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Artificial intelligence, smart urban management on show - SHINE News

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Shanghai-based artificial intelligence companies and the latest adoptions for smart urban management will be highlights at the Exposition on China Indigenous Brand at the Shanghai Exhibition Center starting Monday. Shanghai Fokan Technology Co, which specializes in graphic encoding and data-mining capability with its own high-resolution camera with resolution of 1 billion pixels, is presenting its products and solutions. By combining the algorithms and hardware for surveillance video cameras, it aims to become the data channel for a wide variety of applications related to artificial intelligence. Based on research projects at Fudan University and the Changchun Institute of Optics, Fine Mechanics and Physics of the Chinese Academy of Science, it's now offering airport smart management solutions at two dozen domestic airports by bringing scattered video surveillance footage in an integrated real-time data platform. Fokan Tech said it managed to build cutting-edge optic sensors and image recognition algorithm into one single smart camera which can detect images of humans, vehicles and aircraft within four square meters.


The Convergence of Artificial Intelligence and Industrial IoT

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AIoT, the confluence of AI and Industrial IoT technological forces, gives rise to a new digital solution category – the Artificial Intelligence of Things (AIoT). AIoT is built for industrial companies looking for better ways to connect their evolving workforce to data-driven decision tools and digitally augment work and business processes and making better use of industrial data already collected. ARC Advisory Group has observed that the convergence and overlap of IT and OT groups, driven largely by the digital transformation of industry in recent years has created organizational confusion and a significant "gray-space" of common technologies between each area, one area being AI. However, leveraging AI requires data science capability, which adds additional complexity to an already complex environment. While engineering roles are skilled in analyzing large amounts of data, setting up and creating production grade machine learning environments is not easily accomplished.


National Digital Transformation and Smarter Cities: Eight Forces That Will Shape the Future

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The world's economy is at a tipping point as digital technologies continue to be embedded into both working and personal lives at an unprecedented rate. By 2023, digitally transformed enterprises will account for more than half of global Gross Domestic Product (GDP). Two overarching factors will drive this trend: the proliferation of digital devices and the rising prominence of the millennial and zoomer (Generation Z) user base. These digital-savvy generations account for 75% of the population in the Middle East today. By 2025, the number of connected devices globally is predicted to reach 100 billion, more than 12 times the number of people in this world.


Quick Apply: 7 Lucrative Data Science Internships in May 2021

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Data science is one of the ground-breaking fields for students who have a knack and a keen eye for details in the world of science and technology. Companies are in dire need of aspiring data scientists for proper usage of the continuous flow of real-time data to enhance the business in the competitive world. The future of a company is dependent on data science due to the upsurge of raw data in the tech-savvy era. So, what is the best way to kick-start your career in data science? Analytics Insight has made you a list of seven reputed companies that have vacancies for data science internships.


How Marketers Can Truly Embrace AI and Maximize Its Benefits

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One of the biggest challenges that marketers are facing today and struggling with is the massive amount of data that we see in our line of work, day in and day out. Some would like to call it "data overload," which is only getting compounded due to the speed at which we're getting data in ever-increasing ways. I like to say, and I am sure other marketers will agree, whenever we are putting together any strategic plan, we start with the data. We say, "What does the data tell us?" Data dictates everything that we do, from what people say on social media and review sites about our brands and products to our customers' suggestions on things that we should consider implementing, like a new soda flavor or a new travel route. Further, there are times when the data that comes to marketers also gives us a kernel of insight into potential consumer trends that may impact our brands and products.


Top 10 Artificial Intelligence Innovation Trends to Watch Out For in 2021

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Although the COVID-19 pandemic affected many areas of industry, it did not lessen the impact of Artificial Intelligence in their daily lives. Thus, we can assume that AI-powered solutions will undoubtedly become more widely used in 2021 and beyond. Knowledge will become more available in the coming years, putting digital data at higher risk of being hacked and vulnerable to hacking and phishing attempts. AI and new technologies will help the security service in combating malicious activities in all areas. With strengthened safety initiatives, AI can help prevent cybercrime in the future.


How is Novartis Capitalizing on AI for Medical Innovations?

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Artificial intelligence is nothing strange now, as it is being used by almost all businesses in different industries. The rapid digital transformation and technology adoption in recent years has led many companies to extensively invest in AI to drive growth. Novartis International AG is a leading global healthcare company, based out of Switzerland, that has been efficiently capitalizing on its AI capabilities to develop medical innovations. Novartis incorporates digital and disruptive technologies to create transformative treatment and drug discoveries. Everybody is trying to adopt AI, but how many focus on an ethical approach?


New Aerospike release brings Spark 3.0 compatibility

ZDNet

At its Digital Summit virtual event today, real-time NoSQL database player Aerospike announced a new release of its eponymous product. The v5.6 release adds a few features that together are designed to optimize the loop of real-time data processing and machine learning at the edge and "core" (cloud or corporate data center). The scenarios furthermore involve training machine learning (ML) models at the core from edge data, then pushing the models back to the edge for inferencing. ZDNet spoke with Aerospike founder and Chief Product Officer Srini Srinivasan, who briefed us on the three features that facilitate and optimize this virtuous data/ML cycle. The Aerospike connector for Spark allows real-time and historical data in the database to be used for training ML models, without requiring that data to be exported first.


Accelerating AI, Cloud, 5G, and IoT Innovation

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Artificial Intelligence (AI), Cloud, 5G, and IoT are continuously advancing innovation that extends across business development all the way down to the consumer level. Critical innovations are emerging from the escalation of new technologies, including hybrid workforces, remote healthcare delivery, hyper-personalization, and zero-touch. These use cases are generating myriad benefits for both organizations and consumers, and inspiring new levels of efficiency, productivity, and engagement. We're currently witnessing a dynamic surge in technological advancement that has spawned the era of ubiquitous digital transformation, but these new technologies still need room to grow. Ronald van Loon is working in partnership with NVIDIA, and recently had the opportunity to discuss the technology trends and drivers shaping the post-pandemic future, and assess the role the Arm acquisition by NVIDIA is positioned to play in this development.


Using AI to Track How Customers Feel -- In Real Time

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In order to succeed, firms need to understand what their customers are thinking and feeling. Companies spend huge amounts of time and money in efforts to get to know their customers better. But despite this hefty investment, most firms are not very good at listening to customers. It's not for lack of trying, though -- the tools they're using and what they're trying to measure may just not be up to the task. Our research shows that the two most widely used measures, customer satisfaction (CSAT) and Net Promoter Scores (NPS), fail to tell companies what customers really think and feel, and can even mask serious problems.