Incuspaze, a Gurgaon-based co-working and incubation centre, will launch an incubation programme for startups in artificial intelligence, machine learning, IoT and big data, the company said in a statement on Monday. The 6,000 sq ft centre was launched by UK-based angel investor Sanjay Choudhary last week. Incuspaze will invest between Rs 1 -5 lakh in five to six startups in its batch, and will also offer parallel services such as marketing, accounting and legal. "We are building a global self-sustainable ecosystem for startups and entrepreneurs. We are not only providing a co-working space, but also investor support, mentoring, allied services, global partnerships and to ensure peak performance for all startup founders," said Choudhary in the statement. Choudhary said Incuspaze will enable startups to accelerate product/service development by implementing lean startup methodologies through calculated risk-taking.

NAGOYA – Toyota Motor Corp. and Suzuki Motor Corp. have agreed to form a tie-up in advanced technology development and other operations, sources close to the matter said Saturday. The two automakers will continue to discuss whether to expand the partnership to include a capital alliance, the sources said. The comprehensive tie-up comes after Toyota, Japan's biggest automaker by volume, and Suzuki, a small-car specialist, said in October they would start talks on how they could join forces. The deal is expected to be announced Monday, according to the sources. The global auto industry is facing soaring costs to meet stricter emissions regulations and develop advanced safety technology for electric vehicles and autonomous driving systems.

The 2012 publication Race against the Machine makes the case that the digitalization of work activities is proceeding so rapidly as to cause dislocations in the job market beyond anything previously experienced [1]. Unlike past mechanization/automation, which affected lower-skill blue-collar and white-collar work, today's information technology affects workers high in the education and skill distribution. Machines can substitute for brains as well as brawn. On one estimate, about 47% of total US employment is at risk of computerization [2]. If you doubt whether a robot or some other machine equipped with digital intelligence connected to the internet could outdo you or me in our work in the foreseeable future, consider news reports about an IBM program to "create" new food dishes (chefs beware), the battle between anesthesiologists and computer programs/robots that do their job much cheaper, and the coming version of Watson ("twice as powerful as the original") based on computers connected over the internet via IBM's Cloud [3]. On the darker side, you do not have to be paranoid to be paranoid about the potential technologies that the super-secret computers of the US National Security Agency (NSA) have on their digital drawing-boards.

The Falcons are facing 3rd and goal on the Patriots' 5 yard line. Matt Ryan takes the snap and hands off to Devonta Freeman, already running hard at the goal line. Then, with a crunch audible to the topmost rows of NRG Stadium, Freeman is brought down by Dont'a Hightower right at the goal line. Touchdown?! Silence falls as all eyes turn… not to the referees on the sidelines (there aren't any) but to giant LCD panels behind the end zones. The screens remain black for several long moments until "TOUCHDOWN" lights up.

Fake News, Cont'd: During a TV interview last night, Trump adviser Kellyanne Conway attempted to defend her boss's travel ban by pointing to "the Bowling Green Massacre"--which never took place. Conway tweeted that she "meant to say'Bowling Green terrorists,'" but her gaffe falls into a larger pattern of the Trump administration's "alternative facts." One true fact about the travel ban is that it revoked 60,000 visas--though a DOJ attorney erroneously said 100,000 earlier today. That error was poorly timed, since there's been a recent increase in fake news aimed at the biases of Trump's detractors as well as his supporters. We talked to Brooke Binkowski of the rumor-debunking site Snopes about the rise of fake news among progressives and what to do about it.

We extend chance-constrained path planning with direct method into continuous time. Chance-constrained path planning is a method to obtain the optimal path satisfying a specified risk (or probability of failure) value. Previous work expects trajectories' states as discrete information with respect to time. This discretized encoding makes the conversion from probabilistic path planning to deterministic path planning easy. However, risk guarantees are only produced for the discrete time model. The probability of constraints violation in continuous time could be larger than the discretized risk values. To address this problem, we modified the constraint encoding and risk assessment method. First, we introduce a computationally efficient mean path securing method, which uses fewer binary variables as compared with prior work. Second, we note that the deviation of the actual trajectory from the mean trajectory can be considered as a Brownian motion, for which the reflection principle holds in general. Therefore, we take advantage of the reflection principle to bound the probability of the constraint violation in continuous time. In numerical simulations, we confirmed faster solution generation, and the probability guarantees of the path in the continuous time model, with deterioration in the objective function.

We study the design of data analytic policies in a campus dormitory where smart meters are installed to gather usage data. Given the availability of such data, we consider policies to give feedback on comparative usage levels on a daily basis, and give price incentives accordingly. This requires us to divide users into groups according to their behaviors, and set prices that are reasonable. Instead of doing grouping and price setting based on intuition and guesses, which may be ineffective and unfair, we propose a data analytic approach. This requires us to start the design with a clear set of principles; based on these, and the collected data, the user grouping and corresponding pricing are automatically determined, satisfying the agreed-to principles. We show how this design approach works in a real setting, with real world usage data. We also discuss the difficulties in introducing such policies as they are more complicated and involve some uncertainties, and a possible solution by using opt-in (or opt-out) at the first introduction of such new policies. We expect the data analytic policy approach and our experience to be applicable and useful in general settings.

Online health resources aimed at older adults can have a significant impact on patient-physician relationships and on health outcomes. High quality online resources that are delivered in an ethical, emotionally aligned way can increase trust and reduce negative health outcomes such as anxiety. In contrast, low quality or misaligned resources can lead to harmful consequences such as inappropriate use of health care services and poor health decision-making. This paper investigates mechanisms for ensuring both quality and alignment of online health resources and interventions. First, the recently proposed QUEST evaluation instrument is examined. QUEST assesses the quality of online health information along six validated dimensions (authorship, attribution, conflict of interest, currency, complementarity, tone). A decision tree classifier is learned that is able to predict one criteria of the QUEST tool, complementarity, with an F1-score of 0.9 on a manually annotated dataset of 50 articles giving advice about Alzheimer disease. A social-psychological theory of affective (emotional) alignment is then presented, and demonstrated to gauge older adults emotional interpretations of eight examples of health recommendation systems related to Alzheimer disease (online memory tests). The paper concludes with a synthesizing view and a vision for the future of this important societal challenge.

Minesweeper is a famous single-player computer game, in which the grid of blocks contains some mines and the player is to uncover (probe) all blocks that do not contain any mines. Many heuristic strategies have been prompted to play the game, but the rate of success is not high. In this paper, we explore efficient strategies for the Minesweeper game. First, we show a counterintuitive result that probing the corner blocks could increase the rate of success. Then, we present a series of heuristic strategies, and the combination of them could lead to better results. We also transplant the optimal procedure on the basis of our proposed methods, and it achieves the highest rate of success. Through extensive simulations, a combination of heuristic strategies, "PSEQ", yields a success rate of 81.627(8)%, 78.122(8)%, and 39.616(5)% for beginner, intermediate, and expert levels respectively, outperforming the state-of-the-art strategies. Moreover, the developed quasi-optimal methods, combining the optimal procedure and our heuristic methods, raise the success rate to at least 81.79(2)%, 78.22(3)%, and 40.06(2)% respectively.

The quality of a good sleep is important for a healthy life. Recently, several sleep analysis products have emerged on the market; however, many of them require additional hardware or there is a lack of scientific evidence regarding their clinical efficacy. We proposed a novel method via clustering of sound events for discovering the sleep pattern. This method extended conventional self-organizing map algorithm by kernelized and sequence-based technologies, obtained a fine-grained map that depicts the distribution and changes of sleep-related events. We introduced widely applied features in sound processing and popular kernel functions to our method, evaluated their performance, and made a comparison. Our method requires few additional hardware, and by visualizing the transition of cluster dynamics, the correlation between sleep-related sound events and sleep stages was revealed.