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Why AI-enabled decision-making is the next step in the supply chain digitalisation journey

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As a result, companies have gone through a decade's worth of digital transformation in just a matter of months, with the pandemic forcing them to refresh archaic processes with AI, machine learning, and data science technologies. Such technological advancements will continue to evolve and further establish themselves as a critical component to managing complex logistical landscapes – from improving efficiency and mitigating the effects of a global labour shortage, to identifying more robust and dependable ways to move commodities. In a world where uncertainty is the only certainty, AI-enabled order and inventory visibility across shipments will also be vital to'keep the wheels in motion.' Most importantly, to provide real-time updates on changes to arrival times and to identify potential disruptions before and as they occur. Take the recent congestion issues at the Port of Los Angeles, for example.


Driving Intelligence in Power Management through Digitalization & IoT - Express Computer

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In this decade of 21st century, world is seeing very different challenges in the power management in Power Generation, transmission, distribution & consumption. As most of the countries are taking on challenges on sustainability goals, there is significant Energy Transition happening towards more & more GREEN energy. Lot more sources of energy like Wind, Solar are becoming more viable and being adopted. However, this has put a clear expectation on adding intelligence into the existing products & solutions to manage this transition as well as adopting new digital software-based solutions. With the rapid advancement in the IoT & Cloud infrastructure, creating this intelligence is now feasible and economically viable.


Technology industry artificial intelligence venture financing deals total $913.7m in Asia-Pacific in April 2022

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Copy and paste the image source into your website to display the chart. The value marked a decrease of 29.2% over the previous month of $1.29bn and a drop of 37% when compared with the last 12-month average of $1.45bn. Asia-Pacific held an 18.68% share of the global technology industry artificial intelligence venture financing deal value that totalled $4.89bn in April 2022. China was the top country in Asia-Pacific's artificial intelligence venture financing deal value across technology industry. In terms of artificial intelligence venture financing deal activity, Asia-Pacific recorded 83 deals during April 2022, marking a decrease of 21.70% over the previous month and a rise of 2.47% over the 12-month average.


Artificial Intelligence: Its benefits and challenges - Clover Infotech

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Artificial Intelligence was first popularized by a small group of scientist gathered at the Dartmouth College in the United States in 1956. Since then, AI has advanced considerably and is powering many real-world applications ranging from facial recognition to language translators and virtual assistants such as Siri and Alexa. Still, we are far from witnessing AI-powered robots emulating humans. So far that is confined to the Sci-Fi movies. However, AI has created quite a stir in the business world with its many benefits and challenges.


How AIOps Help Businesses Optimize Their IT Operations?

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Artificial intelligence for IT operations, mainly acknowledged as AIOps, is the talk of the town these days, but people talk less about the way to implement AIOps. However, to implement AIOps successfully, businesses must know the process and tools needed at each stage. And, yes, AIOps will help businesses optimize their IT operations. Today, IT companies operate in complicated and extensive environments, often while connecting on-premises and private and public clouds legacy setups. IT leaders, managers, and teams are usually under pressure to serve the business with their end-to-end IT operations and services. The enterprise's core focus is to prevent the most significant instances and any downtime.


Pharma 4.0TM -- Key Drivers, Game-Changers, Technologies

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The Digital era has been a boon to the industry. But pharma manufacturers deal with increasingly complex challenges in this digital era. Pharma manufacturers need a holistic approach to increase quality, safety, transparency, agility, and productivity. Pharma 4.0TM, a term coined by ISPE (International Society for Pharmaceutical Engineering) is a concept adopted from Industry 4.0. The concept aims to bring in an interactive system, analytical data, advanced automation, and a simplified regulatory framework.


Artificial Intelligence as a Service- Changing Future Dynamics of Business Solutions - Digital Journal

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The rising number of innovative start-up operations working within the domain of AI powered tools and services is one of the key factors driving the growth within the global artificial intelligence as a service market. The solutions offered by the players and vendors functioning within the global artificial intelligence as a service market are utilized in a number of end use industry verticals, such as healthcare and life sciences, telecommunications, manufacturing, education, transportation, media and entertainment, banking, financial services, and insurance or BFSI, retail, government and defence, energy, and agriculture, among others. Some of the key technologies used by the players in the global artificial intelligence as a service market include deep learning, natural language processing or NLP, and machine learning or ML. The rising demand from the BFSI industry vertical is positively influencing the growth in the global artificial intelligence as a service market. On the other hand, healthcare and life sciences end use industry vertical is also expected to contribute heavily in the development of the global artificial intelligence as a service market in coming years.


Edge AI vs. Cloud AI: Which is Best for Your Business?

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In an ideal deployment, all workloads would be centralized in the cloud to enjoy the benefits of scale and simplicity. These deployments can take on the form of edge AI and/or cloud AI, each offering their own potential unique use cases, benefits, and challenges. With this in mind, it will take careful consideration when choosing the best model for your business. Edge AI and cloud AI play a complementary role in ensuring the models serving AI deployments are continuously improving without compromising on data quality and quantity. Cloud AI complements the instant decision-making of edge AI by providing deeper insights for more longitudinal data.


5 Trends in Medical Health Technology in 2022

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It is predicted that technologies such as artificial intelligence (AI), cloud computing, extended reality and the Internet of Things (IoT) will be introduced further among related workers, leading to the development and provision of new and better treatments and services. In the months following the outbreak of the COVID-19 outbreak, the proportion of telemedicine consulting has risen sharply from 0.1% to 43.5%, and is expected to rise further in the future, as this trend could save more patients' lives, said Deloitte Accounting Firm analyst. . To achieve this goal, the next-generation portable device, heart rate, stress, and blood oximetry, enables doctors to accurately determine the patient's condition in real time. During the COVID-19 period, doctors built'virtual hospital rooms' in some areas to observe the treatment status of patients in various areas through the central communication infrastructure. The Pennsylvania Emergency Medical Center is developing a high-quality'virtual emergency room'.


Artificial Intelligence to Support UAVs in Healthcare

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Unmanned aerial vehicles (UAVs), or simply drones, are used in a plethora of civil applications due to their ease of deployment, low maintenance cost, high mobility, and ability to hover. A main advantage of drones is that, in contrast to other vehicles, they are not restricted to traveling over a road network and thus, can swiftly move over disperse locations. Such vehicles are utilized for many applications such as the real-time monitoring of road traffic, civil infrastructure inspection, wireless coverage, delivery of goods, security and surveillance, precision agriculture, and healthcare. Regarding the latter, drones can be utilized in natural disaster relief, as search and rescue units, as transfer units, and to support telemedicine. For drones to be efficient in such applications, their scheduled and coordinated flying is crucial. Moreover, given that drones typically use an electric motor and store the required energy in batteries, their scheduled charging is crucial to maximizing their availability.Controlling drones demands efficient algorithms that can solve problems that involve a large number of heterogeneous entities (e.g., drones’ owners), each one having its own goals, needs, and incentives (e.g., amount of goods to transport), while they operate in highly dynamic environments (e.g., variable number of drones) and having to deal with a number of uncertainties (e.g., future requests, emergency situations). In this context, artificial intelligence (AI) techniq...