TechGist05

Recently I came upon this little tidbit and initially thought how wonderful, (NMT is surely rising!) and decided to take a closer look and read through the research paper . This exercise left me a little uncertain as I now felt doubt, and began to suspect that this is just another example of that never-ending refrain of the MT world, the empty promise. Without a doubt Google had made some real progress, but “Nearly Indistinguishable From Human Translation” and “GNMT reduces translation errors by more than 55%-85% on several major language pairs “. Hmmm, not really, not really at all, was what my pesky brain kept telling me, especially as I saw this announcement coming up again and again through many news channels, probably pushed heavily by the Google marketing infrastructure. Surely the great Google of the original “Don’t Be Evil” ethos would not bullshit us thus. (In their 2004 founders' letter prior to their initial public offering, Larry Page and Sergey Brin explained tha...

This is the second part of an interview with Jean Senellart (JAS) , Global CTO and SYSTRAN SAS Director General. The first part can be found here: A Deep Dive into SYSTRAN’s Neural Machine Translation (NMT) Technology . Those translators who accuse MT vendors of stealing or undermining their jobs should take note that SYSTRAN is the largest independent MT vendor. A position it has held for most of its existence, but has never generated more than €20 million in annual revenue. Which to me suggests that MT is mostly being used for different kinds of  translation tasks and is hardly taking any jobs away. The problem has been much more related to unscrupulous or incompetent LSPs who used MT improperly in rate negotiations. MT is hugely successful for those companies who find other ways to monetize the technology, as I pointed out in  The Larger Context Translation Market .This does suggest that MT has huge value in enabling global communication and commerce, and even in its les...

One of the wonderful things about my current independent status is the ability to engage deeply with other MT experts who were previously off limits because competing MT vendors don't usually chat with open hearts and open cloaks. MT is tough to do well and I think the heavy lifting should be left to people who are committed for the long run, and who are willing to play, invest and experiment in spite of regular failure. This is how humans who endure and persist, learn and solve complex problems. This is Part 1 of a two-part post on the SYSTRAN NMT product announcement. The second part will focus on comparing NMT with RBMT and SMT and also with the latest Adaptive MT initiatives. It can be found here: Comparing Neural MT, SMT and RBMT – The SYSTRAN Perspective Press releases are so filled with marketing-speak as to be completely useless to most of us. They have a lot of words but after you read them you realize you really don't know much more than you got from the headline. S...

This is a guest post by Deepan Patel at Milengo Ltd. This post is part of a series of upcoming posts that will provide varying LSP perspectives on MT technology. I would invite other LSPs who may have an interest in sharing a view to come forward and contact me to discuss different potential subjects. I may not always share the opinions of the guest writers, but I am a proponent of sharing differing views, and letting readers decide for themselves what makes most sense to them. I do not edit these opinions except for minor typos and basic reading flow related edits. I may sometimes highlight some statements in bold to highlight something I think is central to the view. I have added a presentation made by Deep a n at TAUS, which is in the public domain, to provide more detail on his user case context.    -----------   One of the key factors in Milengo’s success in establishing a robust and sustainable framework for ma...