Google is catching up to competitors Facebook, Apple and Amazon in messaging, video calling and home speaker-embedded digital assistants. But it's taking the lead in virtual reality and may have changed mobile phones forever with a new twist on mobile apps that allows them to play without being installed. That's the conclusion of Jan Dawson, an analyst with Jackdaw Research, who was at the Google I/O annual developers conference Wednesday in Mountain View, California. Dawson said Google's new Allo app focuses on the search giant's strengths in search and natural language recognition, but may have come too late behind bigger rivals to gain much use. In a research note he praised Google's new Daydream virtual reality platform, but noted it'll take time to become popular because the high bar for specifications means no devices can support it yet.

Neural machine translation is a recently proposed approach to machine translation. Unlike the traditional statistical machine translation, the neural machine translation aims at building a single neural network that can be jointly tuned to maximize the translation performance. The models proposed recently for neural machine translation often belong to a family of encoder-decoders and consists of an encoder that encodes a source sentence into a fixed-length vector from which a decoder generates a translation. In this paper, we conjecture that the use of a fixed-length vector is a bottleneck in improving the performance of this basic encoder-decoder architecture, and propose to extend this by allowing a model to automatically (soft-)search for parts of a source sentence that are relevant to predicting a target word, without having to form these parts as a hard segment explicitly. With this new approach, we achieve a translation performance comparable to the existing state-of-the-art phrase-based system on the task of English-to-French translation. Furthermore, qualitative analysis reveals that the (soft-)alignments found by the model agree well with our intuition.

It can be a pain to install phone apps you know you'll use just once or twice. The app runs on Google's servers instead of your phone. Only the parts you need get sent to your phone on an as-needed basis. If it works as Google envisions, without lags and other annoyances, users won't have to spend a few minutes downloading and installing that app and having it take up valuable space on the phone. The app maker needs to enable this feature, though.

South Korean professional Go player Lee Sedol reviews his second match against Google's artificial intelligence program, AlphaGo in Seoul on March 10, 2016. The human Go champion said he was left "speechless" after his second straight loss to Google's Go-playing machine.

A sneak peak of what the future holds for Android, Google's artificial intelligence pursuits, and virutal reality. Google announces messaging app Allo at I/O developer conference in Mountain View, Calif. Google debuted its new messaging app to rival Facebook Messenger at I/O, its annual software developers conference. The messaging app has a twist: It's not just for chatting with friends and family. You can ask Google questions the way you would a digital assistant such as Siri.

When Google's AlphaGo computer program bested South Korean Go champion Lee Se-dol in March, it took advantage of a secret weapon: a microprocessor chip specially designed by Google. The chip sped up the Go-playing software, allowing it to plot moves in the time-limited match and look further ahead in the game. But the processor, built in secret over the last three years and announced on Wednesday, plays a more strategic role in the company. Google, a division of Alphabet Inc., has been using it for more than a year to...

Editor's note: This is an excerpt from the upcoming report Data Science for Modern Manufacturing: Global Trends: Big Data Analytics for the Industrial Internet of Things, by Li Ping Chu. Sign up to be notified when the report becomes available. The field of artificial intelligence has been around for decades, and the world has seen massive advances in what is considered deep learning (e.g. IBM's Deep Blue and Google's AlphaGo), but it's only within the past decade that we've seen practical applications of machine learning in an enterprise setting. In the past few years, there has been an explosion in the number of products available that integrate machine learning within a business intelligence platform.

Facebook has two of them: WhatsApp and Messenger. They're all messaging apps--smartphone apps that let you chat with friends and family. But they're rapidly morphing into something else, a new kind of super communication tool that does so much more than just shuttle texts between people. So, it should come as no surprise that Google is building a new one of its own. The big difference is that, well, it comes from Google.

Forget about superintelligent AIs being created by a company, university, or a rogue programmer with Einstein-like IQ. Hollywood and its AI-themed movies like Transcendence and Her have misled the public. The launch of the first truly autonomous, self-aware artificial intelligence--one that has the potential to become far smarter than human beings--is a matter of the highest national and global security. Its creation could change the landscape of international politics in a matter of weeks--maybe even days, depending on how fast the intelligence learns to upgrade itself, hack and rewrite the world's best codes, and utilize weaponry. In the last year, a chorus of leading technology exp erts, like Elon Musk, Stephen Hawking, and Bill Gates, have chimed in on the dangers regarding the creation of AI.

Artificial intelligence has been around since 1956 and has made some giant leaps in that time: beating the best human at chess, the best human at US gameshow Jeopardy and recently beating the best human at complex strategy game Go. Brands have only recently started adopting artificial intelligence for core consumer services. Google's voice recognition technology now claims 98% accuracy and Facebook's DeepFace is said to recognise faces with a 97% success rate. IBM's Watson, which uses artificial intelligence to perform its question-answering function, is 2,400% "smarter" today than when it achieved the Jeopardy victory five years ago. There is no doubt that the relationship between men and machines is changing, and brands are on the cusp of making artificial intelligence an everyday element of their customer offerings.