Monthly Archives: January 2019

What is required from Artificial General Intelligence with regard to Machine Translation?

We will be interested in a series of posts to try to define what is required of an AGI (Artificial General Intelligence) in order to reach the level of superintelligence in MT (machine translation). (All this is highly speculative, but … Continue reading

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Follow-up to the ‘issue of pair reversal’ and first steps for Italian to Corsican

Here is a short follow-up to the ‘issue of pair reversal’ regarding language pairs. It seems some 90% could be achieved in this reversal process. What is lacking here is an adequate handling of disambiguation. Let us focus on one … Continue reading

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Superintelligent machine translation (updated)

Let us consider superintelligence with regard to machine translation. To fix ideas, we can propose a rough definition: it consists of a machine with the ability to translate with 99% (or above) accuracy from one of the 8000 languages to … Continue reading

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New open test

Performing now a new open test, with the first 100 (more or less) words of the ‘article of the day’ from French wikipedia: we get 94,02% = 1 – (8 / 134). Several errors (5) result from lack of vocabulary. … Continue reading

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Minor breakthrough

It is kind of a minor breakthrough. The translation of French ‘en même temps que’ (at the same time as) is somewhat hard, in that it can take two different forms: either à tempu à or à tempu ch’è, depending on the context. The … Continue reading

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Priority pairs regarding endangered languages

There exists priority translation pairs, from the standpoint of endangered languages. Such notion of a priority pair (the most useful pair for the current users of the endangered language), regarding a given endangered language. For example, French to Corsican is … Continue reading

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Should machine translation software go open source

There is an ongoing debate on whether AI software should go open source or not (for example Bostrom’s paper Strategic Implications of Openness in AI Development). Now our current concern is of whether MT software should go open source or … Continue reading

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Some thoughts on the remaining 1% problem

To begin with, let us state the 1% problem, for machine translation: it seems some 99% accuracy in machine translation could be attainable but the remaining 1% (1% is just a given number, somewhat arbitrarily chosen, but useful to to … Continue reading

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