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Like if I type "I have two appl.." for example, often it will suggest "apple" singular instead of plural. Just a small example, but it is really bad at predicting which variant of a word should come after the previous

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[-] 0x4E4F@sh.itjust.works 118 points 11 months ago

Phones don't use LLM for predictive text. The algos are a lot less complex on phones.

[-] Knusper@feddit.de 18 points 11 months ago

I guess, the real question is: Could we be using (simplistic) LLMs on a phone for predictive text?

There's some LLMs that can be run offline and which maybe wouldn't use enormous amounts of battery. But I don't know how good the quality of those is...

[-] ashe@lemmy.starless.one 45 points 11 months ago* (last edited 11 months ago)

You can run an LLM on a phone (tried it myself once, with llama.cpp), but even on the simplest model I could find it was doing maybe one word every few seconds while using up 100% of the CPU. The quality is terrible, and your battery wouldn't last an hour.

[-] astraeus@programming.dev 3 points 11 months ago

Does the AI processing have to be performed locally or constantly active?

[-] EatYouWell@lemmy.world 15 points 11 months ago

No, but you open up a can of worms from a security aspect if you send it out to be processed.

[-] Scubus@sh.itjust.works 7 points 11 months ago

I'm sure every phone having a keylogger won't end badly

[-] Zippy@lemmy.world 3 points 11 months ago
[-] bassomitron@lemmy.world 15 points 11 months ago* (last edited 11 months ago)

The kind of local/offline LLMs that would work on your phone would not be very good quality. There's been amazing progress in quantization of LLMs to get them working on weaker GPUs with lower VRAM and CPUs, so maybe it'll occur, but I'm not an expert.

I also don't foresee them linking it up to a cloud-based LLM as that'd be a shit load of queries and extremely expensive.

[-] astraeus@programming.dev 1 points 11 months ago* (last edited 11 months ago)

OpenAI is probably already handling a significant amount of queries, I think for daily use the LLM should simply initialize a word map based on user history and then update it semi-occasionally, like once a week or two. Most people don’t drastically change their vocabulary in the course of a few weeks

[-] EatYouWell@lemmy.world 1 points 11 months ago

We're talking about orders of magnitude more queries if we start offloading predective text like that.

[-] Mr_Blott@lemmy.world 6 points 11 months ago

That was my next question, thanks!

Didn't think of battery use, makes sense

[-] SpooksMcDoots@mander.xyz 6 points 11 months ago

Openhermes 2.5 Mistral 7b competes with LLMs that require 10x the resources. You could try it out on your phone.

[-] Munkisquisher@lemmy.nz 5 points 11 months ago

A pre trained model isn't going to learn how you type the more you use it. Though with Microsoft owning SwiftKey, I imagine they will try it soon

[-] SidewaysHighways@lemmy.world 5 points 11 months ago

I was so heartbroken when I found out that Microsoft purchased Swiftkey. It was my favorite. Is there any way to still use it without Microsoft involved? Lawdhammercy

[-] neptune@dmv.social 4 points 11 months ago

I think apple has pitched this for a future iPhone, yes.

[-] squaresinger@feddit.de 3 points 11 months ago

They'll probably have to offload that to a server farm in real time. That's not gonna be easy.

[-] 0x4E4F@sh.itjust.works 0 points 11 months ago

I guess... why not... but the db is probably huge, like in the hundreds of GB (maybe even TB... who knows), can't run that offline.

[-] Arthur@literature.cafe 12 points 11 months ago

iOS 17 uses a small gpt-2 based model for predictive text.

[-] 0x4E4F@sh.itjust.works 5 points 11 months ago

Hm, that's interesting 👍.

[-] Kichae@lemmy.ca 0 points 11 months ago

The algorithms are the same. The models are different, being trained on a smaller data set.

[-] FooBarrington@lemmy.world 5 points 11 months ago* (last edited 11 months ago)

No, the algorithms are not the same. Phones don't use transformer models for text prediction, they use Markov chain-based approaches. Also, retraining of transformer models for individualized completion would be too expensive, whereas it's basically free with Markov approaches. Where do you get these ideas?

[-] 0x4E4F@sh.itjust.works 2 points 11 months ago* (last edited 11 months ago)

Perhaps, I'm not a dev, especially not an iOS or an Android one.

this post was submitted on 10 Dec 2023
118 points (84.7% liked)

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