Amazon Echo owners use its voice-based digital assistant Alexa for a variety of purposes. Playing music and listening to the news typically top the list, but smart home control, general knowledge queries, and things like timers and alarms are also popular. Among its many built-in and third-party skills, one of the features least used by Echo owners is probably the one its maker wishes consumers used most: purchasing products through Amazon. Researchers have been predicting huge growth in shopping with virtual assistants. By 2022, the voice shopping space is supposed to be a $40 billion market.

It's All About EmojisEven before the event kicked off, CEO Sundar Pichai assured fixing bugs in things that matter the most, like burger emoji and floating foam on beer mug emoji. Better and smoother updates in AI, Assistant, Photos, News will soon make lives easy for most people. Here's a quick round-up of what Google has in store for your in the coming few days, weeks and months. The AI will convert JPEG to PDF. Google has trained its AI to help all the photography enthusiasts enjoy great features like adding colour to black and white images, making pictures pop by adjusting backdrop, suggesting brighter options for an under-processed picture.

Maybe you haven't noticed, but artificial intelligence has arrived. Gradually, over the last decade or so, it's become so ingrained into our everyday lives that most people don't think twice about it. Spotify assembles a "Discover Weekly" playlist tailored to your tastes. Netflix serves you options for your next binge-watching marathon. Alexa answers your questions and plays that nifty Spotify playlist on command.

Item recommendation is a personalized ranking task. To this end, many recommender systems optimize models with pairwise ranking objectives, such as the Bayesian Personalized Ranking (BPR). Using matrix Factorization (MF) --- the most widely used model in recommendation --- as a demonstration, we show that optimizing it with BPR leads to a recommender model that is not robust. In particular, we find that the resultant model is highly vulnerable to adversarial perturbations on its model parameters, which implies the possibly large error in generalization. To enhance the robustness of a recommender model and thus improve its generalization performance, we propose a new optimization framework, namely Adversarial Personalized Ranking (APR). In short, our APR enhances the pairwise ranking method BPR by performing adversarial training. It can be interpreted as playing a minimax game, where the minimization of the BPR objective function meanwhile defends an adversary, which adds adversarial perturbations on model parameters to maximize the BPR objective function. To illustrate how it works, we implement APR on MF by adding adversarial perturbations on the embedding vectors of users and items. Extensive experiments on three public real-world datasets demonstrate the effectiveness of APR --- by optimizing MF with APR, it outperforms BPR with a relative improvement of 11.2% on average and achieves state-of-the-art performance for item recommendation. Our implementation is available at: https://github.com/hexiangnan/adversarial_personalized_ranking.

The past 100 years have seen an incredible rise in technology advancement, and Artificial Intelligence is part of it. While humans strive to make their lives easier, like using self-driving cars or relying on Cortana, Alexa[1] and Siri to do their daily tasks, the computing technologies can also be used for far worse purposes. While others worry about machines taking over the world and destroying humanity, security researchers at IBM[2] considered a far likely scenario in the near future and created DeepLocker – an AI-powered malware that is capable of using evasive techniques to obfuscate its presence and avoid security software entirely. The most notorious malware like WannaCry, Trickbot,[3] and Zeus devastated the most influential organizations, resulted in millions of damages, and disrupted the work of vital sectors like hospitals all over the world. While such attacks can be prevented by using safety measures and adequate security software, the AI-based malware can result in an attack the world has never seen before.

The fast-rising power and sophistication of artificial intelligence is transforming how insurers engage with their customers. It is dramatically enhancing the experience insurance providers can offer their policyholders. Insurtech start-ups Lemonade, Insurify and Spixii, for example, are deploying intelligent virtual assistants to deliver a powerful customer experience and innovative digital services. Using artificial intelligence to delight customers is not the sole preserve of insurtechs. Large insurers, including Allianz, Credit Agricole, PNB MetLife, GEICO and USAA, are also applying artificial intelligence to heighten the customer experience delivered by their digital distribution channels.

Education has always been a hot topic among intellectuals and reformers. It has seen quite a change in the last decade or so, but not significant enough to get noticed. The new era of learning is still focused on keeping students in the classroom in the hopes that they will bring a better future to themselves and to society as a whole. The current education system has always been focused on a batch study where individual growth is never focused on. With the expansion of the internet, things have changed drastically, as now, anyone can do self-study using YouTube, Udacity, or TED.

Professor Phil Cohen, Director of the Laboratory for Dialogue Research, at Monash University, Faculty of Information Technology, will be a keynote speaker at the Digital A.I Summit, in Melbourne on August 28, 2018. He will discuss the strengths and weaknesses of current "conversational A.I" technology, which is used in today's digital assistants (e.g., Apple Computer's Siri, Google's Google Now, IBM's Watson, and Microsoft's Cortana, etc.), as well as for general classes of applications such as customer service. He will provide a way forward that promises to overcome their limitations to build systems that can participate in flexible, collaborative dialogues that help users to achieve their goals. The Digital A.I Summit is Australia's premier event for bringing together industry leaders and provides a collection of exclusive keynotes and expert panels explaining AI and how it is rapidly transforming many Australian workplaces to significantly improve their productivity. The Digital A.I Summit is a one-day conference and is run in conjunction with the Victorian Government's Digital Innovation Festival.

Some of us have been waiting our entire careers for better calendaring options. How many meetings do you have a week? According to Trello, the average meeting requires 3.5 emails to schedule. So if you are scheduling approximately 8 meetings a week, spending 3–5 minutes on each email, that comes to about an hour a week. If you work 5 days a week, that averages out to an entire day each month of simply scheduling meetings.

Couples, married or not, tend to have similar ages, educations, levels of attractiveness and a host of other characteristics. This could mean that people try to find partners who "match" their stats. On the other hand, it could mean that people try to find slightly more attractive mates – which results in the same pattern as the most desirable partners pair off, followed by the next most desirable, and so on.