The concept of beauty and cosmetics has advanced since the ancient Egyptian standards of smooth hair, clear skin, and beautiful eyes to include hair color and extensions, face contouring, and eyebrow enhancement. For each curve on our face, there now exists a product available to enhance and project it beautifully. The definition of beauty has changed over the years. Growing global economies, increasing disposable incomes, changes in lifestyle (indulgence in cosmetics for skin care, salon and spa treatments), and climate changes have resulted in increased skin care demands. The popularity of natural and organic beauty products, particularly in the United States and European countries, has also fostered the growth of the cosmetics market.

Amazon's Alexa voice assistant faces a massive challenge: Operating not only as a multi-lingual product, but also ensuring that all regional variants of languages it supports are well understood by Alexa, too. To help accomplish that, Alexa has been retrained entirely for every variant needed -- a time and resource-heavy activity. But a new machine learning-based method for training speech recognition created by Alexa's AI team could mean a lot less rework in building out models for new variants of existing languages. In a paper presented to the North American Chapter of the Association for Computational Linguistics, Amazon Alexa AI Senior Applied Science Manager Young-Bum Kim and his colleagues laid out a new system that was able to demonstrate improvements in accuracy of 18%, 43%, 115% and 57%, respectively, on four variants of English (from the U.S., the U.K., India and Canada) used in the trial. The team managed this by implementing a means through which it can tweak its learning algorithm to focus its attention more heavily on just a locale-specific model when it knows in advance that answers to requests from users made in that domain are highly region-specific (i.e. when asking to find a good nearby restaurant) versus when the results are going to be relatively similar regardless of where the request is being made. Alexa's team then combined their locale-specific models into one and also added their location-independent model for the language, and found the improvements measured above.

Self-driving vehicles, dating apps which give out relationship advice, humanoid robots that crack jokes and get upset... With a global market that is expected to reach US$35,870 million by 2025 from its direct revenue sources, artificial intelligence (AI) is no longer just the subject of science fiction books. According to a study carried out by IDC, in the ASEAN region, AI adoption rates are currently on the rise and growth has almost doubled in comparison to last year. When it comes to adopting this emerging technology, Indonesia is leading the way, with 24.6% of companies already embracing AI in some capacity. Thailand comes in second and the bronze medal goes to Singapore. This is somewhat surprising, considering the city state is normally something of a trailblazer in the region when it comes to embracing new technologies.

The UK, which spends more than £2bn on video surveillance each year, is to mark National Surveillance Camera Day on 20 June as part of the National Surveillance Camera Strategy. The aim of the national event is to raise awareness about surveillance cameras and to encourage debate about the use of surveillance cameras in modern society by highlighting how they are used in practice, why they are used and who is using them. The initiative by the Surveillance Camera Commissioner (SCC) and the Centre for Research into Information, Surveillance and Privacy (Crisp) is also aimed at starting a nationwide conversation about how camera technology is evolving, especially around automatic face recognition and artificial intelligence (AI). The organisers hope that the resultant public debate will help inform policy-makers and service providers regarding societally acceptable surveillance practices and legitimacy for surveillance camera systems that are delivered in line with society's needs. As part of the initiative, the SCC is encouraging surveillance camera control centres to throw their "doors open" so that the public can see how they operate.

The adoption of artificial intelligence (AI) is rapidly taking hold across global business, according to a new McKinsey Global Survey on the topic.1 1.The online survey was in the field from February 6 to February 16, 2018, and garnered responses from 2,135 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. To adjust for differences in response rates, the data are weighted by the contribution of each respondent's nation to global GDP. AI, typically defined as the ability of a machine to perform cognitive functions associated with human minds (such as perceiving, reasoning, learning, and problem solving), includes a range of capabilities that enable AI to solve business problems. The survey asked about nine in particular,2 2.The nine capabilities are natural-language text understanding, natural-language speech understanding, natural-language generation, virtual agents or conversational interfaces, computer vision, machine learning, physical robotics, autonomous vehicles, and robotic process automation (RPA). Some would argue that RPA should not be classified as AI in and of itself, but in our experience, RPA systems are increasingly incorporating AI capabilities.

ARTIFICIAL intelligence is being used in interesting ways across the Asia Pacific (APAC). Businesses in the region have been exploring how AI can help improve productivity, efficiency, and create new digital transformation and customer experience opportunities. Of course, the demand and adoption of AI applications in the APAC are driven by megatrends such as data availability, the furthering of the Industry 4.0 agenda, an population aging, and government support. According to a new Frost & Sullivan report, the efforts of leaders working on AI projects is paying off -- especially because of all the related technologies and concepts AI can bring to life. "With the convergence of Internet of Things (IoT) and communication technologies such as 5G, the future of AI application is all-pervasive," commented Frost & Sullivan Industry Analyst Cognitive Industry (AI and IoT), Information, and Communication Technologies Research and Practice Amy Lin.

Robots are getting closer to being able to see and feel the physical world. A team of researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) developed AI software that's capable of predicting what an object will look like or feel like by using'sight' and'touch.' The study could help humans and machines work together more seamlessly in the workplace, researchers say. Robots are getting closer to being more aware of their surroundings. MIT researchers developed AI that's capable of identifying an object by using'sight' and'touch' Their findings also bring robots closer to emulating a common function of the human brain: When humans look at an object, they can often anticipate what it will feel like, i.e. hard, soft, flexible, etc.

Dogs have evolved muscles around their eyes to look cute to humans, scientific research has shown for the first time. The muscles allow dogs to raise a quizzical eyebrow and to look sad - giving them facial expressions similar to our own. The authors say that the eyebrow raising movement triggers a nurturing response in humans. They makes the dogs' eyes appear larger and more child-like. The authors say that the eyebrow raising movement triggers a nurturing response in humans.

Domino's could be putting some of its delivery drivers out of a job this year by rolling out a new wave of robot delivery vehicles in Texas. The robot vehicles, made by the well-funded autonomous driving startup, Nuro, are entirely self-driving and can cart their cargo -- in this case Domino's pizza -- via in-unit storage. Once the robot arrives at its destination, customers must meet the vehicle and use a special pin provided to them upon ordering to unlock the hatch and collect their delivery. Domino's will take the next step in autonomous delivery by partnering with Nuro to deliver pizzas via robot cars. Silicon Valley-based startup, Nuro, will partner with Domino's Pizza to deliver in Houston, Texas.

At a time when facial manipulation tools, deepfakes and fake facial images are more advanced and common than ever before, Adobe, the multinational American computer software company, has trained AI to differentiate these fakes from original facial photos. A team of researchers from Adobe and UC Berkeley in California, U.S., have worked together to create this tool. The aim of their work is to restore faith in digital media, in a day and age when countless fakes and touch ups occur. The team studied Adobe's Photoshop feature called Face Away Liquify, which is meant to change people's faces, eyes and mouths. Later, they trained a convolutional neural network (CNN), used to analyze visual imagery, to pick up the changes made to the faces in the images.