This paper presents preliminary work on learning the search heuristic for the optimal motion planning for automated driving in urban traffic. Previous work considered search-based optimal motion planning framework (SBOMP) that utilized numerical or model-based heuristics that did not consider dynamic obstacles. Optimal solution was still guaranteed since dynamic obstacles can only increase the cost. However, significant variations in the search efficiency are observed depending weather dynamic obstacles are present or not. This paper introduces machine learning (ML) based heuristic that takes into account dynamic obstacles, thus adding to the performance consistency for achieving real-time implementation.

Deep learning models for graphs have achieved strong performance for the task of node classification. Despite their proliferation, currently there is no study of their robustness to adversarial attacks. Yet, in domains where they are likely to be used, e.g. the web, adversaries are common. Can deep learning models for graphs be easily fooled? In this work, we introduce the first study of adversarial attacks on attributed graphs, specifically focusing on models exploiting ideas of graph convolutions. In addition to attacks at test time, we tackle the more challenging class of poisoning/causative attacks, which focus on the training phase of a machine learning model. We generate adversarial perturbations targeting the node's features and the graph structure, thus, taking the dependencies between instances in account. Moreover, we ensure that the perturbations remain unnoticeable by preserving important data characteristics. To cope with the underlying discrete domain we propose an efficient algorithm Nettack exploiting incremental computations. Our experimental study shows that accuracy of node classification significantly drops even when performing only few perturbations. Even more, our attacks are transferable: the learned attacks generalize to other state-of-the-art node classification models and unsupervised approaches, and likewise are successful even when only limited knowledge about the graph is given.

One example of a sci-fi struggle to define AI consciousness is AMC's "Humans" (Tues. At this point in the series, human-like machines called Synths have become self-aware; as they band together in communities to live independent lives and define who they are, they must also battle for acceptance and survival against the hostile humans who created and used them. But what exactly might "consciousness" mean for artificial intelligence (AI) in the real world, and how close is AI to reaching that goal? Philosophers have described consciousness as having a unique sense of self coupled with an awareness of what's going on around you. And neuroscientists have offered their own perspective on how consciousness might be quantified, through analysis of a person's brain activity as it integrates and interprets sensory data.

When we think about artificial intelligence, it's usually something involving robot overloads and the answer to how many tablespoons are in a cup. Less often do we think about their emotional intelligence, something so intrinsic to human interaction that we take it for granted. Pamela Pavliscak, CEO of Change Sciences to took the stage at TNW Conference 2018 to discuss the "emotion revolution" we'll see in our machines and software within the next years. For AI and virtual assistants to make the most positive impact, they'll need to know how to understand and behave within the framework of our very human emotional cues. This concept isn't new; technology companies have tried to humanize technology for ages, to varying degrees of success.

Ocado, the UK leader in home-delivered groceries from robot-run distribution centers, has established a licensing deal with US grocery chain Kroger (NYSE:KR) whereby Kroger will take a 5% stake in Ocado – an investment valued at $247.5 million and Ocado will help Kroger set up systems to manage online ordering, fulfillment and delivery operations utilizing Ocado-proven technologies. Ocado will see the Kroger chain build up to 20 Ocado-designed robot-run warehouses over its first three years. In a recent letter to Kroger stockholders, CEO Rodney McMullen said that Kroger is redeploying capital to emphasize improving its digital capabilities and enabling customers to shop in the store, by ordering online and picking up their order at the store, or getting their groceries delivered to their homes. Although McMullen didn't single out Amazon or any other competitors in the supermarket arena, Amazon's acquisition of Whole Foods and Walmart's price-cutting moves and partnering with online grocery deliver service Instacart are rapidly changing the landscape of grocery shopping. "Kroger is right in the middle of such a reinvention," McMullen said in the shareholder letter.

Paul Steinberg, CTO of Motorola Solutions, speaks to Sam Fenwick about his company's efforts to use AI and machine learning to bring the right data to the user in the right way Paul Steinberg presides over a huge range of research and development activities, ranging from RF engineering and wireless network architectures to drones and robotics. He also manages Motorola Solutions Venture Capital's portfolio and plays a key role in managing Motorola Solutions' intellectual property. One of the things the company is moving towards is a virtual partner – a combination of AI and natural language processing, which allows someone in the field to verbally request information and give commands without talking to a human. Part of the thinking behind this is that people speak faster than they can type, and the need for field workers to stay aware of their surroundings. "The way you and I consume [mobile data] is a slab of black glass, [but the] fundamental imperative [for a police officer, etc] is eyes-up, hands-free. That slab of black glass [is] exactly the opposite: eyes-down, hands-busy. A big part of how we're navigating this problem is around ethnographics and human factors research – living a day in the life of our users and then [working] with the technologists and designers."

IBM CEO Virginia Rometty has announced that in the next two years the company is planning to create 1,800 jobs in France in the fields of Artificial Intelligence (AI), blockchain, and the Internet of Things (IoT), Le Monde reported May 23. The announcement was made at the Tech for Good summit in Paris, which was hosted by the President of France Emmanuel Macron. Pursuing the idea of making France a "center of excellence" dedicated to artificial intelligence, the tech giant is looking to hire 1,800 specialists in France in areas including blockchain, AI, and IoT. This includes at least 400 research jobs that were announced in January. In their efforts to expand operations in France, IBM is cooperating with major clients such as Crédit Mutuel, Orange Bank, Generali, SNCF, and LVMH.

Owkin, a medical research machine learning startup, has announced a new investor in the form of GV (formerly Google Ventures), which has now joined as a late entrant to Owkin's series A round. Founded in 2016, Owkin's platform leverages deep learning algorithms to help clinical researchers across academia, medicine, and the pharmaceutical industries develop predictive models and expedite drug development throughout the whole process. The platform, dubbed Socrates, integrates genomics, clinical data, and biomedical images to identify characteristics, or "biomarkers," associated with diseases. "There is a constant race happening between the data at hand and the knowledge we gain from it," noted Owkin CEO and cofounder Thomas Clozel. "At Owkin, our goal is to augment doctors' and researchers' capabilities in transforming data into knowledge and prediction, and achieve breakthrough medical moments such as the discovery of a new biomarker or target that could transform how patients are treated."

The European Union could spend up to £440 million ($590 million) on killer robots that wage warfare without the need for human assistance. Officially known as Lethal Autonomous Weapons (LAWs), the robots use artificial intelligence to target and kill enemies without human involvement. Brussels has decided to allow bankrolling of the controversial machines through the EU defence fund despite MEPs' attempts to bar LAWs from the kitty. The European Union could spend up to £440 million ($590 million) on killer robots that wage warfare without the need for human assistance. The parliament had wanted to block EU subsidies of the weapons but conceded in talks on Tuesday in order to strike a compromise, two sources who were in the room told the EUObserver.

IBM has a clear strategy towards Open Tech AI. I'm sure you remember back in 2011 when IBM Watson defeated the two world champions in Jeopardy. Apart from being backed by the awesome number of 2,880 IBM POWER7 cores providing 11,520 hyper-threads and 16 TB main memory, IBM Watson was running on Linux and using Hadoop. A lot of things have happened since then, and we are at a stage where IBM is one of the world leaders in AI Technology and Services. But what I'm especially proud of is IBM's clear strategy to create, support, and enhance Open Tech AI.