Most consumers don't really know what artificial intelligence (AI) does, and the basic misunderstanding has some fearful of the technology. In a survey of 6,000 customers in six countries, the findings from Pegasystems study released this week found that consumers are hesitant to embrace AI devices and services. Some 36% are comfortable to engage with businesses using AI even if it results in a better customer experience. About 72% said they have some sort of fear about AI, with 24% worried about robots taking over the world. Only 34% of survey respondents thought they had directly experienced AI, but when asked about the technologies in their lives, the survey found that 84% use at least one AI-powered service or device such as virtual home assistants, intelligent chatbots, or predictive product suggestions.

Triplet networks are widely used models that are characterized by good performance in classification and retrieval tasks. In this work we propose to train a triplet network by putting it as the discriminator in Generative Adversarial Nets (GANs). We make use of the good capability of representation learning of the discriminator to increase the predictive quality of the model. We evaluated our approach on Cifar10 and MNIST datasets and observed significant improvement on the classification performance using the simple k-nn method.

If you're an accountant, lawyer or data analyst, a robot may soon take over your job. A new report from the International Bar Association suggests machines will most likely replace humans in high-routine occupations. The authors have suggested that governments introduce human quotas in some sectors in order to protect jobs. Gerlind Wisskirchen, a lawyer for labour and employment law, coordinated the study, which started one-and-a-half years ago. "We thought it'd just be an insight into the world of automation and blue collar sector," she said.

A soft-bodied robot that swims like a manta ray has been engineered to spy on underwater creatures without disturbing them. The mostly transparent robot has no motor or other rigid machinery and is much faster than other soft robotic fish. The goal is to use the robot to explore underwater areas, says Tiefeng Li at Zhejiang University in Hangzhou, China. It could be used to investigate a submerged ship or plane wreck, or survey coral reefs. "The soft body will make it easy for the robot to sneak through reefs without damaging them," he says.

Here's some good news for the day: life expectancy is continuing to increase, and shows no sign of slowing down. More people than ever before are reaching the milestone of 100 years of age. In fact if the Queen is still sending out telegrams to centenarians, she will soon need an industrial size mail house to keep up with demand! Sure, there are pockets around the world – called bluezones – where the prevailing lifestyles have seen concentrations of the world's oldest people. These zones include Sardinia in Italy and Okinawa in Japan, with research suggesting climate, diet and family structures have helped driven this phenomena.

Artificial intelligence is a hot topic in theoretical and applied research, as well as in general discussions about the profound impact it may have on individuals, industries and economies. The new Centre for Artificial Intelligence at UTS (UTS: CAI) will focus on the theoretical foundations and advanced technologies that will create intelligent machines with greater capacity for perception, learning and reasoning. "Establishing this centre gives us the opportunity to explore beyond core technology and into the impact of our discoveries. This includes the ethics of artificial intelligence, such as interrogating the way it will impact the future of work; and moral decisions we will need to explore around developments such as driverless vehicles," Deputy Vice-Chancellor Research Professor Glenn Wightwick told guests at the launch event. NSW Chief Scientist Professor Mary O'Kane pointed to Australia's well-established research into AI, which included her own experience gaining a PhD in the 1970s at the NSW Institute of Technology, now UTS.

Fast-learning bees die sooner than their slower working co-workers, research has found. These fast-learning bees collected fewer resources for the colony than their less intelligent counterparts overall. The researchers suggest that this may be because the energy that intelligence requires takes away from limited resources, leaving smart bees with less energy to look for food than their less-intelligent co-workers. Dr Nigel Raine, a co-author of the study and professor in the school of environmental sciences at the University of Guelph, Canada, said: 'Ultimately, the results revealed that fast-learning bumblebees collected fewer resources for the colony over their foraging career. 'These findings provide the first evidence of a learning-associated cost in the wild.' 'Our results are surprising because we typically associate enhanced learning performance and cognitive ability with improved fitness, because it is considered beneficial to the survival of an individual or group,' said co-author Dr. Lisa Evans, with Plant and Food Research in New Zealand.

There are around 55 million visually impaired people in India, up to 80% of whom could be helped by everyday procedures like Lasik. Medical and surgical resources, however, are limited. In April 2015, nonprofit L V Prasad Eye Institute, in Hyderabad, India, teamed up with Microsoft India to create Connected Eyes, a cloud-based machine-learning research project that uses data from tens of thousands of eye patients to identify the likelihood of success for new surgery, plus a probable regression rate, so that doctors can deploy those resources most effectively. Last December, Connected Eyes linked up with institutions in Brazil, Australia, and the United States to create the Microsoft Intelligent Network for Eyecare, which will build a universally available service that offers eye doctors immediate predictions for their patients. "This will be a global pool of knowledge that everyone can benefit from," says Anil Bhansali, managing director of Microsoft India R&D.

When restaurant reservation service OpenTable recruited him from dating app EHarmony, Joseph Essas received assurances that he could keep living in Los Angeles. Essas wasn't sure how, but OpenTable's then-Chief Executive Matt Roberts said, "Trust me, we're going to make this work." But after getting his bearings, he saw an easy way to persuade the company to cut his commute. Hiring software developers in San Francisco is cumbersome and expensive. In Los Angeles, it's easier -- and Essas could pull from his network of contacts developed in four prior executive roles in the region.

Databases are widespread, yet extracting relevant data can be difficult. Without substantial domain knowledge, multivariate search queries often return sparse or uninformative results. This paper introduces an approach for searching structured data based on probabilistic programming and nonparametric Bayes. Users specify queries in a probabilistic language that combines standard SQL database search operators with an information theoretic ranking function called predictive relevance. Predictive relevance can be calculated by a fast sparse matrix algorithm based on posterior samples from CrossCat, a nonparametric Bayesian model for high-dimensional, heterogeneously-typed data tables. The result is a flexible search technique that applies to a broad class of information retrieval problems, which we integrate into BayesDB, a probabilistic programming platform for probabilistic data analysis. This paper demonstrates applications to databases of US colleges, global macroeconomic indicators of public health, and classic cars. We found that human evaluators often prefer the results from probabilistic search to results from a standard baseline.