When Microsoft launched the offline functionality for Android, it was really bringing the experience in line with Google's offering on the platform. But while the search giant's Translate app for Android does offline translation of text (and even photos containing text), its iOS app is online-only. That makes Microsoft's Translate app the first from a major company to offer the functionality, and the first ever on the platform to use a neural network to achieve it. The iOS app supports 43 languages, although you'll have to download the relevant libraries before going offline. That's a lot more than the nine the Android version launched with, but Microsoft says it's updating that app to support the expanded catalog.

Microsoft today announced that its Microsoft Translator app for iOS devices can now translate text and images from one language to another even when you're offline. The app already supported this functionality on Android, and the competing Google Translate for Android could work offline, too. But in this case, Microsoft has beat Google to the punch -- Google Translate currently works offline only on Android. "Until now, iPhone users needed an Internet connection if they wanted to translate on their mobile devices. Now, by downloading the Microsoft Translator app and the needed offline language packs, iOS users can get near online-quality translations even when they are not connected to the Internet. This means no expensive roaming charges or not being able to communicate when a data connection is spotty or unavailable," the Microsoft Translator team wrote in a blog post.

Microsoft today announced that its Microsoft Translator app for iOS devices can now translate text and images from one language to another even when you're offline. The app already supported this functionality on Android, and the competing Google Translate for Android could work offline, too. But in this case, Microsoft has beat Google to the punch -- Google Translate currently works offline only on Android. "Until now, iPhone users needed an Internet connection if they wanted to translate on their mobile devices. Now, by downloading the Microsoft Translator app and the needed offline language packs, iOS users can get near online-quality translations even when they are not connected to the Internet. This means no expensive roaming charges or not being able to communicate when a data connection is spotty or unavailable," the Microsoft Translator team wrote in a blog post.

Artificial intelligence is being used all around is, but it looks nothing like The Jetsons. So why are people panicked that robots will take their jobs? The World Economic Forum warned that robots and technological advances will take more than 5 million jobs from humans over the next five years. Machine learning has undoubtedly earned its place in the workforce, but machines don't necessarily have to replace humans – they can in fact enhance the work humans can do. One area where machine learning is flourishing is in the localisation and translation industry.

Google confirmed they plan to improve Google Translate's accuracy through artificial intelligence called deep learning. Deep learning is an advanced model of machine learning where an algorithm takes what it has already "learned" (data previously processed) and uses it to form new ways to solve problems in a pattern. Jeff Dean, Google Senior Fellow, confirmed that his team has been working with the Google Translate team to "scale out experiments with translation based on deep learning." Deep learning and technologies derived from it, including deep and recurrent neural nets, are objectively excellent at tackling sequential problems such as speech and image recognition, as long as there is sufficient existing material to train them. On that front, Google Translate's vast data trove of translated material should indeed prove quite useful.

Artificial intelligence is on the rise in the world of machine translation. A string of recent news about tech giants bolstering machine translation engines with deep learning underscores just how central integrating deep learning into machine translation products has become for companies like Google and Microsoft. Slator reached out to a representative of Beijing-based Baidu, who is authorized to speak for the company, to get an exclusive look at what the Chinese tech leader has in store for its translation technology. Baidu began R&D on Baidu Translate in 2010, launching the product in June 2011. The company felt that translation was in line with what their search users needed.

Microsoft Translator is a cloud-based automatic text and speech translation (a.k.a.

Everyone is looking for the next breakthrough in machine translation. No one believes that machine translation is a completely solved problem. Most people would like to see machine translation systems produce higher quality results. A good translation is one where the meaning of the source is preserved, and it is rendered correctly in the target language. Users expect accuracy on all of the various levels–grammar, syntax, semantics and pragmatics.

For any cloud to be taken seriously, it has to meet an ever rising bar of features. Machine learning seems to be on that list, as all the major cloud providers now feature it. But how they go about doing it is another story. Aside from the "curated API vs. open-ended algorithm marketplace" models, there are the "everything and then some vs. just enough" variants. Here's how the four big cloud providers -- IBM, Microsoft, Google, and Amazon -- stack up next to each other in machine learning. When IBM first announced it would turn its Watson AI system into a consumable service, the questions piled up.

One day in the not-so-distant future, an app might make a dinner reservation for you before you realize you even want to go out, or your smartphone might suggest tourist sights you'd enjoy when you land in a new city. It's possible -- and it's really not so far away, say analysts, who were encouraged today by Google's announcement that it's open sourcing an enhanced machine learning system. The system, dubbed TensorFlow, is smarter, faster and more flexible machine-learning software than Google has ever had before, according to Sundar Pichai, Google's CEO, in a blog post . "Just a couple of years ago, you couldn't talk to the Google app through the noise of a city sidewalk, or read a sign in Russian using Google Translate, or instantly find pictures of your Labradoodle in Google Photos," wrote Pichai. But in a short amount of time they've gotten much, much smarter. Now, thanks to machine learning, you can do all those things pretty easily, and a lot more."