I've been arguing this is the way AI should be deployed. Rather than trying to sell ai as an end to end solution, just let it do the small part that it can reliably do. It's cost effective for the host, and valuable for the user. win win engineering!
Apple’s new Transformer-powered predictive text model
121–130 of 268 posts
Re: Apple’s new Transformer-powered predictive text model
#122I've been arguing this is the way AI should be deployed. Rather than trying to sell ai as an end to end solution, just let it do the small part that it can reliably do. It's cost effective for the host, and valuable for the user. win win engineering!
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Re: Apple’s new Transformer-powered predictive text model
#123Earlier quoted context omitted.
What's "high quality" refer to here? The amount of txt spk I use on my iphone keyboard, vs words that are in the dictionary, is heavily skewed in the direction of short words that a corpus consisting of English text is likely to omit.
You use text speak on an iPhone? How? I find it impossible due to autocorrect. Either it will correct with the full word or it will correct with a wrong word making it more efficient to just type in full.
Turn off autocorrect: https://support.apple.com/en-us/HT207525
Re: Apple’s new Transformer-powered predictive text model
#124The example output reads exactly like the existing output, I have had it get caught in exactly that cycle.
Even large language models with billions of parameters get caught in the cycle. You don't usually see it exposed to users because there are sampling tricks applied, such as repetition/frequency penalty.
I don’t agree, it’s not very common for LLMs to get stuck in loops simply because loops are not commonly observed in the datasets.
Re: Apple’s new Transformer-powered predictive text model
#125Beyond fixing iPhone’s autocorrect as widely mentioned below, I wonder if in future versions Apple will end up switching to phi-1.5 or other models that are much smaller but trained on higher quality data. Would also be cool if they trained their own copilot for Xcode, given their obviously enturmes code base in Swift and Obj-C.
What's "high quality" refer to here? The amount of txt spk I use on my iphone keyboard, vs words that are in the dictionary, is heavily skewed in the direction of short words that a corpus consisting of English text is likely to omit.
My hypothesis is that this question, "What's 'high quality' refer to here?", is a big challenge and the answer depends upon the audience. Here are a few examples:
- kids use one level of slang
- older ages groups using another (and it might mean something quite different)
- communications for professional wouldn't use slang and would use formal messages
- different cultures/regions will use different phrases for the same thing (and some colloquialisms are quite sophisticated like Cockney rhyming slang)
- on twitter when out of space you might then shorten words
The thing that really 'riles me up' / 'get on my wick' / 'annoys me' / 'is immensely frustrating' / 'is an opportunity for a sales feature' [trying to demonstrate the different phrasing depending upon audience] is when the auto correct 'fixes' grammar incorrectly. It needs to be clever enough to realise the correct use of there/their/they're and its/it is/it's.
I'll leave with a relevant poem: https://allpoetry.com/poem/4010351-They-re-There-with-Their-...
Re: Apple’s new Transformer-powered predictive text model
#126In typical Apple fashion, when everyone's going bigger and stronger, they're going in a different direction... With optimising to the smallest model that can run all day without draining your battery.
I love that they're almost never first to market but they find a way to distil value than others don't. It's the almond milk of technology.
Re: Apple’s new Transformer-powered predictive text model
#127I don't want better predictive text. I need better autocorrect. Something happened about 6 years ago where the quality of the autocorrect fell off the roof, and it's been absolutely terrible since then. I spend too much of my time fighting with either mispelling, flipping to the wrong word even though I spelled the word properly, etc. It has made typing on my iPhone an unpleasant experience and I need it to change. T…
I use SwiftKey and it's much better than the Apple one. But it does require giving Microsoft access to most of what you write.
Re: Apple’s new Transformer-powered predictive text model
#128I don’t think you can make a fair comparison like this. The examples at the end are essentially praising GPT-2 for hallucinating - is it better when it’s suggesting completely irrelevant text to your sentences? Apple’s approach can’t generate full sentences on its own, but that’s not the goal anyway.
Re: Apple’s new Transformer-powered predictive text model
#129The example at the end made me wonder if Apple's model is actually better than GPT2 for text prediction. It generated garbage, but all that garbage made somewhat sense in the context of only the word "Today". Whereas GPT2 hallucinated random stuff about the US government. A text prediction model should predict what the user wanted to type, so if you evaluate the models based on that, GPT2 actually performed horribly,…
It seems obvious to me that it's not, because if you asked a human to guess what comes after "today" in a text, they'd never say "probably some gibberish about a day a day".
Garbage in, garbage out? The preceding text is gibberish, so the prediction will be worse. Presumably they also only show completions with a much higher confidence threshold.
Re: Apple’s new Transformer-powered predictive text model
#130In typical Apple fashion, when everyone's going bigger and stronger, they're going in a different direction... With optimising to the smallest model that can run all day without draining your battery. I love that they're almost never first to market but they find a way to distil value than others don't. It's the almond milk of technology.
In typical Apple fanboy fashion they are oblivious to what Google has been doing for over two years now.