i personally have pushed back on every “infinite scrolling” feature request from product designers. first, you think you need it; you don’t. second, you think it’s just so nifty! it isn’t. oh is your content is dynamically generated? what was wrong with Reddit’s pager that launched that site into popularity?

it’s unnecessary complexity that hides information from the user, makes API calls (which are, spoilers, paginated) more complicated, can cause the obvious memory/resource consumption issues, and just generally disempowers the user. which i guess on a social media app is the point. but totally counter to the goals of a fleet management system lol

“Suggesting”

sure, there’s reason to be cynical, but i don’t think handing society to fascists out of bleak pessimism is the way i want to live my life.

i guess in these situations i think of my aunt, who is in her 80s. she has an iPhone. should she buy a NAS and host Immich? i don’t think “make backups” is the simple advice it appears to be for the vast majority of people

i think it’s easy to make comments like this from the peanut gallery, with the benefit of hindsight and a self-selected group of users who will agree. but Apple should be legally obligated to address this. the solution can’t be “this idiot didn’t spend his nights and weekends doing 3-tier backups and high availability infrastructure diversity!”; that’s not scalable. if we just accept that companies can do this, they will continue to. but this has been on the front page of HackerNews. it’ll probably make it to Tim Apple’s desk eventually, so we’ll see what shakes out.

i think the alternative is to use grep args. but ya know i’m living in the future using nushell’s open command and ripgrep so the argument is just kinda adorable

as someone who used to work on “expert models” i’m excited that not everyone has abandoned them for “what if we just had a model that knows everything (that doesn’t exist) and costs a billion dollars to run”

he’s been salty about this for years now and frustrated at companies throwing training and compute scaling at LLMs hoping for another emergent breakthrough like GPT-3. i believe he’s the one that really tried to push the Llama models toward multimodality

i guess the point that’s being missed is that when i say “hard” i mean practically impossible

my point is that it’s hard to program someone’s subjective, if written in whatever form of legalese, point of view into a detection system, especially when those same detection systems can be used to great effect to train systems to bypass them. any such detection system would likely be an “AI” in the same way the ones they ban are and would be similarly prone to mistakes and to reflecting the values of the company (read: Jack Dorsey) rather than enforcing any objective ethical boundary.

but what are the criteria? just because you think you have a handle on it doesn’t mean everyone else does or even shares your conclusion. and there’s no metric here i can measure, to for example block it from my platform.

what about the neural networks that power the DSP modules in all modern cell phones cameras? does a neural network filter that generates a 3D mesh or rather imposes a 3D projection, eg putting dog ears on yourself or Memojis, count? what if i record a real video and have Gemini/Veo/whatever edit the white balance? i don’t think it’s as cut and dry as most people think

it’s already the case that the distinction between what’s “AI” and what isn’t is a subjective, aesthetic difference and not a technical one

pretty sure it’s SteamOS, an Arch Linux derivative, on a fairly popular Snapdragon platform. probably not too difficult to hack on it.

there are some directories in my machines i consider ephemeral. Downloads and ~/temp should be able to be deleted with no real consequences

i’d say so. i was a professional Android dev for years, and security and privacy are definitely one of the reasons i prefer iOS. i don’t have time to play with my phone so much for my personal device. Apple is the lesser of 2 evils since their business model doesn’t depend on this kind of tracking (even if they do it as well albeit to a lesser extent)

but LLMs do represent a significant technological leap forward. i also share the skepticism that we haven’t “cracked AGI” and that a lot of these products are dumb. i think another comment made a better analogy to the dotcom bubble.

ETA: i’ve been working in ML engineering since 2019, so i can sometimes forget most people didn’t even hear about this hype train until ChatGPT, but i assure you inference hardware and dumb products were picking up steam even then (Tesla FSD being a classic example).

i know it’s popular to be very dismissive, but a lot of “AI” has already been integrated into normal workflows. AI autocomplete in development text editors, software keyboards, and question asking bots isn’t going away. speech-to-text, “smart eraser”, subject classification, signal processing kernels like DLSS and frame generation, and so many more will be with us and improving for a long time. Transformers, machine learning optimized chips, and other ML fields are going to be with us for a long time. the comparison to NFTs is either angst or misunderstanding.

nushell :P

i don’t know the full nature of the exploit, but zlib has an exploitable integer overflow via the MiniZip project. even though our images don’t use that project.

https://github.com/madler/zlib/issues/868