The dominant, state-of-the-art collaborative filtering (CF) methods today mainly comprises neural models. In these models, deep neural networks, e.g.., multi-layered perceptrons (MLP), are often used to model nonlinear relationships between user and item representations. As opposed to shallow models (e.g., factorization-based models), deep models generally provide a greater extent of expressiveness, albeit at the expense of impaired/restricted information flow. Consequently, the performance of most neural CF models plateaus at 3-4 layers, with performance stagnating or even degrading when increasing the model depth. As such, the question of how to train really deep networks in the context of CF remains unclear. To this end, this paper proposes a new technique that enables training neural CF models all the way up to 20 layers and beyond. Our proposed approach utilizes a new hierarchical self-attention mechanism that learns introspective intra-feature similarity across all the hidden layers of a standard MLP model. All in all, our proposed architecture, SA-NCF (Self-Attentive Neural Collaborative Filtering) is a densely connected self-matching model that can be trained up to 24 layers without plateau-ing, achieving wide performance margins against its competitors. On several popular benchmark datasets, our proposed architecture achieves up to an absolute improvement of 23%-58% and 1.3x to 2.8x fold improvement in terms of nDCG@10 and Hit Ratio (HR@10) scores over several strong neural CF baselines.

In June, MIT Technology Review ranked the Chinese AI company as the 6th smartest company in the world, just behind Google's parent company Alphabet and also the highest ranked Chinese company on the list. In November, the Chinese government announced plans (in Chinese) to build national AI platforms in partnership with four companies. The three other companies chosen were Baidu, Alibaba and Tencent. But it hasn't always been smooth sailing for iFlytek. Founded in 1999, the company almost changed tracks to go into real estate after experiencing failed products, low revenues and difficulties in securing funding early on.

Artificial intelligence keeps barreling forward, and of all the sectors it will likely impact, we ought to think through autonomous vehicles, criminal justice and the media sooner than later. Those are the first three areas that a new AI-centered philanthropic fund is engaging first. The fund formed early this year with a $27 million pool of donations from the Knight and Hewlett foundations, Reid Hoffman, the Omidyar Network, and investor Jim Pallotta. Now it's announced its first round of payouts. The main grantees won't be a surprise, as the Berkman Klein Center at Harvard and the MIT Media Lab are the anchor institutions, and will share $5.9 million.

Artificial Intelligence Market, the foremost aim of the report is to provide accurate market estimation and to forecast the market on the basis of market segmentation. Significant segments of the market analyzed within the study are technology, end user, and region. The study also provides detailed analysis of top impacting factors and their influence over the market. The report provides the detailed market size with respect to five major regions namely North America, Europe, South America, Asia-Pacific, and Rest of the World. The report contains company profiles of key market leaders and their competitive strategies.

In a recent blog post and tweet, Google announced that it'd be launching a new Artificial Intelligence research centre to be opened later this year in Accra, Ghana. We're continuing to expand our @GoogleAI teams around the world. We'll be opening our first research center in Africa in #Ghana later this year! If you're a machine learning researcher interested in working in Accra, Ghana, apply: https://t.co/YgntDigTJt With this, Accra will be the first African city to join the likes of New York, Montreal, Tokyo, San Francisco, Paris, Beijing, Zurich, Toronto, Seattle, Cambridge/Boston, and Tel Aviv/Haifa, in hosting Google AI centres.

While being a constant learner has its own perks in the industry you're in, it may have long-standing repercussions in the world of AI and automation. When factory workers get automated and replaced for something cheaper and more effective, their skills become inadequate to survive. They then defer to other industries or make other industries more competitive with cheaper labour. That's the true impact of automation that isn't being addressed these days. Research by IT giant Infosys and Future Foundation found that teens living in countries such as India, UK, USA, Australia, France and other leading economies have a significant fear of AI. The youth of these countries believe that their future jobs will be automated in the next 10 years.

On June 10, a car crashed into a supermarket in Shibukawa, Gunma Prefecture, injuring 14 people. At first the incident sounded like yet another elderly person losing control of a vehicle and causing destruction, but then it transpires that the driver was a 55-year-old man. Does that count as elderly? Police arrested the man on suspicion of negligent driving resulting in injuries. Reports say he bore down on the accelerator after he felt the right side of his body go numb, a condition that could be age-related.

The work, reported May 31 in Science, is a step toward creating artificial skin for prosthetic limbs, to restore sensation to amputees and, perhaps, one day give robots some type of reflex capability. "We take skin for granted but it's a complex sensing, signaling and decision-making system," said Zhenan Bao, a professor of chemical engineering and one of the senior authors. "This artificial sensory nerve system is a step toward making skin-like sensory neural networks for all sorts of applications." This milestone is part of Bao's quest to mimic how skin can stretch, repair itself and, most remarkably, act like a smart sensory network that knows not only how to transmit pleasant sensations to the brain, but also when to order the muscles to react reflexively to make prompt decisions. The new Science paper describes how the researchers constructed an artificial sensory nerve circuit that could be embedded in a future skin-like covering for neuro-prosthetic devices and soft robotics.

After a New York Times reporter published a bombshell story on how Facebook intentionally shared personal information of its users with over 60 different device makers – including the two largest, Apple and Samsung – in order to create "Facebook-like experiences" on those devices, U.S lawmakers and regulators are asking Facebook for answers. What they see is a clear pattern of abuse, in which Facebook pledges over and over again that it has figured out its data sharing problem, but new revelations continually come to light. In its defense, Facebook says that the data sharing partnerships with mobile device manufacturers were only intended to make it easier for these global device makers to build software incorporating Facebook functionality into their smartphone devices. According to Ime Archibong, Facebook Vice President of Product Partnerships, the data-sharing program was controlled and monitored by Facebook from the very beginning, and all integrations with the device manufacturers were personally approved by Facebook. Moreover, while personal user data might have been shared with these device makers, Facebook says it was only used in order to give users access to Facebook messages and notifications on their mobile phones. But the New York Times report suggests that the data-sharing program went far beyond this.

The standout speaker on artificial intelligence (AI) was Dr. Noah Silverman, founder of Helios.ai, a consulting firm in Hong Kong.