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  • How AI affect online grocery shopping experience

    How AI affect online grocery shopping experience

    AI will soon revolutionise the online grocery shopping experience, according to research released today ahead of next month’s Consumer Goods Forum Global Summit in Singapore.

    The research, compiled by IGD, is based on a survey of 223 senior industry members across 42 different markets and a series of in-depth interviews. It predicts digital transformation will reshape online food and grocery retailing. In China, already the world’s largest online shopping market, online grocery sales will grow by 286 per cent within four years and account for 11.1 per cent of the nation’s total grocery spending.

    The online store of the future will contain five key features:

    Personal micro stores

    “Personal micro stores” will offer individualised and online-exclusive products as well as personalised promotions, recommendations, advertising and loyalty schemes. More than two-thirds of respondents (69 per cent) believe some retailers will apply personalised pricing and promotions in future. An additional 77 per cent think almost all digital communication to consumers by retailers will be personal.

    “AI will help to unlock personalisation,” explains Simon Mayhew, online retail insight manager at IGD. “The store’s layout will be dynamic and able to predict the customer’s reason for shopping. So, if you need a meal for tonight, your homepage will display only the relevant solutions. When generally browsing, you will only see the products and pack sizes likely to meet your needs. Many products will only be buyable online where there is no constraint on shelf space, and in high-value categories, there will be customisable products, so you can create your own ideal shampoo or cereal.”

    Smart personal assistants

    Tomorrow’s online grocery stores will act as a smart personal assistant, connecting with various devices, preventing shoppers from running out of products and supporting their lifestyle goals. Nearly two thirds (60 per cent) of the experts surveyed predict that smart devices automatically re-ordering products will become a firmly established way of shopping for many people. The shopping experience will also be more inspirational, through personalised planners and sophisticated digital assistants like chatbots. Seventy-one per cent of respondents expect some retailers to provide a service to offer personalised dietary guidance.

    “Smarter devices will make shopping simpler and more inspiring,” says Mayhew. “The online store will help stop you running out of products. Shoppers will subscribe to have their favourite products delivered regularly and AI will predict when you may run out and make or suggest a reorder. Household devices, such as washing machines, will connect to your store and reorder when necessary. This will lock in customer loyalty.

    “The online store will offer more than just groceries, it will also help around the house. With populations urbanising and tending to live in smaller properties, businesses will offer services that prevent the need for space-hungry appliances, such as home cleaning and laundry.”

    Faster and more efficient

    Tomorrow’s online grocery store will be more efficient for shoppers, making it easier and quicker to order products. Login and payment will be available through facial, voice or touch recognition technology. Shoppers will incur less waste, with a greater choice of pack sizes and meal planners to help manage quantities and advise on using leftovers. A better fulfilment service will be on offer with more deliveries, on time and in full and products delivered at the right quality and freshness.

    “For retailers and manufacturers, the online store of the future provides both opportunities and challenges,” says Mayhew. “Data from the online store will guide product development. Retailers will see gaps in their ranges through unfulfilled search requests and have a better understanding of product quality through ratings, reviews and feedback to chatbots.

    “Fulfilment will benefit from robotics and supply chain forecasting will be more accurate. This will mean online pickers have fresher products to select, helping overcome one of the biggest barriers to shopping online. Unattended deliveries to homes, cars, and even ‘straight to the fridge’, will grow in popularity.

    “Improvements in service will reduce the number of returns and make deliveries quicker. We will see greater collaboration in the supply chain, including manufacturers pooling resources to sell directly to consumers. However, there will also be new challenges and potential inefficiencies. Shoppers will expect faster deliveries, and this means smaller, more frequent orders.”

    Frictionless experience

    Tomorrow’s online grocery store will deliver a frictionless combined offline and online shopping experience for consumers. People will switch seamlessly from shopping online and instore with data cross-referenced between the two. This will help bring more personalisation to the physical store and help shoppers find their favourite products quickly and discover new ones. This is an opportunity that many companies need to work on with over half (53 per cent) of survey respondents saying they haven’t or have only just started to integrate their online and offline teams.

    “Before visiting a physical store, you will be able to look online to check in-store, real-time availability, access product information, get product usage ideas and read reviews”, says Mayhew. “When you arrive at the physical store you will then benefit from personalised offers and recommendations. An online app will help you find products and pay for your shopping without cash.”

    Invisible stores

    Tomorrow’s stores will – at times – be invisible, with shoppers buying products from shoppable digital content such as videos, photos and social media. In the future, people can be shopping at any time. There will be no limits to when you can be shopping. China has been leading the merging of media, entertainment and shopping, and Europe and North America will follow.

    “You won’t even need to visit your online store to buy products,” says Mayhew. “Alongside voice ordering, the majority of digital content you see will be shoppable. You could be watching a video or see a still image and just click on it to buy the product.”

    Danger in downplaying

    IGD’s team says there are three primary reasons why no grocery retailer or supplier can afford to downplay online retail:

    • Across most of the world, online is already a fast-growing channel.
    • Online and offline are merging, with an online store vital to complement physical stores.
    • The digital world evolves faster than the physical one and online stores will become increasingly compelling.

    The research house says tomorrow’s shoppers will expect more choice, convenience, inspiration, personalisation and transparency and online stores will play an increasing part in meeting these needs.

    “Grocery retail is seeing an unprecedented amount of change, driven by changing shopper expectations and the ability to meet these using transformative technologies,” says Joanne Denney-Finch, IGD’s CEO. “This offers great opportunities for companies of all sizes. The winners will put the needs of their shoppers first, be prepared to act decisively, maintain the highest everyday standards and exhibit tremendous agility.”

    The report, free to download from IGD, will be presented in detail at the Consumer Goods Forum Global Summit from June 12-15.

    Peter Freedman, the forum’s MD, says the IGD research report sets out a clear, consumer-centric vision of tomorrow’s online shopping experience.

    “It gives us all something to aim towards and it ties nicely to the theme of this year’s Global Summit – Consumer Centricity in a Data-Driven World.

    “And it highlights the importance of the CGF’s positive change agenda – such as using new technologies to deliver accurate product information on the digital shelf, designing out product and packaging waste, and retailer-manufacturer collaboration for growth.”

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  • Alibaba demonstrates smart ordering in cafe and restaurants using voice AI

    Alibaba demonstrates smart ordering in cafe and restaurants using voice AI

    Alibaba Machine Intelligence Technologies has unveiled an intelligent speech interaction technology aimed at “smart ordering” in cafes and restaurants. The new technology lets buyers order their food item or coffee by speaking to a smart ordering machine.

    The Alibaba DAMO Academy unit, which focuses on fundamental AI research, said the machine will understand the customer order requests and display the order onscreen in a split second.

    Buyers can modify their orders as many times as they want, and the machine is expected to catch all the changes and update immediately. For example, a customer might say: “I want to order two large cups of cappuccino. Oh, please make them with less sugar and decaf. To go. And sorry. That should be three cups of cappuccino, two large and one small.” The smart ordering machine will then display the full order as two large cups and one small cup of decaf cappuccino, all with less sugar than usual and note that it’s for takeout.

     

    Smart ordering is possible through the team’s latest research in spoken language understanding (SLU), a field that involves both speech processing and natural language processing. First, the team develops a multi-modal speech interaction solution that can capture both voice and visual features, taking into account such things as the speaker’s pace, pauses between words, pronunciation, breaths and facial expression. Next, the team builds a reinforcement-learning model that allows for revisions and intent detection. All are important in the SLU field, making it possible to apply the latest SLU technology into commercial use.

    The solution is currently only for Chinese-speaking customers. The smart ordering machine is expected to roll out to the market in the next few months, and the technology solution will be available on Alibaba Cloud to benefit small and medium-size enterprises.

    Zhijie Yan, Head of Intelligent Speech Interaction at Alibaba Machine Intelligence Technologies said, “Our multi-modal speech interaction solution, underpinned by our insights in spoken language understanding, can be used in different scenarios including food and beverage ordering, customer service, voice commands for home appliances and in smart cars, and voice response to inquiries in shopping malls or airports.” “With the smart ordering machine as a perfect example, we believe the solution would greatly enhance the customer experience and make running a business more efficient,” added Yan.

    In December last year, Alibaba introduced far-field voice-recognition technology to ticketing kiosks in Shanghai metro stations, allowing passengers to use their voices to tell the kiosks their destination, and the machines will recommend the best route.

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  • Alibaba backs virtual showroom startup Ordre

    Alibaba backs virtual showroom startup Ordre

    Alibaba Group has bought a minority stake in Ordre, a European online luxury wholesale platform.

    Ordre, launched in 2015, allows fashion designers to show off their collections via 360-degree photography and virtual reality to interested wholesale buyers. The technologies make it more convenient for buyers, who aren’t always able to travel due to time and distance constraints, to build inventory each season. The reduced travel translates into lower carbon emissions at a time when sustainability is increasingly important to the industry, said Ordre.

    Dianne Von Furstenberg, Vivienne Westwood and Jason Wu are among the world’s leading designers who have established digital showrooms on Ordre. They also work with fashion brands such as Joseph.

    For Alibaba, the investment is a further push into the luxury sector, which is among its top strategic priorities, given the rising spending power and increasingly sophisticated tastes of Chinese consumers. The Hangzhou, China-based company plans to leverage Ordre’s technologies for consumers, however, delivering a more-enhanced shopping experience on platforms such as B2C marketplace Tmall.

    “Matching Ordre’s technology with Alibaba’s unique data insights and capabilities – of which our recently launched Luxury Pavillion is a great illustration—we can provide our consumers with a personalised and differentiated experience, helping brands develop a deeper engagement with them,” said Jessica Liu, president of Tmall Fashion and Luxury.

    The Luxury Pavillion, which lives within Tmall, was launched last August to deliver to China’s high-end consumers the same kind of brand exclusivity and tailored shopping experience online that they would expect at a brick-and-mortar store. About 50 brands, including l, offer products ranging from apparel and cosmetics to watches and luxury cars.

    The pavillion is driven by Alibaba’s New Retail technologies, which blend online and offline commerce to deliver a better buying experience for consumers. Simon Lock, founder and CEO of Ordre, said the company’s digital assets, including 360-degree images, 360 video and VR fashion shows and designer interviews, are in line with this strategy and could serve Tmall shoppers and brands.

    “Our 360-view allows consumers to understand every aspect and every view of a garment,” he said. “When you’re purchasing online, as much detail as can be provided is going to make your purchasing decision much more confident,” which can help drive down the product return rates.

    The companies are currently discussing a number of potential initiatives that would expand on these technologies. One of which would create new direct-to-consumer channels for Ordre’s partner brands by leveraging content to communicate their brand story and provide more information about products. For example, Ordre’s VR technology was able to recreate Stella McCartney’s Coachella-inspired 2018 fall show and the theatrical experience of Thom Browne’s latest showcase in Paris, so that buyers could watch fashion shows from the front row.

    Other potential collaborations include “fit avatars,” which allow buyers to see collections on models in 360-view and technology that allows buyers to remotely feel fabrics on a touch pad.

    Lock said he was also interested in Alibaba’s “See Now, Buy Now” technology, as well as the company’s artificial intelligence and cloud-computing capabilities.

    “We can work together to create the ultimate global fashion cloud,” he said.

  • Samsung to open AI centers in three countries

    Samsung to open AI centers in three countries

    Samsung Electronics is opening research centers dedicated to artificial intelligence technology in the United Kingdom, Canada and Russia.

    That will bring the number of Samsung’s AI research centers to five, adding to existing ones in Korea and California.

    The Cambridge center in the U.K. opened yesterday, the Toronto center in Canada opens on Thursday and the Moscow center in Russia opens next Tuesday.

    In November, the electronics giant established an AI center under Samsung Research, a unit that heads development of future technology for the company. Two months later, a Samsung AI center was opened in Silicon Valley in the United States.

    The Korean center will function as headquarters for all five AI research centers, making it a global hub for AI research. Samsung has grand plans to expand the number of specialized researchers in the AI field to more than 1,000 by 2020, and some 40 percent will be foreigners.

    “[The AI center] will be a game-changer for Samsung to make a new world for the era of artificial intelligence,” said Kim Hyun-suk, president of Samsung’s consumer electronics unit at Tuesday’s inauguration ceremony of the AI center in Cambridge. Kim also heads Samsung Research.

    The Cambridge center will be led by Andrew Blake, who was director of the Microsoft Research Lab in Cambridge. Professor Maja Pantic of Imperial College London will also lead AI research as part of the unit. Her area of expertise is machine analysis of human emotions, for which she was chosen by the science journal Nature to speak at the 2016 World Economic Forum in Davos.

    Larry Heck was appointed to head the Toronto center. He is an expert in voice recognition and was a former leader of Samsung’s Silicon Valley center. The Moscow center will be led by Higher School of Economics Prof. Dmitry Vetrov and Skoltech Prof. Victor Lempitsky.

    Samsung Electronics has been active in artificial intelligence technology this year. It introduced its AI assistant Bixby in April 2017.

    At the Consumer Electronics Show in January, President Kim vowed to use the virtual assistant in all of its products, including home electronics, by 2020.

    Samsung Vice Chairman Lee Jae-yong reportedly intends to invest in future growth areas such as AI following his return to management this year after months in jail.

    With Lee back at the helm, there is anticipation that Samsung may be more aggressive about acquiring companies with promising research.

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  • The AI moment: preparing for the revolution

    The AI moment: preparing for the revolution

    Artificial intelligence, AI, is the next big technology to have entered mainstream consciousness. From eerie androids such as Sophia to the silent efficiency of automated delivery systems in modern Amazon warehouses, the growth of autonomous driving and the popularity of smart speaker systems such as Alexa or Google Home – AI is everywhere. And it’s coming for our jobs, white collar and blue, threatening massive social and economic upheaval.

    But what is AI really? Why has it suddenly become so popular? Why is everyone so excited about its tremendous potential? Will it really replace humans – and should we welcome it with open arms, or fear for its impact?

    Far from being an omnipotent, autonomous robot, AI is at heart simply a machine programmed to make sense of data on a scale humans can’t deal with. It is the king of the algorithm, a machine learning from its own experiences, objective-oriented and highly intelligent, producing logical conclusions based on input. As part of the digital technology connecting people, things and machines on a big data platform, it has the potential to enable solutions saving time, energy and lives, opening up opportunities as yet undreamt of. And it is still in its infancy in its real world deployment.

    The use of AI is growing dramatically right now in response to extraordinary increases in the amount of data produced daily, as powerful computing has become available at lower costs. Humans alone simply cannot process the complexity and ongoing volume of data from people, devices, sensors and machines.  In parallel, there is a growing awareness of the tremendous potential of AI technologies to solve problems across all industry sectors and the entire spectrum of human life.

    AI can unlock scale and opportunity to deal with the grand challenges facing the world today, from ageing populations to sustainable urban living, access to food, healthcare, water and education, reducing poverty and increasing gender equality. Physical AI will be able to free humans from mundane, routine tasks, allowing them to concentrate on more important, higher-end work, releasing creative potential.

    In emerging markets and smart cities alike, AI can help overcome natural limitations to growth such as geographic size or lack of natural resources, creating new markets and new value, rather than merely improving on existing models.

    Improvements on current models will, however, be where the power of AI is first felt, in its promise of enormous cost savings, increased productivity, lower production cycles and improved back end or internal processes. Within the telco industry itself, AI will accelerate the evolution of network operator infrastructure into intelligent networks able to offer smarter, faster and more scalable services. Using the engine of big data, AI will enable multiple, diverse and often sector-specific demands to be met through highly-tailored network slices managed in real time.

    In the financial services sector, for example, AI can reduce the hundreds of thousands of hours needed to carry out regulatory compliance to a matter of seconds; or the time, effort and investment necessary for a mortgage to a few minutes. New financial services may include mass market personalised services, opening an enormous market of lower earners, or microfinancing for the unbanked. In call centres across a range of industries, AI can work either alongside humans analysing complex data sets in parallel to the human customer-facing contact, or take calls as a co-worker as far as possible before passing on to human expertise.

    In all cases, AI is a tool to augment human abilities rather than replace them. And it is only as good as the person inputting information and parameters into its system.

    This is one of the principal challenges: ensuring that AI is provided with initial information in a way that does not reflect and perpetuate inherent bias, unconscious or not. It is critical to be aware of, and work to avoid, replication of existing divides and inequalities: on gender, race, geography, the urban/rural split, access to education, investment in infrastructure, the availability of talent, the provision of adequate cyber security. Without action, AI will prolong or deepen these divides. There is a very real danger that the powerful impact of algorithms actuated by AI will remain limited to the developed world due to a lack of infrastructure, advanced networks, open data or data scientists.

    Providing open public data and open APIs to allow private companies and individual developers to create solutions for public and commercial services is key to democratising AI – and fast-tracking its deployment. Accessing large data sets in the ecosystem to improve quality of life must be balanced against data protection, privacy and security issues.

    Preparation in general – and education – is critical. The international community, government, businesses and individuals should be as ready as possible for the seismic changes that the widespread adoption and deployment of AI will bring with it.

    The big one, of course, is the transformation of the existing labour market. It is estimated that up to 75% of all jobs will be impacted by AI over the next ten years – and these will not just be routine, low-skilled jobs, but also traditional blue collar sectors such as journalism, law or financial services. Productivity and revenue should rise as costs are cut, but the societal disruption will be enormous.

    AI is often invisible, raising issues of transparency and accountability. It is itself a neutral tool, without morality, but the ethics of its use are complex. Establishing codes of conduct and social norms as the first step to any regulation is urgently necessary at intergovernmental, international level. Regulation – as well as the standardisation necessary for it to function in a multi-vendor ecosystem environment – is further complicated by AI’s inherent structure as an active machine, learning in real time with real data.

    AI is here – and growing fast. There is an increasingly urgent need to bring together key stakeholders from government, industry and academia to debate its impact on a neutral platform such as ITU Telecom World 2018, the leading tech event organised by ITU, the UN lead agency for ICTs. Making AI democratic, fair and equitable is a challenge that cannot be met by any one single stakeholder.

    Experts at ITU Telecom World 2017 last year felt that its first use cases and greatest impact would be economic rather than social: AI will go where the money is, or can be made.  In some sectors, if you are not yet using AI, you are two years behind the curve. But the size of the opportunity is so great, the potential so huge, that it is far from too late.

    The potential negative effects of AI include social and economic disruption, in particular in the job market; the deepening of inequality; the danger of inherent bias; major issues of transparency, security and accountability; the lack of an internationally-agreed ethical code. Now is the time for contingency plans, for preparation and education throughout governments, industries and societies.

    There is downside, after all, to both deploying AI and not deploying it.

    AI will be a key component of discussions at ITU Telecom World 2018 in Durban, South Africa, 10 -13 September, providing the diverse perspectives of international experts from government, industry, SMEs and academia. Find out more at https://telecomworld.itu.int/

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  • How DHL Aims to Remake Logistics with AI

    How DHL Aims to Remake Logistics with AI

    What do semi-autonomous truck platoons, chat-bots, and fraud detection cameras have in common? They’re all part of a big plan that DHL unveiled yesterday to remake itself with artificial intelligence.

    DHL is investing millions to take advantage of recent advances in machine learning that could help it optimize its sprawling $60-billion delivery service, which touches nearly every country in the world and involves 500,000 workers.

    According to Ben Gesing, a project manager in DHL’s Innovation and Trend Research division, the Germany company is pursuing a multi-pronged strategy to utilize a variety of emergent AI technologies and techniques to help it cut costs, increase efficiency, and improve service levels across the company.

    “In terms of data creation, processing storage and accessibility, the technology conditions for AI are very favorable,” Gesing tells Datanami. “Broadly speaking we think the future of AI and logistics is filled with potential.”

    Here are some of the AI projects that DHL is currently working on:

    Autonomous Vehicles – DHL is working on autonomous vehicles on three fronts, including the development of intelligent robotic workers in its own warehouses and air freight centers; the use of semi-autonomous trucks in the line-haul business; and “follow-me” robots used for last-mile route delivery in urban settings.

    One of the more interesting uses of AI is the development of truck platoons in Europe, where anywhere from one to four autonomous semi-trucks follow a lead truck with a human driver down the road. By synchronizing acceleration, braking, and steering among the trucks, the platoon can boost freight capacity while minimizing costs, all without handing total control over to the AI program. DHL will be involved with testing a truck platooning in the UK next year with the British Transportation Research Laboratory and truck manufacturer DAF Trucks.

    Chat Bots – DHL is looking into using autonomous customer service representatives by using deep learning-based natural language processing (NLP) technology, such as Amazon‘s Alexa, to automate some of the easier interactions between customers and DHL’s customer service representatives.

    “Automating some of the low-level queries with chat bots can really increase the value of each interaction between customer and [human] agents by letting them focus on more high-level queries,” Gesing says. “That basically increases our throughput by a multiplier, not just a marginal increase.”

    Computer Vision – DHL is exploring the use of deep learning-based computer vision algorithms for at least two use cases, including fraud detection and optimizing the loading of planes and trucks.

    Some people try to defraud DHL by re-using shipping labels, which Gesing says could be automatically detected using cameras hooked up to fraud-detection algorithms. Similarly, computer vision could boost DHL’s capability to detect the size of packages so they can be stacked better.

    “It doesn’t seem that interesting if you’re not in the logistics industry, but understanding how to best use your space and really optimizing the volume and capacity inside an aircraft or a truck” is important, Gesing says. “We’re getting better and better tools and technology to do that using AI-based vision technology.”

    Resilience 360 – DHL plans to infuse this cloud-based risk management tool with AI capabilities that will give its customers an early warning that something is amiss in their supply chains. This product uses sentiment analysis to monitor 8 million sources of data on the Internet, including social media, for anything that could signal a disruption, including unhappy customers and even labor unrest.

    “For a lot of our B2B or automotive or manufacturing customers, they have very vast supplier networks,” Gesing says. “We proactive identify risky parts of the supply chain so our customers can plan downstream more effectively.”

    DHL Global Trade Barometer –DHL feeds this this recently introduced tool with import/export data and data about containerized air and ocean freight, giving it a view into 75 percent of the world’s daily trade. It uses AI techniques to provide a three-month forecast on the direction of global trade.

    “We have data scientists all over the world, internally and partners with external companies, to do different kinds of optimization of our network, things like predicting demand and capacity needed, or predicting delays in airfreight either by trade lane, by airline carrier, or by day of the week or day of the month,” Gesign says. “It gives us a directional assessment of where global trade is headed…to really get out ahead of our current daily operations to plan more effectively.”

    Big Data to AI

    Over the past several years, DHL has invested in exploiting recent innovations in areas like big data, augmented reality, and Internet of Things. In 2013, DHL published a Trend Radar report on big data, and yesterday it published another report called Artificial Intelligence in Logistics with support from its partner IBM, which you can download here.

    AI is viewed as a big component of DHL’s digital transformation strategy, says Gesing, who works in DHL’s corporate innovation lab in Troisdorf, Germany, one of three innovation labs the company runs (the other is in Singapore, while the one in the United States is currently under development). “AI and machine learning are the extension of big data analytics,” Gesing says.

    DHL’s board views AI strategically, but the innovation centers aren’t the only places where work on AI is being done. “We have a very broad digitalization strategy that comes from our corporate board,” Gesing says. “AI is inherently part of that. But really the best teams are the ones making productive use of this are really empowered to go learn and test and use this stuff.”

    DHL isn’t doing a lot of core research into AI, because much of that work has already been done. Instead, it’s utilizing technology that has already been placed into the public domain by companies like Google, Amazon, Microsoft, IBM, and Facebook.

    “Pretty much anyone who’s doing AI is benefiting from all these great open source tools and platform from all the tech giants,” Gesing says.

  • NBTC backs down on financial relief for AIS, True

    NBTC backs down on financial relief for AIS, True

    Thai telecoms regulator NBTC has backed down on its recommendation of providing financial relief for mobile operators AIS and TrueMove in the face of criticism from academia and the public sector.

    The regulator will no longer support a plan to provide relief from the operators’ 900-MHz license payment obligations.

    The ultimate decision will be down to the National Council for Peace and Order (NCPO) and the government, but the NBTC will not oppose a plan that would ease the financial burden of digital TV operators but leave 900-MHz license winners out.

    AIS and TrueMove both petitioned the NCPO in September requesting assistance in easing their license payment terms. The NBTC had drawn up a proposal to grant five year extensions for the payments of the final 900-MHz license payments, but the proposal was controversial.

    TrueMove noted that the winning prices of the 2015 900-MHz spectrum auction were six times higher than the reserve price and the highest in APAC, and has warned that without financial relief the company will have limited capital for investment in services including 5G and the IoT. The company could also be hampered in its participation in the upcoming 1800-MHz auction.

    AIS has likewise argued that relaxing the 900-MHz payment scheme would allow the company to invest in expanding and upgrading its mobile network, benefiting consumers.

  • Automated stores with no human cashiers on the rise

    Automated stores with no human cashiers on the rise

    Unmanned Stores without cashiers are on the rise, industry sources said, amid local retailers‘ efforts to find a breakthrough in the saturated market.

    Local software firm Danal Co., which operates coffee franchise dal.komm coffee, said it recently opened the country’s first cashier-less coffee shop at the country‘s main gateway, Incheon International Airport.

    The coffee shop, named Beat, is located at the newly opened second terminal and is activated by robots, the company said.

    The store is operated by smart robots that can take orders, make coffee and move cups to a pick-up location where customers can drink.

    “The company aims to add up to 100 stores by the end of this year at various locations, including banks, shopping malls, and universities,” said a company official who asked not to named.

    Unmanned convenience stores are also on the rise, since the country’s first cashier-less convenience store broke onto the retail scene in May. The local operator of 7-Eleven unveiled a shop that utilizes vein recognition technology at South Korean retail giant Lotte‘s 123-story skyscraper.

    Unlike other 24-hour shops, automated convenience stores feature self-service kiosks, where guests scan the bar codes of their items and pay.

    Emart24, an affiliate of leading discount store chain operator Shinsegae, currently operates six cashierless stores, having opened the first one last June.

    BGF Retail Co., the operator of CU, South Korea’s largest convenience store chain, said it is preparing to open an unmanned shop.

    The company currently provides mobile application called “Buy-Self,” which allows customers to search for an item, and provides a payment tool.

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  • 7-Eleven brings facial-recognition technology to stores in Thailand

    7-Eleven brings facial-recognition technology to stores in Thailand

    7-Eleven Thailand is to roll out advanced AI technology, including facial recognition of employees and customers, across all 11,000 stores in the kingdom.

    The convenience store chain’s parent, CP All, has signed a contract with US-Chinese technology company Remark to use its KanKan data intelligence and AI-based facial recognition and behavior-analysis technologies which it says will provide enhanced customer support, business analysis, employee management and security.

    An estimated 10 million people walk into 7-Eleven Thailand stores each day and the KanKan technology can monitor such things as how long a customer lingers in specific places in-store, and even record their emotions. It can identify members of 7-Eleven’s loyalty program allowing management to offer them tailored promotions.

    From a store-management perspective, the technology can monitor stock levels on shelves and provide real-time operations performance and competitor analysis, check employees on and off shift and identify unauthorised personnel on site.

    “The KanKan implementation at 7-Eleven marks our first major collaboration with Remark,” said CP Group chairman Soopakij Chearavanont.

    “The 7-Eleven team evaluated many AI technologies and selected KanKan because it has the most robust platform for meeting business objectives, namely, driving revenues, reducing costs and rapidly improving profit margins.”

    Remark Holdings’ CEO and chairman, Kai-Shing Tao said the 7-Eleven partnership represents “an incredible opportunity to implement our KanKan technologies on a massive scale”.

    Chearavanont told a media briefing that the technology would help the chain cut costs, improve revenues and increase margins.

    Remark has promised that no images of human faces will be stored on servers by 7-Eleven, apparently addressing privacy concerns relating to what happens to recordings, something being raised by lobby groups around the world.

    The companies say only facial features – not whole faces – are used to generate data which is encrypted.

    “No human faces or images ever leaves the KanKan system or goes on the public network,” the company said.

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  • PolyU partners with Alibaba to create AI for fashion retailers

    PolyU partners with Alibaba to create AI for fashion retailers

    Students from Hong Kong’s PolyU have partnered with Alibaba Group’s Vision and Beauty Team to develop AI technology for fashion retailers.

    The students, from the Institute of Textiles and Clothing (ITC) of The Hong Kong Polytechnic University, have created the first-of-its-kind “FashionAI Dataset” for systematic analysis and labelling of fashion images based on “fashion attributes” (fashion characteristics) and “key points” of an apparel.

    PolyU explains that by integrating fashion knowledge and machine learning formulation, the establishment of the dataset will enable machines to better understand fashion, “bringing a new horizon to the fashion retail industry through the application of AI”.

    “Transforming fashion knowledge into determination of fashion related attributes and fashion item categorisation of the fashion image database is a very complicated and challenging task, while it is the most fundamental task in deep learning applications,” explains Calvin Wong, Cheng Yik Hung professor in fashion and associate Head of ITC.

    “ITC is pleased to collaborate with Alibaba to address the needs of fashion retailers and consumers.”

    Menglei Jia, senior staff engineer with Alibaba’s Vision and Beauty team, believes there is huge potential for AI applications in the fashion industry.

    “In order for AI to understand fashion, which could be very subjective, we need to turn fashion knowledge and experience into language that machine can understand. We hope to work with academics and the industry alike to explore the wider applications of AI in scenarios including fashion mix-and-match, assisting design and shopping guide, with the aim to bring new values to the fashion industry.

    “The traditional fashion sector should embrace the new retail practice, and we hope FashionAI can be a bridge that connects AI with fashion.”

    Challenges presented by data on fashion image

    Current fashion image searching technology used on online platforms is based on the whole fashion image to search the exact or other similar images.  However if a customer is interested in some particular fashion attributes of a fashion image and wants to search other fashion items with these attributes, the current searching technology cannot meet the needs of the customer. This greatly limits the potential development and applications for offering more customised shopping experience, PolyU explains.

    From an AI research perspective, this limitation of the current image searching technology is caused by the absence of available fashion image dataset constructed with both fashion professional knowledge and fulfils the requirement of deep learning, ie: the current technology is unable to train a machine to accurately understand and recognise the fashion attributes of each fashion image.

    Addressing the needs of fashion retailers

    Fostering the application of AI in the fashion industry, a PolyU research team led by Professor Wong, worked closely with Alibaba to develop “FashionAI Dataset” to solve two fundamental problems of the deep learning algorithm: “apparel key points detection” and “attribute recognition”.

    Key points (e.g. neckline, cuff, waistline) and fashion attributes (e.g. sleeve length, collar type, skirt style) build the foundation for machine learning in understanding fashion images. The establishment of key points and fashion attribute database enables the computer to effectively and efficiently understand the fashion image which is fundamental for deep learning and recognition algorithms.

    The accuracy of key points detection is determined by several factors such as the dimension and shape of the apparel, distance and angle of shooting, or even how the apparel is displayed or the model is posing in a photo. These factors can lead to poor key points detection and result in an inaccurate analysis of fashion images by the computer. Accurate key points detection can therefore improve the performance of deep learning algorithms.

    Fashion attributes are the basic design elements of an apparel, and their combination determines the product category and styles of a fashion item. With the wide variety of fashion attributes, attribute recognition is a complicated process. A systemic classification of fashion attributes is essential to accurately label fashion attributes, facilitating research on deep learning and algorithm design for fashion image searching, navigating tagging and mix-and-match ideas, etc.

    The Dataset can greatly facilitate understanding fashion images and related algorithm design, and developing machine learning. It would help improve the accuracy of online fashion image searching, enhance effectiveness of cross-selling and up-selling, create innovative buying experience and facilitate customisation of online shopping platforms.

    Global challenge

    PolyU and Alibaba will host two world-first events – the AIFT Conference and FashionAI Global Challenge – with the aim of bringing a new horizon to the fashion retail industry through the application of AI and encouraging knowledge exchange among practitioners.

    The AIFT Conference, to be held from July 3-6 at PolyU, is a first-of-its-kind academic conference to bring together researchers, engineers and practitioners to share their insights on the most updated development and applications of AI and fashion.

    This event will become an annual activity for academic exchange and networking with like-minded individuals who are redefining the world of AI and fashion, and advancing AI research in fashion and textile.

    The FashionAI Challenge invites worldwide AI researchers and developers to solve two imminent issues on the application of AI in fashion with over 400,000 images with high-quality annotations from Alibaba ecommerce platforms. The competition offers a prize pool of RMB 1.34 million. The FashionAI Global Challenge 2018 runs from now until April and is open to the public.

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  • Retail News Asia Honoured with the “Best Global Retail News Platform 2018” Award

    Retail News Asia Honoured with the “Best Global Retail News Platform 2018” Award

    Retail News announced today that it has been named the Best Global Retail News Platform 2018 in the AI Business Excellence Awards. Hailed as the “Internet’s highest honor” by KPMG, EY, PwC and Deloitte, The Business Excellence Awards, is the leading international awards organization honoring excellence on the Internet. The judging panel is compromised of the three directors here at AI Global, they have a combined total of 40 years of work within this industry and know it very well.

    The reason why AI uses an in-house judging panel is because they fully understand the process and also know what our standards are in terms of award winners.  They have been judging the award programs for the past 8 years. AI’s judging panel works very closely with a research team which is comprised of 4 researchers who are in charge of gathering information for each case study and presenting each case file to the judges. This is the 6th year of the Business Excellence Awards, hosted by Acquisition International, and you can view all the details of last year’s awards on their homepage.

    Launched over 8 years ago, AI has rapidly risen to and now has a circulation of 108,000 people in over 170 countries and regularly attracts editorial submissions from some of the biggest players on the global corporate landscape.

    AI is a monthly magazine that seeks to inform, entertain, influence, and shape the global corporate conversation through a combination of high quality editorial, rigorous research and an experienced and dedicated worldwide network of advisors, experts and contributors.

    Alongside the monthly issue AI hosts annual award programs which aim to highlight and provide recognition to the companies and individuals who have worked hard to get where they are today. The AI awards are only given 100% based on merit and not based on the judgment of a number of votes received.

    RetailNews is committed to providing both local and global retailers with the latest breaking retail news throughout the Asian market. This on a daily base. We have resources for everyone from the independently owned business owners, online-only retailers, and major chains expanding their reach throughout the Asian market, says Sven – founder of Retail News.

    We Are Stronger Together

    You can quickly and easily search for the latest breaking retail news by country, or come here to keep an eye on the latest local, global and seasonal trends.

    On Retail News you can network, engage, and share invaluable information with other retailers. Our retailers come from a wide range of industries and expertise, meaning that whatever the question may be—we have you covered!

    We are extremely honored with this recognition and my team has been working extremely hard the last 3 years to bring us to a level where we are operating now, Sven added. With nearly 8 million visitors a month, 23 daily retail updates, Retail News is believed to be the Retail industry leader.

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  • Alibaba teams up with Singapore university on AI

    Alibaba teams up with Singapore university on AI

    Chinese tech giant has set up a joint research facility at Singapore’s Nanyang Technological University to develop artificial intelligence-based technologies in retail, transportation and healthcare

    Chinese e-commerce and technology giant Alibaba has partnered Singapore’s Nanyang Technological University (NTU) in a joint research facility aimed at harnessing artificial intelligence (AI) to solve societal issues such as Singapore’s ageing population.

    The first of its kind outside China, the Alibaba-NTU Singapore Joint Research Institute will bring together NTU’s AI capabilities, including efforts to develop an artificial companion for the elderly, and Alibaba’s expertise in natural language processing, machine learning and cloud computing.

    The multimillion-dollar partnership between Alibaba and NTU is expected to involve 50 scientists and engineers from both parties over five years. Besides addressing the needs of ageing societies, they will also develop AI technologies in areas such as retail, urban transport and healthcare.

    For example, NTU’s expertise in healthcare research and Alibaba’s knowhow in AI to diagnose and prevent diseases will be pooled to achieve breakthroughs in health-related AI. Both parties will also conduct research to improve urban mobility and reduce Singapore’s carbon footprint.

    Alibaba said its contribution to the research facility will come from a $15bn fund earmarked for its Damo research and development (R&D) programme, which includes establishing research labs across the globe, including one in Singapore.

    The joint research institute is located on the NTU campus, but it is open to researchers and academics worldwide. Alibaba will also build a crowdsourcing platform to connect researchers and industry practitioners in an AI-focused R&D community.

    Jeff Zhang, Alibaba’s chief technology officer, said the AI technology developed by the institute will first be rolled out in NTU, followed by other parts of Singapore and Southeast Asia at a later date.

    “By launching our first joint research institute in Singapore, we hope to work with talent in Singapore and researchers worldwide to explore technology innovation that can address common issues faced by the society at large,” said Zhang.Alibaba’s efforts to develop AI capabilities in Singapore follows the recent launch of Chinese facial recognition specialist Yitu’s regional headquarters in Singapore that will mainly serve as a sales, marketing and operations outfit for now.

    Yitu said plans are also in the pipeline to establish R&D capabilities in the city-state by the end of 2018.

    In May 2017, Singapore’s National Research Foundation said it would invest up to S$150m (US$107m) over five years in a programme called AI.SG to drive adoption of AI to solve business problems.

    To nurture a local AI community, AI.SG will also work with startups and corporate laboratories through new facilities that will provide software tools, anonymised datasets and high-performance computing resources.

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  • Retailer spending on AI to rise, says Juniper Research

    Retailer spending on AI to rise, says Juniper Research

    Juniper Research predicts global retailer spending on AI will reach US$7.3 billion a year by 2022, up from an estimated $2 billion for this year.

    Its report AI in Retail: Disruption, Analysis and Opportunities: 2018-2022 says retailers will heavily invest in AI tools that let them differentiate and improve customer services. These range from automated marketing platforms that generate tailored, timely offers to chatbots that provide instant responses to customers.

    Juniper found that spending will be strongest in customer service and sentiment analytics, where AI can be applied to understand reactions to purchased products and service received.

    It predicts retailer spending share in 2022 as:

    1. Customer service/sentiment analytics, 54 per cent
    2. AI-based automated marketing, 30 per cent
    3. Demand forecasting, 16 per cent.

    Juniper predicts retailers will use AI insights to design product ranges as well as create targeted promotional offers.

    “Retailers are looking to replicate the success of Amazon in making AI a core part of their business,” says research author Nick Maynard.

    He says retailers will increasingly turn to tactics such as AI-optimised pricing and discounting, as well as demand forecasting.

    With the advent of specific days for shopping, such as the Black Friday phenomena, understanding customer demand and planning appropriately is more important than ever, says the report.

    Juniper says retailers need to invest in this area in order to stay competitive, particularly in low-margin retail segments. Also, the cost of AI tools, now uneconomical for many players, will drop by 8 per cent over the next four years, helping realise 300 per cent growth in software spend.

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  • Japan sees investors flock to AI, big data funds

    Japan sees investors flock to AI, big data funds

    Funds that are oriented towards artificial intelligence (AI) and big data are attracting Japanese investors, according to the latest data compiled by QUICK Asset Management Research Center. This happens as popular monthly-distribution trusts are registering a net outflow of funds.

    The latest data on fund flows for investment trust management companies shows that individual investors are being lured to trusts that focus on AI and other cutting-edge technologies.

    Daiwa Asset Management, for example, registered a net inflow of JPY 370.1 billion in 2017, the largest among investment trust management companies. A fund for investment in robotics-related stocks, introduced by Daiwa at the end of 2015, continues to lure investors. Goldman Sachs Asset Management also recorded strong sales of a fund for global stock investments utilizing big data.

    Let’s recall that the latest Monex Global Retail Investor Survey conducted from November 27 to December 1, 2017, shows that “Technology” ranked at the top of the most attractive sectors among retail investors in Japan, U.S. and China (Hong Kong). There was no major change in the other sectors. However, while “Finance” was ranked high by retail investors in U.S and China (Hong Kong), “Banks” ranked low in Japan, and a difference in bias was apparent.

    This is in line with the results from the preceding investor survey, which also showed that technology was the most attractive sector for investors in all three regions covered by the survey. Monex explained back then that this interest is largely fueled by almost daily media coverage about advancements in AI and that expectations of technology companies among retail investors are extremely high.

    There has been, indeed, a plethora of news regarding investment into AI, especially in Japan. In November 2017, Xenodata Lab, a Tokyo-based firm that leverages the power of artificial intelligence to provide finance data analytics products to financial services companies, announced that it had secured JPY 250 million in funding from Japanese financial majors, such as Mitsubishi UFJ Financial Group Inc, SMBC, Mizuho, and Okasan Securities.

    And in December last year, Mitsui & Co Ltd (TYO:8031) announced an investment into Preferred Networks, Inc (PFN), a company that specializes in AI technology development and provision, with the focus being on deep learning.

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  • Huawei teams with Baidu on AI development

    Huawei teams with Baidu on AI development

    Huawei has entered a partnership agreement with Chinese search giant Baidu covering AI platforms and technology, internet services and content ecosystems.
    The two companies plan to develop an open mobile and AI ecosystem using Huawei’s HiAI platform and Baidu Brian, a collection of AI assets and services.
    The HiAI platform is being developed on Huawei’s embedded AI chipset, the Kirin 970. The chipset was used in the Huawei Mate 10, the world’s first smartphone powered by an embedded AI chipset, which launched earlier this year.
    The planned joint AI ecosystem will use Huawei’s neural network processing unit and Baidu’s PaddlePaddle deep learning framework to empower AI developers and provide consumers with a rage of AI offerings and smart services.
    In addition, the partners will work together on voice and image recognition for smart devices to enable more efficient human-machine interaction, and jointly build an augmented reality ecosystem for consumers.
    “The future is all about smart devices that will actively serve us, not just respond to what we tell them to do,” commented Richard Yu, CEO of Huawei’s consumer business group.
    “With a strong background in R&D, Huawei will work with Baidu to accelerate innovation in the industry, develop the next generation of smartphones, and provide global consumers with AI that knows you better.”
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