Learn About Machine Learning
August 30, 2017
For an in-depth look at the technology behind Google Translate, turn to Stats and Bots’ write-up, “Machine Learning Translation and the Google Translate Algorithm.” Part of a series that aims to educate users about the technology behind machine learning (ML), the illustrated article delves into the details behind Google’s deep learning translation tools. Writer Daniil Korbut explains the factors that make it problematic to “teach” human language to an AI, then describes Long Short-Term Memory (LSTM) networks, bidirectional RNNs, sequence-to-sequence models, and how Google put those tools together. See the article for those details that are a bit above this writer’s head. There’s just one thing missing—any acknowledgment of the third parties that provide Google with language technology. Oh well.
Another valuable resource on machine learning, found at YCombinator, is Google researcher Jeff Dean’s Lecture for YC AI. The post includes a video that is over an hour long, but it also shares the informative slides from Dean’s presentation. They touch on scientific and medical applications for machine learning, then examine sequence-to-sequence models, automated machine learning, and “higher performance” ML models. One early slide reproduces a Google blog post in which Dean gives a little history (and several relevant links):
Allowing computers to better understand human language is one key area for our research. In late 2014, three Brain team researchers published a paper on Sequence to Sequence Learning with Neural Networks, and demonstrated that the approach could be used for machine translation. In 2015, we showed that this this approach could also be used for generating captions for images, parsing sentences, and solving computational geometry problems. In 2016, this previous research (plus many enhancements) culminated in Brain team members worked closely with members of the Google Translate team to wholly replace the translation algorithms powering Google Translate with a completely end-to-end learned system (research paper). This new system closed the gap between the old system and human quality translations by up to 85% for some language pairs. A few weeks later, we showed how the system could do “zero-shot translation”, learning to translate between languages for which it had never seen example sentence pairs (research paper). This system is now deployed on the production Google Translate service for a growing number of language pairs.
These surveys of Google’s machine translation tools offer a lot of detailed information for those interested in the topic. Just remember that Google is not (yet?) the only game in town.
Cynthia Murrell, August 30, 2017
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This time around Stu is getting married to a young Asian beauty named Lauren (Jamie Chung), who’s father completely disapproves of him.