TechGist05

  This is a guest post by Luigi Muzii based on a presentation he made recently on the coming industry disruption. Digital disruption is all around us today, and one characteristic of how it manifests is how it sneaks up and is in control before the incumbents even realize what has happened. Sears and other retailers barely saw Amazon coming, taxi companies did not see Uber coming, the hotel industry was caught unaware by Airbnb and so it goes.   A recent Cisco/IDC suggests that 40% of all companies today will be affected (disappear) by the digital disruption.   It is quite possible that a new player could emerge in the translation industry that produces a platform that allows buyers and sellers to congregate and conduct efficient transactions with minimal broker (LSP) support (or just platform support). The translation industry is one that still struggles to talk about quality in a way that is clear and meaningful to customers. A platform that provides CAT tools, properly integrated MT

This is a guest post by the principals of Tmxmall, which is a Chinese Translation Memory Marketplace, i.e. a site that sells translation memory to interested parties (mostly translators and LSPs). This is one of two such intiatives coming from China. I will be featuring the other one shortly. Data is a critical requirement for any of the modern MT technology paradigms. While SMT was able to handle some level of noise  in the data used, it appears that NMT is more particular and the "more data is better" principal does not apply as clearly, if it ever did. The quality of the training data matters with AI and machine learning.  The pursuit of building up training data resources will always exist in the context of any Machine Learning technology. However, commodity data that you can easily obtain or buy tends to usually be low quality data, and not high-quality data by most people's assessment. This is what TAUS has to say about these new initiatives: "The internet gian