Vancouver-based Responsive Capital Management is looking for Asian financial institutions interested in adapting its artificial intelligence to the back end of wealth management. Although Responsive markets itself in public as an AI-driven tool for investing, its business model to date has relied on leasing its technology to other wealth managers to improve their operations. This raises the question of a robo-advisor's true value. Is it the investment decisions, or the user interface and automation of back-office operations? "We want to help wealth managers compete through a better client experience and outcomes," said Davyde Wachell, the company's CEO.

The skip-gram neural network model is actually surprisingly simple in its most basic form. Train a simple neural network with a single hidden layer to perform a certain task, but then we're not actually going to use that neural network for the task we trained it on! Instead, the goal is actually just to learn the weights of the hidden layer–we'll see that these weights are actually the "word vectors" that we're trying to learn. We're going to train the neural network to do the following. Given a specific word in the middle of a sentence (the input word), look at the words nearby and pick one at random.

When Hollywood inevitably makes a biopic about Travis Kalanick, the embattled CEO of Uber--the most valuable private company in the world--screenwriters will have a hard time toning down reality to make it sound halfway believable. In the past few months alone, details have emerged about stolen trade secrets from Google regarding self-driving cars, sneaky tracking techniques for evading authorities, and, most alarmingly, allegations of ignored sexual harassment complaints and the most noxious office environment west of Wall Street. There were even reports that a top executive obtained the medical report of a woman who was raped by an Uber driver--and that CEO Travis Kalanick viewed the document. It all culminated in the company tapping former US attorney general Eric Holder to conduct an independent investigation into Uber's policies and culture. On Tuesday morning, during a highly anticipated all-hands meeting at Uber's headquarters in San Francisco, the board of directors shared the results of Holder's investigation: a 13-page document filled with recommendations for how to fix Uber's culture, including ceding some of Kalanick's power to a chief operating officer, who has yet to be hired, one of more than a dozen executive roles that are now empty.

In the 1995 film'Batman Forever,' the Riddler used 3-D television to secretly access viewers' most personal thoughts in his hunt for Batman's true identity. By 2011, the metrics company Nielsen had acquired Neurofocus and had created a'consumer neuroscience' division that uses integrated conscious and unconscious data to track customer decision-making habits. What was once a nefarious scheme in a Hollywood blockbuster seems poised to become a reality. Researchers can use P300, a brain signal that alerts us to important changes in our environment and holds what is important or relevant to you. Ethical issues arise when BCIs are able to'read' someone's mind who isn't actively cooperating - or giving consent Researchers can use P300, a kind of brain signal that alerts us to important changes in our environment, in an experimental setting to determine what is important or relevant to you.

Fearing the appropriation of technologies that are said to affect US national security, a federal agency in Washington is considering limiting Beijing's ability to invest in Silicon Valley companies and startups, as China seeks to modernize its military forces. The Committee on Foreign Investment in the United States (CFIUS), a secretive group that documents the purchase of US companies by foreign entities, is poised to strengthen its regulatory role, particularly regarding China, based on a call from US lawmakers to improve national security. New technologies, including machine learning and artificial intelligence currently in development in the high-tech Silicon Valley corridor in California are increasingly fertile ground for Chinese investment, and CFIUS wants to make sure the US isn't giving away the farm. According to the unreleased Pentagon report, which was viewed by Reuters, China seeks to use new US tech to upgrade its military, and CFIUS has been tasked with stepping up its oversight, as lawmakers demand greater security. "We're examining CFIUS to look at the long-term health and security of the US economy, given China's predatory practices," said an official with the Trump administration who was not authorized to speak publicly, according to Reuters.

This study proposes a fully convolutional network (FCN) model for raw waveform-based speech enhancement. The proposed system performs speech enhancement in an end-to-end (i.e., waveform-in and waveform-out) manner, which dif-fers from most existing denoising methods that process the magnitude spectrum (e.g., log power spectrum (LPS)) only. Because the fully connected layers, which are involved in deep neural networks (DNN) and convolutional neural networks (CNN), may not accurately characterize the local information of speech signals, particularly with high frequency components, we employed fully convolutional layers to model the waveform. More specifically, FCN consists of only convolutional layers and thus the local temporal structures of speech signals can be efficiently and effectively preserved with relatively few weights. Experimental results show that DNN- and CNN-based models have limited capability to restore high frequency components of waveforms, thus leading to decreased intelligibility of enhanced speech. By contrast, the proposed FCN model can not only effectively recover the waveforms but also outperform the LPS-based DNN baseline in terms of short-time objective intelligibility (STOI) and perceptual evaluation of speech quality (PESQ). In addition, the number of model parameters in FCN is approximately only 0.2% compared with that in both DNN and CNN.

We present a probabilistic framework for overlapping community discovery and link prediction for relational data, given as a graph. The proposed framework has: (1) a deep architecture which enables us to infer multiple layers of latent features/communities for each node, providing superior link prediction performance on more complex networks and better interpretability of the latent features; and (2) a regression model which allows directly conditioning the node latent features on the side information available in form of node attributes. Our framework handles both (1) and (2) via a clean, unified model, which enjoys full local conjugacy via data augmentation, and facilitates efficient inference via closed form Gibbs sampling. Moreover, inference cost scales in the number of edges which is attractive for massive but sparse networks. Our framework is also easily extendable to model weighted networks with count-valued edges. We compare with various state-of-the-art methods and report results, both quantitative and qualitative, on several benchmark data sets.

A host of bizarre biomedical robots turned up at ICRA 2017, IEEE's flagship robotics conference, which took place earlier this month in Singapore. We saw swallowable robots that poke the stomach with needles and worm-like robots that explore the colon. Equal parts unnerving and fascinating, these bots aim to help people--perhaps in ways we hope we never need. This capsule robot innocuously tumbles around inside your stomach--until it reaches suspicious-looking tissue. Then, like an EpiPen on steroids, the soft-bodied bot whips out a needle and jabs that spot inside your stomach in ten fast pumping movements.

U.S. officials reportedly are rethinking the advisability of allowing the Chinese to invest in sensitive technologies seen as vital to national security. Reuters reported Wednesday U.S. officials are concerned such cutting-edge technologies as artificial intelligence and machine learning could be used by the Chinese to augment their military capabilities and achieve greater advancements in strategic industries. Technology is the fastest growing industry in the United States, and China has funneled $45.6 billion into U.S. acquisitions and Greenfield investments in the last year, Rhodium Group found. That investment is expected to double this year. Read: What Is Artificial Intelligence?

Montreal-based Element AI, a key player in the city's burgeoning artificial-intelligence sector, has clinched a major financing deal to fund future growth and job creation. Element is set to announce on Wednesday that it has raised US$102-million from a group of investors led by San Francisco venture capital fund Data Collective (DCVC). The deal is the largest Series A funding round for an AI company in history, Element says. The investment will allow Element to "accelerate its capabilities and invest in large-scale AI projects internationally, solidifying its position as the largest global AI company in Canada and creating 250 jobs in the Canadian high tech sector by January 2018," it said in a news release. Element was founded last year by tech entrepreneurs Jean-François Gagné and Nicolas Chapados, Montreal venture capital fund Real Ventures, and Université de Montréal AI scientist Yoshua Bengio.