Navi allows you to understand anyone, anywhere, anytime. Traveling abroad can be an incredible adventure, but the language barrier can make even the most intrepid explorer nervous. The fear of being unable to communicate or understand signs and menus keeps many would-be travelers from ever leaving their home country. With the rise of powerful translation apps, you can harness the latest technology right on your smartphone to bridge the language gap wherever your journey takes you. I've tested out the top contenders to bring you my picks for the best translation apps for global travelers.

Today's language translation apps are like self-driving cars: incredibly useful, promising, nearing maturity, and almost entirely powered by machines. It's astonishing that the technology even exists. Even so, machine translation is still clunky at times, if not awkward. Consider a recent conversation I had with my neighbor, Andre, who immigrated from Russia last year. Speaking little to no English, Andre is navigating the American Dream almost entirely through Google Translate, the most popular speech-to-speech translation app, first launched 10 years ago.

In brief Authorities in the United Arab Emirates have requested the US Department of Justice's help in probing a case involving a bank manager who was swindled into transferring $35m to criminals by someone using a fake AI-generated voice. The employee received a call to move the company-owned funds by someone purporting to be a director from the business. He also previously saw emails that showed the company was planning to use the money for an acquisition, and had hired a lawyer to coordinate the process. When the sham director instructed him to transfer the money, he did so thinking it was a legitimate request. But it was all a scam, according to US court documents reported by Forbes.

Until recently, a multinational company looking to help customers around the world book international travel would have had to build separate chatbots from scratch to converse in French, Hindi, Japanese or other languages. But thanks to artificial intelligence research breakthroughs that have enabled algorithms to more accurately parse nuances in the way different languages express concepts or structure sentences, it is now possible to build a single bot and use Microsoft Translator to translate questions and answers accurately enough for use in multiple countries. Over the past few years, Microsoft deep learning researchers were the first to achieve human parity milestones in developing algorithms that could perform about as well as a person on research benchmarks testing conversational speech recognition, reading comprehension, translation of news articles and other challenging language understanding tasks. Now, the benefits of those AI research breakthroughs are making their way into products from Azure to Bing. Search engineers are borrowing lessons from Microsoft AI researchers who developed a new deep neural network model that can learn from multiple natural language understanding tasks at once.

A new batch of Machine Translation tools driven by Artificial Intelligence is already translating tens of millions of messages per day. Proprietary ML translation solutions from Google, Microsoft, and Amazon are in daily use. Facebook takes its road with open-source approaches. What works best for translating software, documentation, and natural language content? And where is the automation of AI-driven neural networks driving? William Mamane, Head of Digital Marketing at Tomedes, a professional language services agency, had been a skeptic of machine translation.

A new batch of Machine Translation tools driven by Artificial Intelligence is already translating tens of millions of messages per day. Proprietary ML translation solutions from Google, Microsoft, and Amazon are in daily use. Facebook takes its road with open-source approaches. What works best for translating software, documentation, and natural language content? And where is the automation of AI-driven neural networks driving? William Mamane, Head of Digital Marketing at Tomedes, a professional language services agency, had been a skeptic of machine translation.

Companies such as Amazon, Google, Microsoft, and many others have rapidly expanded their machine learning offerings and now increasingly encroach on the heart of language services. Take Bridgeman Images, for example. Bridgeman is a "specialist in the distribution of fine art, cultural and historical media for reproduction" -- the Getty Images of the art world, if you will. According to an Amazon case study published on February 6, 2019, the company needed automated translation to localize into many languages at scale. They opted for Amazon Web Services' Amazon Translate to localize "570 million English characters into Italian, French, German, and Spanish" over the course of 15 days.

I visited Beijing last week and learned a great deal from Microsoft's AI //innovate event in China - our 2nd largest developer base for Cognitive Services on Azure. The most heart-felt demo was Harry Shum could communicate with an almost deaf student of Nanjing University of Technology. Using two mobile phones with Microsoft Translator, the deaf student not only had no problem to communicate with Harry but also removed his language barriers between Chinese and English! I started speech recognition research as a graduate student in Beijing's Tsinghua University more than 35 years ago. My graduate student dream was to help people communicate better without language barriers.

A fresh wave of artificial intelligence rolling through Microsoft's language translation technologies is bringing more accurate speech recognition to more of the world's languages and higher quality machine-powered translations to all 60 languages supported by Microsoft's translation technologies. The advances were announced at Microsoft Tech Summit Sydney in Australia on November 16. "We've got a complex machine, and we're innovating on all fronts," said Olivier Fontana, the director of product strategy for Microsoft Translator, a platform for text and speech translation services. As the wave spreads, he added, these machine translation tools are allowing more people to grow businesses, build relationships and experience different cultures. Microsoft's research labs around the world are also building on top of these technologies to help people learn how to speak new languages, including a language learning application for non-native speakers of Chinese that also was announced at this week's tech summit. The new Microsoft Translator advances build on last year's switch to deep neural network-powered machine translations, which offer more fluent, human-sounding translations than the predecessor technology known as statistical machine translation.

Huawei has really upped its game in recent years, especially with the launch of its Huawei Mate 10 Series late last year. Its sleek build aside, its specifications are pretty outstanding. In fact, it boasts Kirin 970 – which Huawei designed and built itself – the world's first AI processor for smartphones with a dedicated Neural-Network Processing Unit (NPU). This chipset pretty much fuels the smartphone's machine-learning features and includes a special module dedicated to AI calculations. AI is becoming increasingly important in today's smartphone experience, and coupled with machine learning, they are the reasons why our phones are getting better and more powerful every year.