Collaborating Authors


How BFSI is Harnessing the Power of AI & Intelligent Automation


AI fraud detection applications collect public customer data from across the entire internet to identify who is a real customer, and who may not be. Combined with a financial institution's internal customer data, a high level of accuracy is achieved in spotting fraudulent activities in real-time. Additionally, false flags are reduced. For example, in the past, if a credit card holder swiped their card from the other side of the country, the card ran the risk of being locked by the financial institution. With today's AI tools and predictive analytics, a bank may have access to a customer's geolocation, transaction history such as airline tickets, and social media posts regarding future vacations, preventing false flags, and ultimately, damage to the bank/client relationship.

The world in your pocket: How smartphones will get smarter in 2022


In 2022, there will be even more niche phones that offer a rich experience and a narrow appeal like gaming phones and foldables. New phones for 2022 are already debuting left and right, and it's barely been two weeks. During CES 2022, Samsung announced the Galaxy S21 FE, the follow-up to its popular 2020 phone the Galaxy S20 FE. OnePlus teased us all with a slow trickle of details about the new features and CPU in the OnePlus 10 Pro. Sony finally brought the photography-focused Xperia 5 III to the US.

Ohio State receives $3 million grant to boost broadband jobs – The Columbus Dispatch


… the state and telecommunications industry has the potential to also create job opportunities in artificial intelligence, machine learning and …

How AI Is Paving the Way to Greater Humanity in Marketing


Turns out, machines can bring more humanity to the conversations and interactions our brands are having every day. Leaders who are integrating AI's objective curiosity and performance speed with human creativity and problem-solving are finding new sources of insights and value that benefit their teams, their businesses, and most of all, their customers. An inescapable reality is that today's customers expect--not just want, but now demand--new heights of personalization. This is as true in b-to-b marketing as it is in b-to-c. And our news feeds remind us every day that the pressure is on marketers to deliver.

SoftBank Makes $146M Bet on AI Firm Qraft


SoftBank is investing $146 million in the South Korean artificial intelligence (AI) company Qraft Technologies Inc. to help it expand into the U.S. As The Wall Street Journal (WSJ) reported Monday (Jan. The companies declined to disclose Qraft's valuation, per the WSJ. SoftBank, based in Tokyo, is one of the largest tech investors in the world, managing a portfolio in excess of $100 billion. Qraft has 50 employees, most of whom work on the company's AI project and who own about a third of the business, with outside investors controlling the rest. "SoftBank [now] makes up a large portion of that," Robert Nestor, the U.S. CEO of Qraft., told the WSJ.

WSJ News Exclusive


Founded in 2016 by its chief executive, Marcus Hyung-Sik Kim, the Seoul-based firm plans to use the investment to further its expansion into the U.S. and other key markets, said Robert Nestor, Qraft's U.S. CEO. The companies declined to disclose Qraft's valuation. Tokyo's SoftBank is one of the world's largest investors in technology companies, with its Vision Fund and a successor managing a portfolio of more than $100 billion. Asset managers, once skeptical of the value of AI and mindful of their staffs' concerns that the programs would replace human stock- and bond-pickers, are now looking to add data-analysis tools that can help them combat chronic underperformance and justify the fees they charge investors. The industry's awakening has triggered an arms race to hire the programmers who can develop those tools and spot the market signals hidden in the data.

SoftBank Invests in Artificial-Intelligence Startup WSJD - Technology

Qraft Technologies plans to use the $146 million investment to fuel U.S. and China expansion.

Artificial intelligence measures service quality


TT Ventures, the corporate venture capital company of Türk Telekom, offers various supports to startups, including in areas like sales, marketing, infrastructure and technology through its parent company, in addition to financial investments with its unique investment model that it has developed. QuantWifi, which operates in the field of telecommunications, is one of the four startups invested in by TT Ventures. The company develops cloud and machine learning-based solutions that measure the quality of in-home wireless connections and internet connections for internet service provider telecom companies to identify and recommend ways to fix problems. That is, artificial intelligence offers a competitive advantage by performing quality control of services. Within the scope of the cooperation, QuantWifi continues to measure and improve the wireless (Wi-Fi) connection satisfaction of customers who are provided internet service from Türk Telekom.

DeepBrain AI grasps attention at CES 2022 with its AI Human imbedded AI Kiosks.


DeepBrain AI is showcasing its AI Human imbedded "AI Kiosks" from January 5th to January 7th at CES 2022 held in Las Vegas Convention Center, along with its CES 2022 Innovation Awards honoree SaaS solution "AI Studios". "AI Kiosks" leverages the power of Artificial Intelligence with its human-based AI avatars that inform, solve, and guide users through thousands of possible scenarios and real time interactions. As mentioned above, AI Humans imbedded in the Kiosks are based on real humans with a variety of races and languages. Visitors who tried the "AI Kiosks" on-site were all amazed to have an actual real-time interactive conversation with an AI looking like a real person. Moreover, as part of the MOU recently signed with Arirang TV, a special AI Human will be demonstrated on the 6th at DeepBrain AI's booth.

Building Interpretable Models on Imbalanced Data


I've always believed that to truly learn data science you need to practice data science and I wanted to do this project to practice working with imbalanced classes in classification problems. This was also a perfect opportunity to start working with mlflow to help track my machine learning experiments: it allows me to track the different models I have used, the parameters I've trained with, and the metrics I've recorded. This project was aimed at predicting customer churn using the telecommunications data found on Kaggle [1] (which is a publicly available synthetic dataset). That is, we want to be able to predict if a given customer is going the leave the telecom provider based on the information we have on that customer. Now, why is this useful? Well, if we can predict which customers we think are going to leave before they leave then we can try to do something about it! For example, we could target them with specific offers, and maybe we could even use the model to provide us insight into what to offer them because we will know, or at least have an idea, as to why they are leaving.