Biometric, Bad, Virtual, Aggregator, Predictive, Geospatial

This week, we begin with an article about Taliban’s capture of biometric devices in Afghan that contains individuals’ sensitive personal information including their career trajectory. Next, we have a piece on how to escape the obscure data problems while building AI/ML solutions. The following article examines China’s goals to thrive in world’s AI industry and the establishment of Hua, an AI powered student is the first milestone achieved. Following that, we have an article discussing the launch of Account Aggregator, one place to consolidate all financial data of users, by major banks in India. Next is a piece about how predictive AI technologies will help businesses in terms of cookie-less ads, data management & customer connection. Finally, we have an article on rise of geospatial economy which will harness the flow of data and drive better analytics.

This Is The Real Story Of The Afghan Biometric Databases Abandoned To The Taliban

As the Taliban swept through Afghanistan in mid-August, declaring the end of two decades of war, reports quickly circulated that they had also captured US military biometric devices used to collect data such as iris scans, fingerprints, and facial images. Some feared that the machines, known as HIIDE, could be used to help identify Afghans who had supported coalition forces. According to experts speaking to MIT Technology Review, however, these devices actually provide only limited access to biometric data, which is held remotely on secure servers.

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“Bad Data Can Kill Good AI”

A good painter will tell you that surface preparation means everything.  A great paint job on a poorly prepared surface will look shabby and will not last.  Likewise, a good data scientist will tell you that data preparation is critical to any AI system’s success.  Even the best, most sophisticated analytics technique applied to low quality, poorly integrated, sloppily engineered, or largely irrelevant data will be, at best, unreliable. Much ink has been spilled describing AI and machine learning and it’s uses in banking.  But less has been written on the essential foundation of AI: robust data.

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A Small Step For China’s First Virtual Student, A Leap For CCP’s AI Ambitions

On 3 June 2021, Hua Zhibing, China’s first virtual student, announced that she has enrolled at Tsinghua University and will be studying at the Department of Computer Science and Technology. This virtual student is an Artificial Intelligence (AI) powered student avatar developed jointly by researchers from China’s industry and academia. The researchers from China’s Tsinghua University, non-profit research organisation Beijing Academy of Artificial Intelligence (BAAI), and private companies Zhipu Huazhang Technology (Zhipu AI) and Xiaoice worked together to develop the systems required to achieve this feat.

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India Launches Account Aggregator To Extend Financial Services To Millions

India’s top banks five years ago built the interoperable UPI rails and enabled over 150 million people in the South Asian market to pay digitally. Scores of firms — including local firms Paytm, PhonePe, CRED and international giants Google and Facebook — in India today support the UPI infrastructure, which is now reporting 3 billion transactions each month. Banks are now ready for their second act. On Thursday, eight Indian banks announced that they are rolling out — or about to roll out — a system called Account Aggregator to enable consumers to consolidate all their financial data in one place.

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How Can Predictive AI Transform Customer Connection?

Predictive analytics is bringing smarter insights and better efficiency into many areas of our lives, even if we aren’t always aware of it. Take healthcare, for example, a sector that has been firmly in the spotlight in recent months. Scientists have recently combined self-reported symptoms data and artificially intelligent (AI) modeling to predict which early signs of COVID-19 can be used for faster detection. Interest in using data stores to identify useful patterns is also sparking growing commercial interest.

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The Geospatial Economy: A Flood Of Geospatial Data Is Here To Lift All Boats

The world is awash in a growing tsunami of data pouring from satellites, drones and Internet of Things (IoT) devices. The ability to harness all that data, contextualize it in space and time and put it in the hands of everyday planners and operations teams will affect every industry and open the door to a massive new geospatial economy. Geospatial data — information that links people, objects or behaviors with the “when and where” they occupy — is critical to managing resources and solving problems that range from finding lost hikers to directing disaster response, accurately assessing underwriting risk or addressing food scarcity.

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