The new funding will enable Ubie to accelerate its growth and strengthen its presence in the U.S., following strong interest and traction in that market. To date, Ubie has raised $76 million in total. It will also focus on expanding its business to the U.S. in order to apply the technology it has developed in Japan, one of the leading countries in the medical field. This is the second overseas corporation following Singapore. The decision follows the fact that the number of users has been increasing steadily since the release of the AI symptom checker in April 2022 in the U.S. The establishment of the local subsidiary will further strengthen the partnership with U.S. pharmaceutical companies, as well as the products, including hiring local people in the U.S. Ubie is a Japanese health-tech startup founded by a medical doctor and an engineer in 2017.

Business automation and digital transformation have become key to securing the future of businesses around the world. One of the more recent extensions of the concept of transformation is hyperautomation. Hyperautomation technology takes automation opportunities one step further. The term was coined by industry analytics and consultancy firm Gartner. Gartner defines hyperautomation as a "business-driven, disciplined approach that organizations use to rapidly identify, vet, and automate as many business and IT processes as possible." The concept combines automation tools and technologies with emerging technologies.

As Business Insider reports, "most banks (80 percent) are highly aware of the potential benefits presented by AI and machine learning. In fact, many banks are planning to deploy solutions enabled by AI: 75 percent of respondents at banks with over $100 billion in assets say they're currently implementing AI strategies, compared with 46 percent at banks with less than $100 billion in assets," according to a UBS Evidence Lab report. Business Insider further notes that many banks are using AI in front-office applications "to smooth customer identification and authentication, mimic live employees through chatbots and voice assistants, deepen customer relationships, and provide personalized insights and recommendations." In middle-office functions, the UBS report states, AI is being used to assess risk, detect and prevent fraud, improve processes to prevent money laundering, and perform know-your-customer regulatory checks. "The winning strategies employed by banks that are undergoing an AI-enabled transformation reveal how to best capture the opportunity. These strategies highlight the need for a holistic AI strategy that extends across banks' business lines, usable data, partnerships with external partners, and qualified employees."

DeepView is an AI technology recognizing human behavior. As it can be applied to preventing safety accidents caused by drinking, fainting, etc. and performing prompt emergency rescue measures. It is expected to become the core technology for making a safe city. Most existing behavior recognition technologies have a two-stage structure of detecting a person first and then recognizing the position of him/her. Therefore, they had problems of not detecting well a person with atypical postures, such as being crouched or collapsed, compared to a standing person.

A Korean research team developed a technology for detecting humans lying on the road in real-time. Therefore, preventing safety accidents in the city and rapidly responding to it will be possible, and a safer society is expected to be accomplished. The Electronics and Telecommunications Research Institute (ETRI) announced that it applied the technology of Visual AI ‘DeepView’ to Daejeon Metropolitan City in earnest to prevent safety accidents in the city and promptly respond to them. DeepView is an AI technology recognizing human behavior. It detects people lying on the road through surveillance cameras in real-time. As it can be applied to preventing safety accidents caused by drinking, fainting, etc. and performing prompt emergency rescue measures. It is expected to become the core technology for making a safe city.

There is a heated debate on the state of the race between the United States and China to dominate in AI. But perhaps the more strategic question is whether China is building the metaverse. Built upon infrastructural technologies like AI, the metaverse refers to the vast array of digital experiences and ecosystems, from e-commerce and entertainment to social media and work, where we spend more and more of our lives. It's soon going to be hard to conceive of a world in which much of our social and economic lives are not defined by the rules of the metaverse. To the builder goes the opportunity to establish rules to their own benefit.

When automation is a core technology, transformation can occur at speed, meaning faster return on digital investment. Insurers that are heavily dependent on traditional business models have struggled over the past year with financial strain. But automation presents an opportunity to establish short-term successes to speed up recovery and long-term results that can stimulate growth by accelerating digital transformation. Customer expectations are at an all-time high as digital-native brands like Amazon continue to dominate and set standards that are difficult for other companies to copy. These standards don't only appear in business-to-consumer transactions but also in business-to-business transactions that include promoting product innovation and mix.

As we noted at the beginning of this series on the AI bank of the future, disruptive AI technologies can dramatically improve banks' performance in four key areas: higher profits, at-scale personalization, smart omnichannel experiences, and rapid innovation cycles. The stakes could not be higher, and success requires a holistic transformation spanning all layers of the organization's capability stack. Our previous articles have focused on the capability stack's technology layers: reimagined engagement, 1 1. Leveraging these capabilities to create value requires an operating model combining structure, talent, culture, and ways of working to synchronize all layers of the stack. Synchronizing these layers is not easy. Any organization undertaking an AI-bank transformation must determine how to structure the organization so that its people interact and leverage tools and capabilities to deliver value for each customer at scale. In this article, we take a closer look at the need for a platform operating model, the categories and scope of operating models, and the building blocks of effective models.

It's hard to imagine the world without all the technology of today that have transformed the way we live, work and play. It wasn't long ago when we had to stop to look at a map or ask for directions. It used to take days to see a doctor, but with the power of technology, like wearable digital health meters, you can get information to and from your doctor in real time. Video games meant playing a simple game of "Pac-Man" to now being able to be virtually transported to be part of a game. These examples play a role in how digital experiences have enriched and changed the way we live our daily lives.

NanoSniff has partnered with Vehant Technologies, a pioneer in Artificial Intelligence/Machine Learning- based physical security, surveillance and traffic monitoring and junction enforcement solutions. Union Education Minister, Ramesh Pokhriyal'Nishank' has launched NanoSniffer, a Microsensor based Explosive Trace Detector (ETD) developed by NanoSniff Technologies, an IIT Bombay incubated startup. NanoSniffer has been marketed by Vehant Technologies, a company that was incubated at IIT Delhi as a startup in 2005. A 100 per cent'Made in India' product in terms of research, development & manufacturing, the core technology of NanoSniffer is protected by patents in the US and Europe. Given the constant threats, which our nation faces due to geo-political realities, explosives and contraband detection has become a norm at high security locations like airports, railways and metro stations, hotels, malls and other public places.