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:
https://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?
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mostly translation and making audio books
Thank you. Which all apps/models do you use?
no need for any of that stuff for me, so i don’t use it
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.
Thank you.
There seem to be offline models for many languages other than English too.I agree. People need to focus on the AI ownership aspect more. Should it not come under public control or oversight?
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.
It’s by no means new, but I’ve found OCR to be useful.
Thank you.
Translator has an OCR option. I currently use it for OCR.
Before that: https://f-droid.org/packages/io.github.subhamtyagi.ocr/
I just don’t, and wont
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.
Why? Opensource AI is good if it is the corporate ownership and data safety aspect, right?
Why use Google translate when you can use offline opensource models to get translation? Why send your data to Google or some other company?
Also, you don’t need internet connectivity for offline models.
I just like talking to Gemini once in a while to sort out all the thoughts in my head and keep me from indulging in lingering depression spikes.
Use duck.ai. at least your mental state records will not be used against you later.
