As a general rule of thumb, the law and government are slow-moving and deliberate. That's really handy for important things that you have to get right, but the trouble is that disruptive technology tends to move much faster. That's bad enough if the disruptive technology you're talking about is (say) the sharing economy, but it's more serious when it's something that Elon Musk once described as "potentially more dangerous than nukes". That thing is artificial intelligence. And while it's hard to feel too threatened when it's your Amazon Echo failing to understand you saying "Play REM" for the tenth time in a row, the threat – potentially – is a real one.

Representing documents is a crucial component in many NLP tasks, for instance predicting aspect ratings in reviews. Previous methods for this task treat documents globally, and do not acknowledge that target categories are often assigned by their authors with generally no indication of the specific sentences that motivate them. To address this issue, we adopt a weakly supervised learning model, which jointly learns to focus on relevant parts of a document according to the context along with a classifier for the target categories. Derived from the weighted multiple-instance regression (MIR) framework, the model learns decomposable document vectors for each individual category and thus overcomes the representational bottleneck in previous methods due to a fixed-length document vector. During prediction, the estimated relevance or saliency weights explicitly capture the contribution of each sentence to the predicted rating, thus offering an explanation of the rating. Our model achieves state-of-the-art performance on multi-aspect sentiment analysis, improving over several baselines. Moreover, the predicted saliency weights are close to human estimates obtained by crowdsourcing, and increase the performance of lexical and topical features for review segmentation and summarization.

While modern day web applications aim to create impact at the civilization level, they have become vulnerable to adversarial activity, where the next cyber-attack can take any shape and can originate from anywhere. The increasing scale and sophistication of attacks, has prompted the need for a data driven solution, with machine learning forming the core of many cybersecurity systems. Machine learning was not designed with security in mind, and the essential assumption of stationarity, requiring that the training and testing data follow similar distributions, is violated in an adversarial domain. In this paper, an adversary's view point of a classification based system, is presented. Based on a formal adversarial model, the Seed-Explore-Exploit framework is presented, for simulating the generation of data driven and reverse engineering attacks on classifiers. Experimental evaluation, on 10 real world datasets and using the Google Cloud Prediction Platform, demonstrates the innate vulnerability of classifiers and the ease with which evasion can be carried out, without any explicit information about the classifier type, the training data or the application domain. The proposed framework, algorithms and empirical evaluation, serve as a white hat analysis of the vulnerabilities, and aim to foster the development of secure machine learning frameworks.

NASA is developing a robot that could go where no robot has gone before: over and under difficult terrain on Mars or another planet. The PUFFER -- Pop-Up Flat Folding Explorer Robot -- could traverse ground that a standard rover would get caught on, making a helpful travel companion. The space administration says its Jet Propulsion Laboratory in California is working on the little trooper, which will be lightweight and "was inspired by origami." A NASA video (below) shows how it's done: The robot can fold into itself to squeeze underneath short obstacles or use its tailfin as leverage to propel itself up and over them. And it could last a long time because it has solar panels on its underside so it can recharge. PUFFER wouldn't go on a solo journey to Mars, but would be a teammate that could tag in when a larger rover faces a topographical blockade.

Ten minutes from downtown Holland, Michigan, there is a massive $300 million dollar plant that manufactures advanced battery cells for electric vehicles. When it was first announced in 2009 that LG Chem would be setting up a subsidiary in the small town of 34,000 people, government officials planned for an economic revitalization. They spared no expense to woo the Korean giant. The local, state, and federal government awarded over $250 million in tax subsidies, grants, and concessions, promising that Michigan would become "the world capital for advanced batteries." The plan amounted to spending $750,000 for a job that paid only $54,000 a year.

Wherever you fall along these lines, you want to make sure that your taxes are accurately being prepared to ensure that you experience no issues with the IRS. H&R Block has introduced a new partnership with IBM Watson to bring its customers a new and improved tax preparation experience. Watson is an artificial intelligence technology that continuously learns from the data fed into its system. As more customers' tax information is processed by Watson, it will apply the knowledge it has retained in order to give tax preparers the best advice for their customers. The technology is so in-depth because it was given a large amount of data about tax laws and codes, allowing it to gain deeper insight into the varied situations that affect an individual's tax return.

Amazon has successfully conducted drone deliveries in England, but consumers across the Atlantic have yet to witness it in action – until now. The e-commerce giant showed off its Prime Air drone to the public during a conference in California by dropping off a box containing a bottle of sunscreen. The demonstration brings Amazon one-step closer to commercializing its service, which it said will deliver packages in 30 minutes or less by drones flying up to 50 miles per hour. The firm said its drones will deliver packages 30 minutes or less while flying at speeds of 50 mph. It is understood Amazon will use'highly automated' drones equip with GPS to locate the exact address.

PUFFER's project manager Jaakko Karras conjured up its design back when he was experimenting with origami while working on robots at UC Berkeley's Biomimetic Millisystem Lab. The team replaced the paper he used in his design with printed circuit boards and then 3D printed wheels for the machine. PUFFER's latest set of wheels have treads and can inch forward one wheel at a time, so it can climb slopes. They can also fold over the robot's body if it needs to squeeze into a tiny opening. While the current prototype can already drive up to 2,050 feet on one charge and withstand extremely high temperatures, the team has more plans for the machine.

Known as Information Warrior 17, it will take place between 26 March and 6 April in various locations in and around Scotland. It is intended to drive the development of cutting edge technology in the Navy, including artificial intelligence, to put the UK at the forefront of Information Warfare. It will also test the defensive capabilities of ships and submarines against cyber attacks, which are as real a threat in the modern age as traditional weapons like rockets, missiles, and torpedoes. Admiral Sir Philip Jones, First Sea Lord, said: "We are living in a data-driven age in which our adversaries are already exploiting the potential of Information Warfare, and we must respond in kind." The Royal Navy has expressed an interest in using AI technology to develop a "Ship's Mind" at the centre of its warships, enhancing efficiency and allowing for fast and complex decisions to be made automatically.

The Devon and Cornwall Police force is to become the first in the UK with a permanent, 24-hour drone assistance unit. The flying fuzz will be on hand to search for missing persons, seek out suspects and generally provide an eye in the sky whenever needed, gathering intel at crime scenes and responding to road accidents. The dedicated unit, which will also help out police in neighbouring Dorset, is set to launch this summer after a new "drone manager" is hired to oversee the nine sites the coppercopters will operate out of.