“A team of Microsoft researchers announced on Wednesday they’ve created the first machine translation system that’s capable of translating news articles from Chinese to English with the same accuracy as a person. The company says it’s tested the system repeatedly on a sample of around 2,000 sentences from various online newspapers, comparing the result to a person’s translation in the process – and even hiring outside bilingual language consultants to further verify the machine’s accuracy.”
Source: Techcrunch
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it actually looks pretty good. Welp, time to find a new career.
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- It doesn't "know" that what it produces is correct. It's capable of producing several options (in this case, two), one of which is likely to be quite accurate, but it can't tell on its own which one to use.
- It looks like it's designed to parse text written in a specific way, i.e. by trained journalists. News reports have certain style conventions and it's not hard to imagin... See more
- It doesn't "know" that what it produces is correct. It's capable of producing several options (in this case, two), one of which is likely to be quite accurate, but it can't tell on its own which one to use.
- It looks like it's designed to parse text written in a specific way, i.e. by trained journalists. News reports have certain style conventions and it's not hard to imagine that a machine with access to a vast amount of data can identify and pick up relevant information. Evidence to this is that the machine performed extremely poorly when I threw a couple of interview quotes at it. They were not in a style that the machine was trained in, and the confused machine was not even able to try and fake a fluent output. I also tried several legal text excerpts, relatively simple ones (terms of service) that pose no significant difficulty for a well-educated reader without formal legal training. The machine was able to produce a more-or-less acceptable output for the more verbose sample, but the other two threw it off completely.
The second weakness can be mitigated with more data, but the first has no solution in the foreseeable future. Accumulating more human selection data can increase the confidence of the choice, but only to a certain extent. It can't deliver total confidence without a human reviewer, and at that point you have a competent translator in the loop.
Translators are cheap, translation mistakes are expensive. The translation market could transform and it could shrink, but it has a long way to go before it becomes irrelevant. ▲ Collapse
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