From the onset of the Covid-19 pandemic, artificial intelligence (AI) has been used to support the unprecedented fight against the resulting crisis[1], albeit with some reservations due to operational and ethical issues. The scientific community, along with policy-makers and the media industry worldwide, has emphasized AI's potential utilization to optimize the fight against the virus on multiple fronts, including healthcare, economy, trade, global travel, technology, safety and preventative measures against future outbreaks. Thus far, AI has helped authorities in many countries curb the Covid-19 pandemic's spread in several significant ways. For instance, AI has been used to notify health authorities about excess occupancy of public spaces and potential severe health risks posed by virus clusters.[2] In the infrastructure sector, innovative technologies have been used to help monitor the flow of people and vehicles along roads through radars, thus helping to ensure compliancy with emergency measures.

Being the Silicon Valley hi-tech giant, Google has started implementing cutting-edge technologies like artificial intelligence to provide efficiency to the world. Google AI conducts research to advance the state-of-the-art through AI-based software. AI at Google develops artificial intelligence tools to ensure that the world can access the strong and smart functionalities of AI. The mission of Google AI is to organize the real-time information and make it accessible to the world for multiple different useful purposes for each and every sector. The implementation of artificial intelligence has offered Google Translate, Google Assistant, and many more with new ways of solving real-life complicated problems.

Know how Google AI leverages artificial intelligence to protect and help the global community.

Current shortages of retail team candidates will make it difficult to keep your store operations functioning properly.

As per the definition found in Britannica by Copeland, AI is commonly referred to as a computer system with human intellectual features, e.g., reasoning, discovering, generalizing, and learning from prior exposure [1,2]. U.S Food and Drug Administration (US-FDA) has also stated in 2019 that AI has the potential to transform the healthcare industry by its ability to derive new information from the vast dataset that feeds into it [2,3]. Machine learning (ML) can be simply understood as a subset of an application of AI in which machines analyze and use a large dataset to produce unique algorithms capable of "statistical learning" as described by Gutierrez [2]. The use of ML has surged in critical care in the field of the discovery of drugs, diagnostic tools, medical imaging, and therapeutics amongst others. It can potentially help us better understand the vast set of data available to us in an intensive care unit (ICU) and apply it to tackle a multitude of medical conditions [2,4]. ML can be divided into two main models based on learning tasks, which are supervised and unsupervised learning algorithms.

The white paper provides an overview of the current situation of TB diagnosis and screening in Vietnam, and introduces the AI model developed by …

Similar to that at the RSNA, AI developed at the University of Toronto and the Center for Addiction and Mental Health trained their Al deep learning algorithm with data from the Alzheimer's Disease Neuroimaging Initiative through the National Institutes of Health's National Institute on Aging using data from over 800 geriatric patients ranging from healthy to mild cognitive impairment to Alzheimer's disease. Their algorithm was found to be able to accurately predict cognitive decline leading to AD in cohorts by analyzing brain scans, clinical data, and genetics by up to 5 years before symptoms appear; research was published in PLOS Computational Biology.

The Seattle Seahawks will now be utilizing Amazon Web Services in bringing artificial intelligence ... [ ] and machine learning to their game preparation in hopes to make more efficient on the field decisions. Amazon has deep roots in Seattle which are about to get deeper. The company announced it will be expanding its services within the NFL, after partnering with the Seattle Seahawks to provide the team with its cloud and machine learning/artificial intelligence offerings. In the comprehensive partnership, the company will move the vast majority of its infrastructure to AWS and will also provide wide-ranging services, including computing, storage and database, as well as analytics intended to drive game strategy decisions for the team. Amazon's NFL Next Gen Stats offering has been providing player tracking data throughout this season and the Seahawks will utilize their data, that tracks the position of the ball on the field as well as every player 10 times per second, to provide detailed information on each player's impact on the field.

Artificial intelligence can streamline the manufacturing process in several ways. First, AI can be used to take over repetitive tasks that would cause injuries to human workers over time. Second, AI can forecast demand and correlate that with scheduling to optimize production timing, saving costs on overtime, electricity, excess inventory and more. Excess inventory costs companies $443 billion each year, and one AI solution applied to this problem reduced one company's inventory overages by 20 percent, double the predicted savings.

With the exponential growth of Artificial Intelligence based applications in various fields, it is now making its way to the space. Japan government plans to use Artificial intelligence to analyze images of earth captured by the satellites to predict and prevent disasters. AI based analysis could be used to develop new services for disaster management in areas prone to high occurrence of disasters. The main idea is to use AI to monitor any change in the images and predict the risk of disasters. For example, changes in the steep slopes could be an indication for landslides, or changes in sea behavior may imply arrival of tsunami.