Why Natural Language Processing is the future of enterprise AI
Business Intelligence

Why Natural Language Processing is the future of enterprise AI

Jon Oberlander is Professor of Epistemics at the University of Edinburgh. I spoke to him about the current trends for AI in the enterprise, particularly Natural Language Processing.

 

AI used to be obscure but has become a widespread term, even amongst the general public. What's changed?

We've reached a kind of inflection point. In the past it used to be said that as soon as something worked it stopped being called AI and was simply taken for granted. That was the paradox of success in this field. But now it's the other way around: anything that works is called AI.

Today's driver of success is machine learning. Bayesian algorithms and deep learning are what's driving the interest in this field. It's still generally called AI and machine learning, although deep learning is the more precise term.

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Alex Cruickshank

Freelance technology journalist Alex Cruickshank grew up in England and emigrated to New Zealand several years ago, where he runs his own writing business.

Comments

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Stephen Lander on September 18 2017

I have difficulty with the claim that automatic translation is getting better. I recently conducted a study of Google (which is supposed to be using AI techniques)and Bing Translate where I fed in a newspaper article. Not one paragraph was properly translated, either by Google or Bing. There were many elementary errors and some absolute nonsense. There was also not much difference between the two systems ─ sometimes Google did a better job than Bing, and sometimes Bing was better than Google. I also did not have the impression that the quality of the translations had improved much from a similar study I did over 20 years ago with SYSTRAN. It seems to be fashionable to claim that automatic translation is getting better, but the claims do not stand up to empirical testing.

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Alex Cruickshank on September 19 2017

Good point. I'm making use of Google Translate a lot at the moment and it's certainly still the case that human translators do a better job. As an acquaintance recently put it, "Sooner or later Google Translate is going to start a war." I suspect that the advances in this tech haven't yet made it to the consumer/end-user realm, or perhaps it depends on the source data. I believe Google Translate was largely trained on the multi-language minutes of the European parliament, which may not work well in other spheres.

no-images

Stephen Lander on September 18 2017

I have difficulty with the claim that automatic translation is getting better. I recently conducted a study of Google (which is supposed to be using AI techniques)and Bing Translate where I fed in a newspaper article. Not one paragraph was properly translated, either by Google or Bing. There were many elementary errors and some absolute nonsense. There was also not much difference between the two systems ─ sometimes Google did a better job than Bing, and sometimes Bing was better than Google. I also did not have the impression that the quality of the translations had improved much from a similar study I did over 20 years ago with SYSTRAN. It seems to be fashionable to claim that automatic translation is getting better, but the claims do not stand up to empirical testing.

no-images

Alex Cruickshank on September 19 2017

Good point. I'm making use of Google Translate a lot at the moment and it's certainly still the case that human translators do a better job. As an acquaintance recently put it, "Sooner or later Google Translate is going to start a war." I suspect that the advances in this tech haven't yet made it to the consumer/end-user realm, or perhaps it depends on the source data. I believe Google Translate was largely trained on the multi-language minutes of the European parliament, which may not work well in other spheres.

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