In the past week, Google has rolled out an update to the Translate API that includes a new feature that allows it to use machine-learning to predict text based on what it already knows about the language.
The company is also improving the translation algorithms for Google Translator, an extension that works with the web and native apps.
Google’s announcement is a major step toward expanding the capabilities of its translation software, but there are a number of other important updates as well.
The most notable is a new set of features for its translation engine that allow the company to use artificial intelligence to automatically extract text from a document.
Google already offers an AI tool called the Google Translations API, which lets developers create their own translation engine.
The API lets developers build their own engines that can extract text based, for example, on keywords in the document.
The latest update for the API allows developers to automatically learn how text in a document is structured, including whether it’s in the same language or in multiple languages.
Google also improved the efficiency of its API by automatically creating and extracting the most relevant matches for each word in a translation.
“With the latest update, we are introducing more efficient, machine-like AI to our translation engine, making it faster, more accurate, and more expressive,” the company said in a blog post.
The updated API is available to developers on GitHub, and Google said that it will continue to improve the service and offer new features.
For example, Google Translators now supports “deep learning” — a branch of artificial intelligence that uses deep learning to learn new tasks from the previous one, such as identifying which words are relevant to a topic.
This new version of the API is also a “first-of-its-kind” feature, Google said, adding that the company plans to add more language-specific features in the future.
Google Translated works by learning how to extract words from text using its own algorithm, and it then uses that knowledge to extract text that can be easily translated into other languages.
The update includes the following improvements: Automatic word extraction from text.
Now, if a document has several different words that sound similar, Google’s machine-learned system will automatically extract a matching word based on these similarities.
For instance, if there are two words “mushroom” and “moth,” the system will use the word “moulter” to extract a “moult” from the text.
This is similar to how it works in text analysis, in which computer scientists use machine learning to figure out which words belong to the same word and then try to infer meanings from them.
For the most part, Google says, the algorithm will not try to guess what the original text might have in common with other documents.
For other cases, however, the system may try to figure things out on its own.