Apple has unveiled all the new features heading to iPhones and iPads at its developer conference in San Francisco on Monday, including speed boost for even older devices, improved privacy and a host of new features. The look of iOS 12 will be very familiar, with the company focusing on improving the experience and the underlying software rather than simply splashing on a new coat of paint. The new iOS 12 will be available for any device running iOS 11 now, which means any Apple smartphone from the iPhone 5S or newer, and any iPad from the iPad mini 2 and iPad Air or newer, plus the sixth generation iPod touch. The developer version is available now, but the first public beta is due later in June, for those eager to test it as soon as possible. A final release will be available in September for everyone else.

Let's face it, the future isn't turning out to be what we were promised in decades past. No flying cars, and the closest thing to robot butlers are Siri and Alexa. Don't get me wrong, they're handy in their ways: suggesting nearby Thai food or tending to virtual shopping carts as we yell our grocery lists across the room. In fact, nothing that's commercially available really is -- at least not yet. In marketing, for example, all kinds of martech come with an AI label.

Asus just showed the world Project Precog at Computex 2018, and I'm drooling all over my keyboard. Imagine a slim laptop with dual touchscreens, one of which can transform into an adaptive keyboard and trackpad combo that can dynamically change the position of keys based on where your fingers are. Imagine a laptop that learns your work routines and can conserve battery life to anticipate an upcoming video conference. Asus' Project PreCog in Stand Mode Asus is also making waves at Computex with their recently announced ROG Phone. Project Precog (likely named after the precognitives from the film Minority Report) will ship with Microsoft Cortana and Amazon Alexa built in, and can function in 4 different configurations: stand mode, book mode, tent mode and flat mode.

Digital assistants have the potential to be the bridge between smart homes, smart cars, smartphones, PCs, wearables and other devices that we use in our personal and professional lives. They could make our lives better organised, and our devices and services much easier to use. What are the promises and challenges of this brave new world of intelligence augmentation? Join us at "A.I. everywhere: How digital assistants will transform our lives" on 5 June 2018 at the Centre for Global Dialogue in Rüschlikon, outside of Zurich. The conference will connect networks of artificial intelligence research and practice with thought leaders and decision makers from society, business and government.

Amazon is introducing a feature that will allow Alexa to suggest voice apps when you don't know what app to ask for. Instead, you will be able to simply tell Alexa what you want to accomplish to receive recommendations of skills to help you achieve that goal. Now in beta, the CanFulfillIntentRequest interface can be used by the creators of Alexa skills in the U.S. to alert Amazon to the kinds of questions their skill may be able to answer or queries the skill is able to fulfill. Amazon's Alexa Skill Store now has more than 30,000 voice apps, and getting users' attention can be something of a challenge. The intent request introduced today should help users discover more voice apps and connect developers making skills with a larger audience.

My regular readers will recognize Zaid's name. In 2012, at LegalTech New York, I used his very cool "The Mashup App" which was a vision for the future of the web: a web where we control our personal information and curate our digital data -- from memories to knowledge -- from all from our personal devices. The app is a personal database in which you save your digital data. You can save all types of data including web, PDF, images, video, audio, location, and time data. Since your personal database is on your device, you can save everything that is important to you – in this case, a log of every place I visited during my 3 days at LegalTech that year, plus the 3 days after in NYC at client meetings. From this I could generate a "diary" of my day, or my week and I could also associate any document (such as a PDF or a restaurant receipt or dry cleaning bill) I had to that "pin" location and/or day.

SAN JOSE, CALIFORNIA – Apple will offer more ways for people to limit the time they spend on iPhones while introducing features designed to make its products even more indispensable. The paradox emerged Monday as Apple executives previewed new versions of free software due out this fall. The forthcoming controls are aimed at addressing criticism that devices are becoming increasingly addictive and distracting, especially for children during their formative years. Yet Apple made it clear it also hopes to make its devices and services even more alluring -- and potentially irresistible -- by creating new avenues for its digital assistant, Siri, to serve as a backup brain for its users. The company is also creating more entertainment options and new ways to communicate, including a way for up to 32 people to join a group video chat through FaceTime. People have become so dependent on technology that it's unlikely any company will be able to solve the addiction problem, but they can help keep it from getting worse, Gartner analyst Brian Blau said.

Apple's Siri has fallen behind its virtual assistant competition. Google's Assistant expertly surfaces information, while Amazon's Alexa works with a staggering number of third-party apps for a broad variety of capabilities. Apple isn't admitting defeat, though: Siri played a prominent role at WWDC, the company's "Worldwide Developers Conference," on Monday. Specifically, Apple is finally tackling the issue of customization with its personal digital assistant: Making Siri do more, proactively, to make your day easier. Apple is primarily accomplishing this with a new tool called Siri Shortcuts, a sort of IFTTT built straight into iOS for personalizing and automating Siri commands and functions.

Apple AAPL 0.84% introduced at least seven things at its annual Worldwide Developer Conference that could actually make your life better. After a year filled with bug fixes and heavy user criticism about everything from fragile MacBook keyboards to Siri's incompetence, Apple's focus was on improving existing things rather than introducing new ones. It didn't do enough, at least not during the keynote, to address the bugs and shortcomings of its core products. But it did show us it had some real user needs in mind with these improvements. Facebook and others have recently come under fire for tracking you online, often without you knowing.

Recent advancements in deep neural networks for graph-structured data have led to state-of-the-art performance on recommender system benchmarks. However, making these methods practical and scalable to web-scale recommendation tasks with billions of items and hundreds of millions of users remains a challenge. Here we describe a large-scale deep recommendation engine that we developed and deployed at Pinterest. We develop a data-efficient Graph Convolutional Network (GCN) algorithm PinSage, which combines efficient random walks and graph convolutions to generate embeddings of nodes (i.e., items) that incorporate both graph structure as well as node feature information. Compared to prior GCN approaches, we develop a novel method based on highly efficient random walks to structure the convolutions and design a novel training strategy that relies on harder-and-harder training examples to improve robustness and convergence of the model. We also develop an efficient MapReduce model inference algorithm to generate embeddings using a trained model. We deploy PinSage at Pinterest and train it on 7.5 billion examples on a graph with 3 billion nodes representing pins and boards, and 18 billion edges. According to offline metrics, user studies and A/B tests, PinSage generates higher-quality recommendations than comparable deep learning and graph-based alternatives. To our knowledge, this is the largest application of deep graph embeddings to date and paves the way for a new generation of web-scale recommender systems based on graph convolutional architectures.