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
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.
Succint
Now guess how it feels to type German with predictive text. Most of our words can have more than a dozen different word endings depending on time and how the word is used. And that’s not taking into account that we use compound words, which word prediction pretty much cannot predict and often doesn’t even know. So spell check will mark a legal compound word as misspelled, because it doesn’t understand the concept of compound words and doesn’t know this specific word combination.
To show what I mean, the term “Danube steam boat captain’s hat” becomes “DonauDampfSchiffKapitänsMütze” (I added capital letters which shouldn’t be there to show where the next word in the compound word begins).
While this is an extreme example, it’s pretty common for compound words to consist of 4-5 words.
What the duck are you talking about?
