Here are some news to make your technical support life easier. This time we've focused on making the interface and functions even more intuitive. Technical support should always be easily accessible wherever you are--that's why we've made your virtual expert mobile-first. We simplified the layout of the virtual expert to make it easier to find things. Now every important action you want to access is found in the same place--just look in the drawer!

A few years back, when someone said "Artificial Intelligence" (AI), we immediately thought about Skynet, Terminator, Matrix, HAL 9000, J.A.R.V.I.S., and all the other SCI-Fi technologies we saw in movies. Since then, things have changed quite drastically. When you hear about AI, you expect a conversation about smart assistants like Siri, Cortana, Alexa, or you expect to hear about how IBM Watson won Jeopardy! AI slowly went past the research phase and made its way into multiple industries including healthcare, fashion, weather forecasting, teaching, and driving. IBM even made Chef Watson cook some food (and it didn't even taste that bad).

With the advent of cloud computing, e-commerce, and social media, it's difficult to keep tabs on who has access to our data, and harder still to know how much care they're taking with it -- barely a day goes by without some form of data-breach, lapse, or privacy scandal coming to the fore. But what constitutes "data-misuse" is covered by a broad gamut of scenarios that reach beyond poor security hygiene. Online tracking and profiling is rife -- it turns out there is a heap of money to be made from knowing where you are, what you do, and what you like. It all comes down to personalization: selling things, be it products, playlists, or a political ideology, based on who you are. The Facebook and Cambridge Analytical, which highlighted how social networks armed with vast banks of personal data could be leveraged to profile voters and micro-target with personalized political ads, was something of a watershed moment in terms of elevating the issue of data-privacy and abuse into the public consciousness.

A year ago, we were so impressed with what was then called the Google Home Hub, we called it one of the top 10 best tech products of 2018, with one caveat. We wished it could be bigger. Now, the all-new, and yes, larger version is in stores, with a bigger 10-inch screen (up from 7 inches) higher price tag ($229, vs. $129) and a confusing new name. The new Google Nest Hub Max, with a ten-inch screen, back to back with the old Nest Hub, with a 7-inch screen. The old Home Hub is now called the Nest Hub, and the larger, new version is the Nest Hub Max.

Apple is attending Interspeech 2019, the world's largest conference on the science and technology of spoken language processing. The conference, of which Apple is a Platinum Sponsor, will take place in Graz, Austria from September 15th to 19th. For Interspeech attendees, join the authors of our accepted papers at our booth to learn more about the great speech research happening at Apple. Apple continues to build cutting-edge technology in the space of machine hearing, speech recognition, natural language processing, machine translation, text-to-speech, and artificial intelligence, improving the lives of millions of customers every day. If you're interested in opportunities to make an impact on Apple products through machine learning research and development, check out our teams at Jobs at Apple.

"Alexa, what is natural language processing?" Pose that question to Alexa – or Siri, Cortana, Google Assistant, or any other voice-activated digital assistant – and it will use natural language processing (NLP) to try to answer your question about, um, natural language processing. That makes Alexa and its ilk a natural example of NLP in action: NLP is a core technology that enables virtual assistants to process your verbal queries and respond with some degree of accuracy. But that doesn't necessarily define NLP; it just points to a popular real-world application of NLP. Plus, the voice assistant example is actually too narrow: Natural language processing isn't just about speech but also written text. Moreover, NLP is already ubiquitous, and your smartphone assistant is only one common example of its everyday use.

A: There are so many applications for conversational interfaces, from commerce to customer support. The challenge isn't finding an application for conversational interfaces, it's identifying customer pain points that might best be addressed with a conversational interaction. In most cases, a conversational interface is added as an additional means of interacting with a system, and right now you're seeing a lot of interesting experimentation going on. For example, KLM Airlines' Facebook Messenger chatbot lets you find flights by having a text chat with an AI Assistant. You can obviously still search for flights using their traditional interface, but the chat experience is definitely worth checking out.

From Google Home to Amazon Echo, Home AI systems are all the rage right now. These require "Smart Speakers" and tend to function mostly with devices that are Smart Home-ready (or have apps that provided added value like Smart Home connection). While these devices are really cool, there are limitations, namely that for Echo or Home to hear you, you need to be in the house. But recently, Mark Zuckerberg showed us that you don't need this hardware. Over the past year or so (for a sum total of about 100 hours) Zuckerberg has spent his off time creating a massively intelligent Smart Home System that he controls with nothing more than his computer and his Smart Phone.

Oracle today announced availability of its AI-trained voice with Oracle Digital Assistant. Now, enterprise customers can use voice commands to communicate with their enterprise applications to drive desired actions and outcomes, enriching the user experience with conversational AI, simplifying interactions and improving productivity. "Enterprises are demanding an AI-powered voice assistant that understands their specific vocabulary and enables naturally expressive interactions for its users," said Suhas Uliyar, vice president, AI and Digital Assistant, Oracle. "Most of all though, enterprises value a highly secure AI-powered voice assistant that stores their business' sensitive data in Oracle's second generation cloud infrastructure." Built on Oracle's next-generation infrastructure, Oracle Digital Assistant applies AI with deep semantic parsing for natural language processing (NLP), natural language understanding (NLU) and custom machine learning (ML) algorithms.

The pursuit of improved accuracy in recommender systems has led to the incorporation of user context. Context-aware recommender systems typically handle large amounts of data which must be uploaded and stored on the cloud, putting the user's personal information at risk. While there have been previous studies on privacy-sensitive and context-aware recommender systems, there has not been a full-fledged system deployed in an isolated mobile environment. We propose a secure and efficient on-device mechanism to predict a user's next intention. The knowledge of the user's real-time intention can help recommender systems to provide more relevant recommendations at the right moment. Our proposed algorithm is both context and sequence aware. We embed user intentions as weighted nodes in an n-dimensional vector space where each dimension represents a specific user context factor. Through a neighborhood searching method followed by a sequence matching algorithm, we search for the most relevant node to make the prediction. An evaluation of our methodology was done on a diverse real-world dataset where it was able to address practical scenarios like behavior drifts and sequential patterns efficiently and robustly. Our system also outperformed most of the state-of-the-art methods when evaluated for a similar problem domain on standard datasets.