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The AI Eye: Accenture (NYSE: $ACN) Driving Innovation for Changi Airport with DIVA Factory, Currux Vision and Costar Technologies (OTC: $CSTI) Announces Results of Smart City AI Test


Point Roberts, WA and Vancouver, BC - March 9, 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: Accenture (NYSE: ACN) Driving Innovation for Changi Airport with DIVA Factory, Currux Vision and Costar Technologies (OTC: CSTI) Announces Results of Smart City AI Test


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

Stocks discussed: (NYSE:ACN) (OTC:CSTI)

Accenture (NYSE:ACN) is assisting Changi Airport Group (CAG) in Singapore with the establishment of a digital factory to drive innovation. Called DIVA (digital, innovation, ventures and analytics), the factory will allow CAG to develop, experiment and launch new digital products and services by leveraging artificial intelligence (AI), digital marketing, big data / analytics, predictive maintenance and the internet of things (IoT). Jeffrey Loke, a senior vice president at CAG, commented:

"By establishing DIVA with Accenture, we hope to continue to foster a culture of innovation and experimentation, by injecting new ways of working within our organization. DIVA is helping CAG implement digital innovations, at speed and at scale, at the enterprise level, serving all CAG departments, including commercial, operations, engineering, IT, and corporate marketing & communications."

AI and Deep Learning solutions company Currux Vision Corp. and camera and surveillance provider Costar Technologies, Inc. (OTC:CSTI) have announced the results of a test "for a fully integrated Smart City AI Traffic Video Analytics and Management Solution with the City of Grapevine, Texas." According to the press release, the "system can operate with 95% - 98% or higher accuracy under various conditions including day and night, rain, camera vibrations, and even partial camera view obstruction." Alex Colosivschi, Founder and CEO of Currux Vision, commented:

"The urbanization, increased traffic, and climate change drive the urgent need for a next-generation traffic monitoring and management solution like our Smart City AI product. Today, the deployment of traffic cameras in cities is hampered by either lack of or subpar autonomous video monitoring systems that require cloud access or extensive high-bandwidth internet infrastructure. We designed the Smart City AI product to significantly accelerate wide-scale adoption of AI-capabilities by cities and businesses both in the US and internationally. We are happy to have a great partner like Costar to accelerate this transition."

Global AutoML Market to Reach $14.511 Billion by 2030

A report from Prescient & Strategic Intelligence finds that the global automated machine learning (AutoML) market will grow from $269.6 million in 2019 to $14.511 billion by 2030 with a compound annual growth rate (CAGR) of 43.7 percent in the forecast period. An excerpt from the report description outlines key trends driving the market:

Increasing preferences toward cloud-based platform[s] is observed as a major trend in the market. Cloud-based platforms involve [the] Software-as-a-Service (SaaS) model, which enables users to access these solutions virtually, through a secured platform over the internet. Cloud deployment offers greater flexibility and scalability, and reduces associated IT infrastructure costs.

With rising number of fraudulent incidents, detection and prevention of fraud is a huge challenge for organizations across all verticals. Presently, a large number of companies are using big data and traditional machine learning methods to detect and prevent fraud. However, as the dataset tends to be imbalanced and highly skewed in terms of positive and negative classes, to get accurate results, typically [involves] high domain knowledge and a large number of processes are required for data preprocessing, data exploration, missing data handling, training, feature engineering, model selection, evaluation, and so forth. Auto Machine Learning solutions optimize all these processes without human intervention, which is further driving the growth of the market.

Sam Mowers,

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