The AI Eye Epsode 357: Patriot One's Xtract Technologies Collaborating with AWS (NasdaqGS: $AMZN) and Others on AI Radiology Solution for COVID-19

Point Roberts, WA and Vancouver, BC - May 28, 2020 ( Newswire) (, a global investor news source covering Artificial Intelligence (AI) brings you today's edition of The AI Eye - watching stock news, deal tracker and advancements in artificial intelligence.

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The AI Eye Epsode 357: Patriot One's Xtract Technologies Collaborating with AWS (NasdaqGS: $AMZN) and Others on AI Radiology Solution for COVID-19


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Today's Column - The AI Eye - Watching stock news, deal tracker and advancements in artificial intelligence

Stocks discussed: (TSX:PAT) (OTC:PTOTF) (NasdaqGS:AMZN) (NasdaqGS:NICE)

Xtract Technologies (Xtract AI), a wholly-owned subsidiary of Patriot One Technologies Inc. (TSX:PAT) (OTC:PTOTF) (FRANKFURT: 0PL), is collaborating with Amazon Web Services (AWS), a subsidiary of Amazon (NasdaqGS:AMZN), Vancouver General Hospital, the University of British Columbia (UBC), and SapienML, and others in the development of an Artificial Intelligence (AI) solution to help radiologists identify the increased risk of the COVID-19 virus. Data derived from CT and X-ray scans obtained from around the world, is being used by the Xtract AI team to train "innovative 3D residual networks, a particular style of AI algorithm, to automatically identify" affected areas of the lung that help indicate COVID-19. Martin Cronin, CEO of Patriot One Technologies, said

"This is an incredibly important project, which we are proud to be a collaborator on, and we hope that our team and technology can provide a meaningful addition to the ongoing efforts to minimise COVID-19's impact on the world."

Dr. William Parker, the project lead and a radiology resident at UBC, explained:

"AI models are not magic, but this model we've developed is an open source gift to start answering questions. If we are going to get to the point of helping patients, we need to know the strengths and weaknesses of the models, and we need to have an understanding that not all models are created equal. The goal of our AI model is to drive feedback so that we can improve the model and make it available for clinical use in the fall of 2020."

Alfa-Bank, one of Russia's largest private commercial banks, has seen customer experience improvement after adopting AI-powered analytics solutions from NICE Ltd. (NasdaqGS:NICE), according to an announcement today. According to the press release, Alfa-Bank "leverages NICE Nexidia Analytics and NICE Quality Central to automatically analyze interactions and identify call topics that resonated with customers or areas needing improvement," enabling it "to proactively drive up positive experiences while improving service processes." Ivan Pyatkov, Director of Digital Business, Member of the Alfa-Bank Board, commented:

"This project, driven by the NICE Nexidia Analytics and Quality Central, has exceeded our expectations. The system has already driven significant revenues for the bank owing to growth in sales, optimization of service processes and improved loyalty last year, and in 2020 we expect to see continued substantial growth in profits."

Global AI in Manufacturing Market to Reach $9.89 Billion by 2027

A report from Fortune Business Insights finds that the global AI in Manufacturing market will grow from $1.82 billion in 2019 to $9.89 billion by 2027 with a compound annual growth rate (CAGR) of 24.2 percent in the forecast period. An excerpt from the report summary outlines some key drivers in the market:

Manufacturers are witnessing the need for production optimization in industries such as chemical, automotive, semiconductor & electronics, among others on a large scale. Artificial intelligence and machine learning are powerful tools to minimize the consumption of resources and energy in every industrial process. Manufacturing companies are using these technological models to optimize power consumption and resources. The advancements of artificial intelligence (AI) and machine learning (ML) have opened new horizons for production optimization. AI and ML support to build a statistical model using the available data from many sources such as a reading of many sensors, initial material used for manufacturing, and more. Based on this data it helps the manufacturer to predict accurate parameters of the final product. Furthermore, it prevents extra losses and gives the exact amount of materials/additives required for manufacturing a particular product reducing extra cost. Moreover, this enables the businesses to make the production cost-effective.

Sam Mowers,

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