In a world in which people are increasingly willing to trade privacy for convenience, facial recognition seems to be a new frontier. And the foremost pioneers on that frontier now appear to be the folks at Dubai International Airport.
Airport officials plan to install a virtual tunnel-shaped aquarium equipped with 80 supposedly invisible cameras that will identify passengers as they walk through, in lieu of customs agents looking from your passport to your face and back. The first aquarium will be up and running by the end of next summer, according to The National. Emirates customers will be the first to experience the tunnel, but the airport plans to install more until 2020.
Facial recognition is popping up at more and more airports as a way to streamline the process of identifying passengers ahead of boarding, and it has its conveniences. You don’t have to remember your passport or driver’s license or other forms of ID, and the lines will theoretically move more quickly because people don’t have to stop and wait for an official to check those IDs.
Dubai’s aquariums seem to be taking the relaxation idea to a level no one else has thought of, but the aquariums serve a purpose other than to calm passengers as they head to their planes.
“The fish is a sort of entertainment and something new for the traveler but, at the end of the day, it attracts the vision of the travelers to different corners in the tunnel for the cameras to capture his/her face print,” Obaid Al Hameeri, the deputy director general of Dubai residency and foreign affairs, told The National.
The National reports that travelers will be able to register their faces at kiosks, and those scans will presumably be matched up with what the aquarium-tunnel cameras pick up as you pass through.
If the cameras determine you are who you say you are, you’ll get a green light at the end of the aquari-tunnel. If not, you’ll get a red light, and an official will likely conduct extra screening of some kind.
It’s not clear what Dubai airport officials will do with these face scans after they have them. Do they keep them on file, assuming you’ll return? Do they share this information with government officials in the United Arab Emirates? How about with officials in other countries?
And face scans are just part one of a two-part plan. Soon, these aquariums may also have cameras that scan your irises. Just remember that when you’re looking at all the pretty fish.
After decades of false starts, Artificial Intelligence (AI) is already pervasive in our lives. Although invisible to most people, features such as custom search engine results, social media alerts and notifications, e-commerce recommendations and listings are powered by AI-based algorithms and models. AI is fast turning out to be the key utility of the technology world, much as electricity evolved a century ago. Everything that we formerly electrified, we will now cognitize.
AI’s latest breakthrough is being propelled by machine learning—a subset of AI which includes abstruse techniques that enable machines to improve at tasks through learning and experience.Although in its infancy, the rapid development and impending AI-led technology revolution are expected to impact all the industries and companies (both big and small) in the respective ecosystem/value chains. We are already witnessing examples of how AI-powered new entrants are able to take on incumbents and win—as Uber and Lyft have done to the cab-hailing industry.
Currently, deployed key AI-based solutions, across industry verticals, include:
Predictive analytics, diagnostics and recommendations: Predictive analytics has been in the mainstream for a while, but deep learning changes and improves the whole game. Predictive analytics can be described as the ‘everywhere electricity’—it is not so much a product as it is a new capability that can be added to all the processes in a company. Be it a national bank, a key supplier of raw material and equipment for leading footwear brands, or a real estate company, companies across every industry vertical are highly motivated to adopt AI-based predictive analytics because of proven returns on investment.
Japanese insurance firm Fukoku Mutual Life Insurance is replacing its 34-strong workforce with IBM’s Watson Explorer AI. The AI system calculates insurance policy payouts, which according to the firm’s estimates is expected to increase productivity by 30% and save close to £1 million a year. Be it user-based collaborative filtering used by Spotify and Amazon to content-based collaborative filtering used by Pandora or Frequency Itemset Mining used by Netflix, digital media firms have been using various machine learning algorithms and predictive analytics models for their recommendation engines.
In e-commerce, with thousands of products and multiple factors that impact their sales, an estimate of the price to sales ratio or price elasticity is difficult. Dynamic price optimization using machine learning—correlating pricing trends with sales trends using an algorithm, then aligning with other factors such as category management and inventory levels—is used by almost every leading e-commerce player from Amazon.com to Blibli.com.
Chatbots and voice assistants: Chatbots have evolved mainly on the back of internet messenger platforms, and have hit an inflection point in 2016. As of mid-2016, more than 11,000 Facebook Messenger bots and 20,000 Kik bots had been launched. As of April 2017, 100,000 bots were created for Facebook Messenger alone in the first year of the platform. Currently, chatbots are rapidly proliferating across both the consumer and enterprise domains, with capabilities to handle multiple tasks including shopping, travel search and booking, payments, office management, customer support, and task management.
Royal Bank of Scotland (RBS) launched Luvo, a natural language processing AI bot which answers RBS, Natwest and Ulster bank customer queries and perform simple banking tasks like money transfers.
If Luvo is unable to find the answer it will pass the customer over to a member of staff. While RBS is the first retail bank in the UK to launch such a service, others such as Sweden’s SwedBank and Spain’s BBVA have created similar virtual assistants.
Technology companies and digital natives are investing in and deploying the technology at scale, but widespread adoption among less digitally mature sectors and companies is lagging. However, the current mismatch between AI investment and adoption has not stopped people from imagining a future where AI transforms businesses and entire industries.
The National Health Services (NHS) in the UK has implemented an AI-powered chatbot on the 111 non-emergency helpline. Being trialled in North London, its 1.2 million residents can opt for a chatbot rather than talking to a person on the 111 helpline. The chatbot encourages patients to enter their symptoms into the app. It will, then, consult a large medical database and users will receive tailored responses based on the information they have entered.
Image recognition, processing and diagnostics: On an average, it takes about 19 million images of cats for the current Deep Learning algorithms to recognize an image of a cat, unaided. Compared to the progress of natural language processing solutions, computer vision-based AI solutions are still in developmental stage, primarily due to the lack of large, structured data sets and the significant amount of computational power required to train the algorithms.
That said, we are witnessing adoption of image recognition in healthcare and financial services sectors. Israel-based Zebra Medical Systems uses deep learning techniques in radiology. It has amassed a huge training set of medical images along with categorization technology that will allow computers to predict diseases accurately better than humans.
Chinese technology companies Alipay (the mobile payments arm of Alibaba) and WeChat Pay (the mobile payments unit of Tencent) use advanced mobile-based image and facial recognition techniques for loan disbursement, financing, insurance claims authentication, fraud management and credit history ratings of both retail and enterprise customers.
General Electric (GE) is an example of a large multi-faceted conglomerate that has adopted AI and ML successfully at a large scale, across various functions, to evolve from industrial and consumer products and financial services firm to a ‘digital industrial’ company with a strong focus on the ‘Industrial Internet’. GE uses machine-learning approaches to predict required maintenance for its large industrial machines. The company achieves this by continuously monitoring and learning from new data of its machines ‘digital twins’ (a digital, cloud-based replica of its actual machines in the field) and modifying predictive models over time. Beyond, industrial equipment, the company has also used AI and ML effectively for integrating business data. GE used machine-learning software to identify and normalize differential pricing in its supplier data across business verticals, leading to savings of $80 million.
GE’s successful acquisition and integration of innovative AI startups such as “SmartSignal” (acquired in 2011) to provide supervised learning models for remote diagnostics, “Wise.io” (acquired in 2016) for unsupervised deep learning capabilities and its in-house the data scientists, and of “Bit Stew” (another 2016 acquisition) to integrate data from multiple sensors in industrial equipment has enabled the company to evolve as a leading conglomerate in the AI business.
Industry sector-wise adoption of AI: Sector-by-sector adoption of AI is highly uneven currently, reflecting many characteristics of digital adoption on a broader scale. According to the McKinsey Global Index survey, released in June, larger companies and industries that adopted digital technologies in the past are more likely to adopt AI. For them, AI is the next wave. Other than online and IT companies, which are early adopters and proponents of various AI technologies, banks, financial services and healthcare are the leading non-core technology verticals that are adopting AI. According to the McKinsey survey, there is also clear evidence that early AI adopters are driven to employ AI solutions in order to grow revenue and market share, and the potential for cost reduction is a secondary idea.
AI, thus, can go beyond changing business processes to changing entire business models with winner-takes-all dynamics. Firms that are waiting for the AI dust to settle down risk being left behind.
The author is Founder and Partner of digital technologies research and advisory firm, Convergence Catalyst.
By Lindsay Brownell, Wyss Institute Communications
What if you could improve your average running pace from 9:14 minutes/mile to 8:49 minutes/mile without weeks of training?
Researchers at Harvard’s Wyss Institute and the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) at Harvard University have demonstrated that a tethered soft exosuit can reduce the metabolic cost of running on a treadmill by 5.4 percent, bringing those dreams of high performance closer to reality.
“Homo sapiens has evolved to become very good at distance running, but our results show that further improvements to this already extremely efficient system are possible,” says corresponding author Philippe Malcolm, former postdoctoral research fellow at the Wyss Institute and SEAS, and now assistant professor at the University of Nebraska, Omaha, where he continues to collaborate on this work. The study appears today in Science Robotics.
Running is a naturally more costly form of movement than walking, so any attempt to reduce its strain on the body must impose a minimal additional burden. The soft exosuit technology developed in the lab of Wyss core faculty member Conor Walsh represents an ideal platform for assisted running, as its textile-based design is lightweight and moves with the body. A team of scientists in Walsh’s lab, led by Wyss postdoctoral fellow Giuk Lee, performed the study with an exosuit that incorporated flexible wires connecting apparel anchored to the back of the thigh and waist belt to an external actuation unit. As subjects ran on a treadmill wearing the exosuit, the unit pulled on the wires, which acted as a second pair of hip extensor muscles applying force to the legs with each stride. The metabolic cost was measured by analyzing the subjects’ oxygen consumption and carbon dioxide production while running.
The team tested two different “assistance profiles,” or patterns of wire-pulling: one based on human biology that applied force starting at the point of maximum hip extension observed in normal running, and one based on a simulation of exoskeleton-assisted running from a group at Stanford University that applied force slightly later in the running stride and suggested that the optimal point to provide assistive force might not be the same as the biological norm. Confirming this suspicion, Lee and colleagues found that the simulation-based profile outperformed the…Continue Reading
Minimalist frames, technology-equipped accessories, 3D printing and lots of multi-functionality make bikes more convenient, safe, fun and beautiful, as proven by these 14 cycling concepts and innovations. With modular parts, commuter-friendly features and designs that make racing more fun for casual cyclists, bikes get a functional makeover for the modern age.
Archont Electro E-Bike
Isn’t this bike a beauty? The Archont by Ono features the profile of a vintage motorcycle, but it’s an electric bicycle with a handcrafted stainless steel frame and 29-inch front wheel. The curvaceous cruiser has a 72-volt battery with a range of 99 kilometers and can go up to 80 km/h.
fUCI Bike: Fast Road Bike for Non-Racers
Most racing bikes are designed to the standards of the UCI (Union Cycliste Internationle), the governing body of every major bike tour in the world, to keep the races fair. But not everyone who wants a fast bike wants to compete in official races, and there are lots of fun features their bikes could have without these regulations. Designer Robert Egger presents fUCI (eff UCI), which has a larger back wheel, electric motor in the hub, a storage space in the wheel and a smartphone mount.
Recoiling Plume Mudguard
This mudguard has literally got your back when it starts raining, keeping you from getting splattered. With a rubber mount stretching to fit any standard seat post size, the simple add-on absorbs shock so it won’t automatically fold up when you hit a bump. Resistant to rust and corrosion, it suspends over the real wheel or retracts within seconds.
Combining two entirely separate sports, the Sno Bike concept by Venn Industrial Design Consultancy features a Z-shaped tensile frame linking a rear wheel to a single ski controlled by the handlebars. How would it actually handle in real-life conditions? It’s impossible to say, since it’s just a concept, but it looks like fun.
Shibusa Bicycle with Swappable Electric-Assisted Parts
This sleek black modular bike can be boosted with electric components or made back into a regular bicycle just by swapping a few parts. The award-winning Shibusa design eliminates the bulkiness associated with many electric bikes for a “hassle-free commuter” offering plenty of flexibility. Modular components include a stand-alone bike light, battery pack, storage rack and charge monitor.
Advanced technology gives us the ability to live better and the opportunity to get things done faster. On the flipside, how and when do you draw the line between accelerated technological progress, while avoiding human obsolescence.
As we embrace new technological phases of progress more fervently, scientifically and compassionately than before, we must be careful to avoid allowing our human value to depreciate. Modern technology is great, as long as we do not allow it to make us lazy and useless. (Taken from the April 11, 2009, article, Blinding “Me” With Science – Tips For Preventing Human Obsolescence)
Have you ever gotten so caught up in watching a game or a video through virtual reality, that you were unable to consciously decipher whether it was real or not? There are several technological applications designed for play or entertainment that add new dimensions of digital components where the real and virtual worlds enhance each other. Such technology transports end-users into a new age of collaboration and thinking.
Virtual reality (VR), a common application and acronym we are familiar with, offers digital recreation of a real life setting. Typically VR headsets are very popular with gamers, entertainment, media, films, and design, by merging the power of 3-dimensional graphics in an artificial environment. Augmented reality (AR) provides virtual elements in a setting that overlay the real world. Mixed reality (MR) on the other hand, sometimes referred to as Hybrid reality (HR) merges and interrelate the real and virtual worlds, which reacts to each other in real-time environments and visualizations.
Leaders in the tech industry are doing some revolutionary things with motion-activated commands and holograms. VR and AR technology can possibly make a great impact on the medical field. While we are making quantum leaps between virtual, augmented and hybrid worlds, are we also experiencing cautionary symptoms of hyperreality? Hyperreality, a postmodern semiotic concept, coined by French Sociologist and Cultural Theorist, Jean Baudrillard, (according to his book, Simulacra and Simulation), explains a human condition in which the inability to consciously distinguish simulation from the real world really exists.
Technology is reflecting entertainment, reality, and function in radical ways. Of course, there are discussions from various non-tech individuals who seem to agree that addictions to simulated reality, particularly where young people are involved, sometimes gives evidence of real-time life encounters handled through the lens of the 3-D world. For example, kids may not truly understand the consequences resulting from the danger of handling an unsecured weapon and mimicking a VR fight scene that could have fatal consequences.
So what do you think? With such amazing software used to create entertainment for these devices, can hyperreality become such a threat that many gamers may not be able to logically distinguish hybrid reality from the real world?