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
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
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…
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.
Does the AI processing have to be performed locally or constantly active?
No, but you open up a can of worms from a security aspect if you send it out to be processed.
I’m sure every phone having a keylogger won’t end badly
And latency.
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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
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
Openhermes 2.5 Mistral 7b competes with LLMs that require 10x the resources. You could try it out on your phone.
I think apple has pitched this for a future iPhone, yes.
They’ll probably have to offload that to a server farm in real time. That’s not gonna be easy.