Originally published at PangeaMT blog I recently attended TAUS Tokyo Summit, where neural machine translation (NMT) was a hot topic. As Macduff Hughes from Google put it “Neural machine translation was a rumor in 2016. The first releases and tests happened six months ago and now it is here.” Although it is early days to
One year after its launch, NLPPeople analysed the hundreds of job ads that had been published on its website during that time. In a blog post we discussed the supremacy of the US in NLP jobs, the imbalance between industry and academia, among other other striking patterns. Almost three years later it’s time to take
Deep learning is currently taking the IT world by storm. Facebook, Bloomberg and Google are actively exploring deep learning techniques. Thousands of deep learning startups operating in various industries raise seed funding every day. If you like traveling, have the budget and want to find out more about deep learning technology, there are so many
Big Data and cross-language processing can be a very happy marriage that will open way to the new generation of powerful multilingual product. However, what is missing to let it happen already? What is the profile of the individual who will bring the multlingual Big Data to life? Read about it below. Big Data is a
This time, we would like to present you a post written by one of our regular visitor, Irina Popova. She is searching for a new career challenge after her recent graduation from the University of Stuttgart and would like to share one of her first real-world work experiences.
Machines have become so smart that they are taking over our daily activities from driving to writing. Nick Gallimore, a professional recruiter in the artificial intelligence area is trying to find an answer to the question “Where is the hiring going to come in the new world?”.
Machine translation is one of the most known and demanded NLP applications that thousands of millions of people use on a daily basis. At the same time, the voice of criticism by professional translators is clearly to hear. We asked several translators with MT experience about limitations of MT and in which areas MT providers
In this post we continue presenting the main groups of factors that influence any young NLP company by example of a Machine Translation startup in Europe. Here, we will cover the following areas: Technology&Research, Data, Evaluation, Resources and Translators & Post-editors. Please refer to the previous post for the rest of the discussion. .
This spring the University of Toronto ran an online course on statistics and statistical calculus at the Coursea.org platform. We are delighted to present a review of this course written by Viktoria Denisova.
If you are thinking of starting your own business in the NLP area (and some of you do think about it, for sure), you might be interested in look at the analysis done by bmmt: one of successful machine translation startups. Read a series of posts describing several groups of factors that have impact on