Translations

From around 1405, it means vulgar Latin * puppa from Puppe in Central France, Poppa in Italy, Latin puppa, all "stern"

Stool (The third person presents a simple stool, a current participle, simple past and past participle alone)

Another night, before the breeze we blew and after the sea which was rolling behind us, unfortunately we regret by the wave of our stern to attack the window stove in the cabin, the main deck Rush through the cabin along

Stool (The third person presents a simple stool, a current participle, simple past and past participle alone)

Pastor W. Awdry, 2001 Thomas Tank Engine Series: Unique Story Collection from the Railway Series in 2001 - p. 157 - Egmont Books, Limited, 15th August 2001

Two minutes have passed - five - seven - ten. "Hi!" When the Queen's train slid into the station, everyone knew a whistle and a strong cheer.

Stool (The third person presents a simple stool, a current participle, simple past and past participle alone)

In addition to fighting, the history of this country seems to include only old feces that can not kiss boots of young mentally ill patients due to strict treatment and vague love as in the past is.

Translation - doing a good job - is a long process. If you like to translate and learn languages, that is not as boring as it sounds. It takes time, yes, but it is not a chore. With Google Translate, you can enter text into a machine and edit the results, which makes the translation process smoother (especially after updating the neural network). It is faster to handle text than to write text from scratch. If you are fluent or communicating in the target language, this can speed up your process. However, if you do not have enough experience you probably will not understand simple (very basic) errors in Google Translate and other machine translations. Speaking of amateurs' words, it is a foolish mistake.

Traditionally, machine translation relies on a large number of text datasets in one language and the corresponding translation of the target language. For language pairs that do not have this training data, Google translates it into English first and then translates it into the target language so that English is a direct expression of semantics or intermediate language. Recently, Google rewrote the machine translation stack as a whole and published its method in Google Neuro machine translation. The neural network uses an input sentence such as "knowledge is power" and uses an encoder to convert them to a high dimensional vector. From this number, it goes through the decoder into the target language, eg 'knowledge creates power'. If you lose sight of you in this paragraph, it is important that the new system find a digital way to express the meaning without direct human data entry.

Machine translation (MT) automatically translates text from one natural language (source language) to another language (target language) using machine capabilities. The idea of ​​using a machine for translation was first proposed by Warren Weaver in 1949. Machine translation has been done for a long time (from the 1950's to the 1980's) by studying the language information of the source language and the translation language and generating a translation based on the dictionary. And the grammar is called Rule Based Machine Translation (RBMT). Along with the development of statistics, statistical models became applied to machine translation, and translations were generated based on analysis of bilingual text corpus. This approach, known as Statistical Machine Translation (SMT), achieved superior performance than RBMT and became dominant over the 1980s and early 2000s. Their research has laid the foundation for the future application of neural networks in machine translation.