posted in Asklemmy

How all do you use AI/ML in life? Especially offline uses

Speech to text, Voice typing is cool.
F-droid lists opensource apps that support Whisper and Vosk models.
Futo voice is not opensource, but is source available.
It’s good for English. For my mother tongue, Malayalam, the support seems to be underdeveloped currently.
Handy seems to be good for Windows, but have not used it much.

Then for Translations: f-droid.org/packages/dev.davidv.translator/
Using Mozilla’s translation Models. A good enough offline and Open source alternative to GTranslate.

Are there other cool uses of offline ML/AI that you know?

f-droid.orgOffline Translator | F-Droid - Free and Open Source Android App RepositoryOn-device translation of text, images and pdf/odt files, with TTS
Edited ⁨⁨Sep⁩ ⁨7⁩, ⁨2026⁩, ⁨16:07⁩⁩enPage

Replying to @⁨1Malayali@lemmy.ml⁩

My spam filter on my email server. Autocorrect on Heliboard. I think that’s it. Luckily I picked up English at a young age so I don’t need it for translation.

Also for people having a kneejerk reaction, “AI” and “ML” as terms long predate the current slopwave. The ML I am talking about in the previous paragraph is not genAI, it is the kind of ML to classify things (emails into spam/ham, words into correct/incorrect), that you can feed training data to improve its accuracy rate.

Replying to @⁨Bluegrass_Addict@lemmy.ca⁩

Machine Learning (and even Large Language Models) do have genuine use cases they excel at and are probably more efficient at.

One good example is protein folding. ML transformed biomedical research by basically solving the protein folding problem in minutes on a GPU instead of essentially trying to brute force a solution that was millions to tens of millions times more complex. I’m glossing over details, but it’s mind blowing how much better (especially when you consider resource usage) how much better ML is in this case. Think $1 and minutes vs $100000+ and years… for a single protein.

The problem is using LLMs and Generative AI for things they seem good at but actually aren’t.

Replying to @⁨RoddyStiggs@lemmy.blahaj.zone⁩

Technology cannot be unethical, right?
It’s use/application, safety regulation aspects, ownership etc. would be the focus, right?

The corporations who supports copyrights are stealing data(from others and other corporations) for training AI.
By calling the technology unethical, we are letting them off the hook by making it vague and on the technology, rather that their decision to not provide credit or remuneration for the original data creators, right?

Replying to @⁨1Malayali@lemmy.ml⁩

I use it to generate little bash and python scripts for mundane tasks, random ideas I don’t have a good starting point for, or boilerplate code I don’t have the energy to write manually. Or also to decipher cryptic error messages and logs. Nothing that I publish though, just all testing and personal scripts.

I do this with models running locally on my gpu. 14B parameters is surprisingly decent and fast enough for a 16 GB slot-powered workstation model.

For fun, since the model is local, I also toss in some excerpts of my writing, see what it can glean from my style and vocabulary, something I’d never do with an LLM hosted by someone else for obvious reasons.

Replying to @⁨1Malayali@lemmy.ml⁩

Occasionally I’ll spin it up on my local machine and have a chat with it about technical stuff.

Sometimes it’s fun just running scenarios with it because it’s novel. Or I use duck.ai kinda like an instruction manual you can ask things to. Never ever on anything with actual stakes.

I do find it’s good at deciphering Linux stuff, and I do end up actually learning rather than just blindly trusting whatever it spits out.

I don’t want chatbots to replace friends asking each other things or discussing technical topics on forums though. That would be sad. But sometimes it helps with those simple “been asked a thousand times” issues where I’d get bogged down reading 15 tabs and still not be certain what the best move could be.

So I guess I find it good at distilling existing information.

Using it to “create” anything though? As an artist and game dev, I find the thought genuinely disgusting. I suck at coding, but I’m not selling out my coder brethren and sistren to a machine, just like I’d be disappointed in them doing the same to me as an artist.

Replying to @⁨1Malayali@lemmy.ml⁩

I was always fascinated by declarative Linux distros like NixOS and tiling managers, but the thing that always stopped me is it’s time consume aspect. Everything had to be written by hand, et cetera.

Now it’s as simple as “Hey buddy ChatGPT, install this and that, make these keyboard shortcuts, turn off logs on startup, switch DM, debug this”. Some can say that’s not a true way - punch me, it’s the most easy way to configure your OS.