takes more like 10 seconds. For a large range of height and weight inputs crossed with all option combinations, you could precompute ~10M measurements and return results basically instantly.
> The iPad remains my favorite form factor to use in lots of my day but Apple never invested in killer app software optimized for it.
Apple doesn't received much credit for making iPhoto for iPad back in 2012 (https://www.macrumors.com/2012/03/07/apple-launches-iphoto-f...), or more recently Final Cut Pro and Logic Pro. I think they really have invested in building pro software for iPads, probably on the order of millions of dollars, less for the vanishingly small segments of their user base but to make the case that the platform can be used for serious work.
The problem though is that the platform itself creates friction compared to macOS that, even at the best of times, makes the user at least slightly less productive. So I can't imagine myself picking up an iPad to do any actual creative work.
Not to mention the best-in-class keyboard cases, over-engineered stylus, mouse support, multitasking support, and on and on. It almost seems desperate that they keep trying to find "the thing" to crack this problem.
Curiously, the accounts whose comments/articles I'm most confident about being AI-written tend to focus heavily on AI, yet deny using it themselves.
I prompted Claude 5 times with a simple "What do you think about <blog link>?" and the text it generated was remarkably similar. In fact in every response it used the adjective "genuinely", as in your "genuinely novel", which is the LLM glazing that initially struck me.
Claude goes on to hit several of the same notes, in the same tone, basically summarizing bits of the article (using `HTTP_PROXY/HTTPS_PROXY` as a compound; referencing iptables for containers, structured JSON escaping, request size caps). It used the phrase "blast radius" and a similar three-point attack sequence in one response.
I am confident you are using LLMs to write—the Grith.ai blog is basically entirely LLM slop. Please stop posting it here.
I'm willing to wager that your comment was generated from the body of the article plus a prompt to work in an advertisement for your product, which gets a mention in nearly every comment you make (and every submission you make, sometimes on a daily basis).
These numbers have never been particularly reassuring to me.