Published in AI

AI can’t translate languages

by on17 October 2022

This is not an area companies should want to experiment

For a while now companies have been thinking that they can off-load their translation work onto AI-based systems to save a buck – but a top boffin has warned that the software is not up to the task.

NYU professor emeritus Gary Marcus has warned that AI as it is understood can’t translate to save its life because it really can’t understand what it is seeing.

Marcus said that people are led to believe that AI understands human language, which it certainly does not.

What it really is, is a glorified autocomplete system that predicts words and sentences. Just like with your phone, you type in something, and it continues. It doesn't understand what it is doing or its meaning.

"And a lot of people are confused by that. They're confused by that because what these systems are ultimately doing is mimicry. They're mimicking vast databases of text. And I think the average person doesn't understand the difference between mimicking 100 words, 1,000 words, a billion words, a trillion words — when you start approaching a trillion words, almost anything you can think of is already talked about there. And so when you're mimicking something, you can do that to a high degree, but it's still kind of like being a parrot, plagiarist, or something like that. A parrot's not a bad metaphor because we don't think parrots understand what they're talking about."

This inability to translate due to lack of understanding will spill out into other areas which AI is being touted as a saviour, such as driverless cars.

"Merely memorising a lot of traffic situations that you've seen doesn't convey what you really need to understand about the world in order to drive well"), he said.

Another area which as got Marcus goat is OpenAI's DALL-E which is based on the not-necessarily-intended contributions by human beings, who have maybe signed off on a 'terms of service agreement, but don't recognise where this is all leading.

 Marcus says he's heartened by some recent AI developments as people are daring to step out of the deep-learning orthodoxy, and finally willing to consider "hybrid" models that put deep learning together with more classical approaches to AI.

“The more the different sides start to throw down their rhetorical arms and start working together, the better," he said.


Last modified on 17 October 2022
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