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
Phones don’t use LLM for predictive text. The algos are a lot less complex on phones.
The algorithms are the same. The models are different, being trained on a smaller data set.
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?
Perhaps, I’m not a dev, especially not an iOS or an Android one.
Succint
AI is a vast field. LLMs and neural networks are a small part of it.
LLMs are very expensive to run and a lot more complex than the markov chains often used for predictive text.
Predictive text just chooses a likely word based on what’s typed. This may be as simple as looking for words that start with what you’ve typed.
LLMs vectorise words and understand the complex relationship between vectors using many data points. So it would spot the word “two” and realise that plurals are used with it.
Predictive text also can vectorize words, but the number of vectors per word are much, much simpler.
LLMs like chatgpt take a wild amount of resources to run.
If you want something as smart as gpt3 and you want it to run at typing speeds, you’ll need a gaming PC running it.
People just recently managed to run gpt3 strength models at all on ordinary laptop hardware (slowly).
There is currently no way to run something gpt4 strength on ordinary consumer hardware (I’m just guessing but I think it takes a few hundred gb of VRAM to run)
LLMs are orders of magnitude more sophisticated and expensive to run. But don’t worry, I’m sure not so far in the future we will see smaller LLMs being run on device to be used as autocorrect.
It would have to be pretty specific and small to work on a phone and I think a side effect would be everyone’s conversations start to sound a lot more homogeneous.
you’re not wrong. Google just announced Gemini Nano that will run directly on the Pixel 8. Of course, it’s the first of it’s kind and will probably be slow and it’s not used as autocorrect yet. But just give it one year or two and it will probably be more common.
Can we have Scottish ones that know what a bawbag is, and when to put an “e” on the end of “shit”?
Thanks!
Think of it from the LLM’s perspective - in the general pool you have common English, you have less common variations such as this, and then you have whatever the heck people like Kid Rock are doing…
Bawitdaba, da bang, da dang diggy diggy
Diggy, said the boogie, said up jump the boogie
Because they’re using different tech. That’s like asking why do phone calls sound bad compared to voip calls. They’re just using different tech.
Lawnmowers can’t keep up with Ferraris either, despite both being vehicles.
edit for wording
What the duck are you talking about?
You’re comparing apples to oranges.
If humans are just brains why are we smarter than dogs who also have brains?
It’s “no stupid questions”, so “no cunty answers” thanks
Well fuck you too pal, I thought it was a good analogy.
It wasn’t
It was, but the wrong community
