Karl Benz and Henry Ford revolutionized transportation with the initial development and mass production of the automobile. Now, more than a century later, the automotive industry is poised to transform transportation again, with a push to develop connected, personalized and autonomous driving experiences, electric vehicles and new mobility business models from ride-sharing to ride-hailing and multimodal, smart transportation concepts. This industry is expected to see significant growth, becoming a $6.6T industry by 2030, with disruptive business models accounting for 25 percent of all revenues, according to consulting firm, McKinsey & Company. From shared vehicle services to fully electric transportation, manufacturers are developing new products and services to enable large fleets offering mobility-as-a-service, which will increasingly replace individual car ownership. This involves modernizing the in-vehicle experience with productivity, entertainment, and personal assistants that are safe and secure, following users across different transport modes, adding value for businesses and consumers alike.

Between 2018 and 2019, organizations that have deployed artificial intelligence (AI) grew from 4% to 14%, according to Gartner's 2019 CIO Agenda survey. AI is reaching organizations in many different ways compared with a few years ago, when there was no alternative to building your own solutions with machine learning (ML). AutoML and intelligent applications have the greatest momentum, while other approaches are also popular -- namely, AI platform as a service or AI cloud services. Conversational AI remains at the top of corporate agendas spurred by the worldwide success of Amazon Alexa, Google Assistant and others. Meanwhile, new technologies continue to emerge such as augmented intelligence, edge AI, data labelling and explainable AI.

Aviva Canada with Amazon Echo helps consumers find answers to common insurance questions and get an insurance quote. If a person is curious about accident benefits, for example, all they have to do is ask, "Alexa, what is my accident benefits coverage?" Manulife with Amazon Echo advises customers on what is left on their health benefits. Need new glasses but not sure how much coverage you have? Simply ask, "Alexa, ask Manulife Benefits how much I do have left for glasses?"

Two lovers hold hands across a table, overlooking a virtual vista of the Mediterranean. As the pair exchange sweet nothings, the fact they are actually sitting thousands of miles apart bears little significance on the romantic experience. The couple was deemed "hyper-compatible" by online dating technology that matched them using a search engine infused with artificial intelligence (AI). Using data harvested about their social backgrounds, sexual preferences, cultural interests, and even photos of their celebrity crushes, they were thrust together in a virtual reality of their own design. This technology is in the early stages of development.

Artificial intelligence (AI) has come a long way in recent years. For example, AI has defeated the human world champion of Go, recreated the periodic table of elements, enabled self-driving vehicles, identifed crop diseases, and predicted depression from speech. Imagine what could happen as AI improves capabilities in areas that are squarely in the domain of the human brain. Today, technology is far from achieving parity with human-level intelligence, also known as "strong AI" or artificial general intelligence (AGI). Recent AI advances in one capability--pattern recognition--has spawned an investment gold rush for AI startups and machine learning talent from venture capital, corporations, and governments who have recognized the potential competitive advantage.

Whether you use an Amazon, Google or Apple smart speaker, concerns about what these devices are sending back to the mothership are becoming more widespread. Consumer Reports takes a look at just how concerned you should be, and what you can do to control your digital privacy with these connected devices. They enjoyed their first digital assistant so much they decided that one wasn't enough. "I believe we have five," Rhee said. But when it comes to how these connected devices work, Eric has some concerns -- especially when it comes to the privacy of his two young daughters.

SINGAPORE (Sept 10): Move over, Siri. Here comes OCBC with its own artificial intelligence digital assistant. In a first for Singapore, customers of OCBC Bank can now pay their bills, check account transactions and track expenses by talking to their phones. The new voice-activated banking service, called OCBC Banking Assistant, was developed and trained over 13 months. It has been taught how customers in Singapore speak.

Globally, the adoption of wearable artificial intelligence (AI) will be primarily driven by increasing concerns among consumers towards health and fitness. Rising prevalence of obesity and other cardiac illnesses around the world will boost the adoption of these devices. Wearable AI gadgets such as smartwatches and fitness bands are equipped with sensory hardware to monitor health-oriented vitals, including heart rate and blood pressure and can help improve early detection of diseases. Innovative advances in technology have resulted in continuous enhancements in the design and functionality of smart wearables. The availability of these devices at affordable prices will create a large consumer base for wearable gadgets in the coming years.

Recommender systems are personalized: we expect the results given to a particular user to reflect that user's preferences. Some researchers have studied the notion of calibration, how well recommendations match users' stated preferences, and bias disparity the extent to which mis-calibration affects different user groups. In this paper, we examine bias disparity over a range of different algorithms and for different item categories and demonstrate significant differences between model-based and memory-based algorithms.

The demand for Itinerary Planning grows rapidly in recent years as the economy and standard of living are improving globally. Nonetheless, itinerary recommendation remains a complex and difficult task, especially for one that is queuing time- and crowd-aware. This difficulty is due to the large amount of parameters involved, i.e., attraction popularity, queuing time, walking time, operating hours, etc. Many recent or existing works adopt a data-driven approach and propose solutions with single-person perspectives, but do not address real-world problems as a result of natural crowd behavior, such as the Selfish Routing problem, which describes the consequence of ineffective network and sub-optimal social outcome by leaving agents to decide freely. In this work, we propose the Strategic and Crowd-Aware Itinerary Recommendation (SCAIR) algorithm which takes a game-theoretic approach to address the Selfish Routing problem and optimize social welfare in real-world situations. To address the NP-hardness of the social welfare optimization problem, we further propose a Markov Decision Process (MDP) approach which enables our simulations to be carried out in poly-time. We then use real-world data to evaluate the proposed algorithm, with benchmarks of two intuitive strategies commonly adopted in real life, and a recent algorithm published in the literature. Our simulation results highlight the existence of the Selfish Routing problem and show that SCAIR outperforms the benchmarks in handling this issue with real-world data.