Yeah, this is actually a pretty great application for AI. It’s local, privacy-preserving and genuinely useful for an underserved demographic.
One of the most wholesome and actually useful applications for LLMs/CLIP that I’ve seen.
Yeah, this is actually a pretty great application for AI. It’s local, privacy-preserving and genuinely useful for an underserved demographic.
One of the most wholesome and actually useful applications for LLMs/CLIP that I’ve seen.
Ideally you want something that gracefully degrades.
So, my media library is hosted by Plex/Jellyfin and a bunch of complex firewall and reverse proxy stuff… And it’s replicated using Syncthing. But at the end of the day it’s on an external HDD that they can plug into a regular old laptop and browse on pretty much any OS.
Same story for old family photos (Photoprism, indexing a directory tree on a Synology NAS) and regular files (mostly just direct SMB mounts on the same NAS).
Backups are a bit more complex, but I also have fairly detailed disaster recovery plans that explain how to decrypt/restore backups and access admin functions, if I’m not available (in the grim scenario, dead - but also maybe just overseas or otherwise indisposed) when something bad happens.
Aside from that, I always make sure that all of all the selfhosting stuff in my family home is entirely separate from the network infra. No DNS, DHCP or anything else ever runs on my hosting infra.
It would be better to have this as a FUSE filesystem though - you mount it on an empty directory, point the tool at your unorganised data and let it run its indexing and LLM categorisation/labelling, and your files are resurfaced under the mountpoint without any potentially damaging changes to the original data.
The other option would be just generating a bunch of symlinks, but I personally feel a FUSE implementation would be cleaner.
It’s pretty clear that actually renaming the original files based on the output of an LLM is a bad idea though.
I don’t think it’s necessarily a bad thing that an AI got it wrong.
I think the bigger issue is why the AI model got it wrong. It got the diagnosis wrong because it is a language model and is fundamentally not fit for use as a diagnostic tool. Not even a screening/aid tool for physicians.
There are AI tools designed for medical diagnoses, and those are indeed a major value-add for patients and physicians.
Android still doesn’t have shake-to-undo. I use iOS and Android and switch between them regularly for work, and every time I typo something or accidentally delete a bunch of text on Android, it’s incredibly jarring to not have the undo capability.
Exactly. So the organisations creating and serving these models need to be clearer about the fact that they’re not general purpose intelligence, and are in fact contextual language generators.
I’ve seen demos of the models used as actual diagnostic aids, and they’re not LLMs (plus require a doctor to verify the result).
There are some very impressive AI/ML technologies that are already in use as part of existing medical software systems (think: a model that highlights suspicious areas on an MRI, or even suggests differential diagnoses). Further, other models have been built and demonstrated to perform extremely well on sample datasets.
Funnily enough, those systems aren’t using language models 🙄
(There is Google’s Med-PaLM, but I suspect it wasn’t very useful in practice, which is why we haven’t heard anything since the original announcement.)
It is quite terrifying that people think these unoriginal and inaccurate regurgitators of internet knowledge, with no concept of or heuristic for correctness… are somehow an authority on anything.
I know of at least one other case in my social network where GPT-4 identified a gas bubble in someone’s large bowel as “likely to be an aggressive malignancy.” Leading to said person fully expecting they’d be dead by July, when in fact they were perfectly healthy.
These things are not ready for primetime, and certainly not capable of doing the stuff that most people think they are.
The misinformation is causing real harm.
Ohh, my bad! I thought the person you were replying to was asking about Gitea. Yeah, Forgejo seems truly free and also looks like it has a strong governance structure that is likely to keep things that way.
This sadly isn’t true anymore - they now have Gitea Enterprise, which contains additional features not available in the open source version.
From here:
Don’t use Gitea, use Forgejo - it’s a hard fork of Gitea after Gitea became a for-profit venture (and started gating their features behind a paywall).
Codeberg has switched to Forgejo as well.
Also, there’s some promising progress being made towards ActivityPub federation in Forgejo! Imagine a world where you can comment on issues and send/receive pull requests on other people’s projects, all from the comfort of a small homeserver.
I saw a job posting for Senior Software Engineer position at a large tech company (not Big Tech, but high profile and widely known) which required candidates to have “an excellent academic track record, including in high school.” A lot of these requirements feel deliberately arbitrary, and like an effort to thin the herd rather than filter for good candidates.
Songs and albums that I’ve uploaded from my own collection have disappeared from Apple Music, despite my physically owning them on CD and Apple advertising the ability to store my CD rips in the cloud.
It’s unacceptable. I’m still on Apple Music for now, but moving my music library to Jellyfin looks more appealing by the day.
Agreed, and it could definitely make such an assumption. The other aspect that I don’t really get is… if a superintelligent entity were to eventuate, why would it care?
We’re going to be nothing but bugs to it. It’s not likely to be of any consequence to that entity whether or not I expected/want it to exist.
The anthropomorphising going on with the AI hype is just crazy.
Yeah bro but eXpOnEnTiAl ImProVeMeNt bro!
And haven’t you heard of Roko’s basilisk? Better be careful what you say on the cybernets, lest our AGI/ASI overlords of 2026 take a disliking to your commentary regarding their eventual supremacy!
Excuse me while I go back to mining Dogecoin until I can buy enough NFTs to make Elon or Sam Altman notice me.
/s
Idk… in theory they probably don’t need to store a full copy of the page for indexing, and could move to a more data-efficient format if they do. Also, not serving it means they don’t need to replicate the data to as many serving regions.
But I’m just speculating here. Don’t know how the indexing/crawling process works at Google’s scale.
This is probably an attempt to save money on storage costs. Expect cloud storage pricing from Google to continue to rise as they reallocate spending towards ML hardware accelerators.
Never been happier to have a proper NAS setup with offsite backup 🙃
Power management is going to be a huge emerging issue with the deployment of transformer model inference to the edge.
I foresee some backpedaling from this idea that “one model can do everything”. LLMs have their place, but sometimes a good old LSTM or CNN is a better choice.