The last few years saw customers shift their preference from buying clothes at retail outlets to conveniently buying online on their gadgets. This change in customer behavior was further accelerated by COVID-19 as customers had to depend on buying online for most of their shopping needs. Despite COVID-19 beginning to ease off slowly, customers believe that shopping online is a lot more convenient than having to go from store to store to get what they’re looking for. E-commerce brands are thus doing their best to keep their hard-earned customers engaged on their platform by delivering personalized user experiences. We caught up with Mohit Panjwani, Associate Director- Revenue Growth at Myntra to understand how e-commerce fashion brands like Myntra are leveraging the power of customer data and marketing analytics to craft memorable and personalized shopping experiences. Myntra is India’s leading e-commerce company committed to making fashion and lifestyle products accessible to everyone. From its birth as a customization company in 2007 to being technology and fashion pioneers today, Myntra has grown to become the ultimate destination for fashion and lifestyle, being host to a wide array of merchandise including clothing, footwear, accessories, jewellery, personal care products, etc. Mohit shares his thoughts on: * Major customer engagement and retention challenges faced by e-commerce brands * Importance of adopting an omnichannel approach to effectively engage with customers across all touchpoints of the user journey * Need to have a consistent messaging across channels beyond website and app- thoughts on product recommendations, personalized emails, and app push notifications * How predicting customer churn through ML is critical to increasing retention * Innovative campaigns and ideas used to increase customer engagement and repeat purchase behavior * 3 biggest e-commerce trends that can pick up steam in 2021 Tune in to gain insights on how the best in the business caters to customer needs and requirements by delivering customer experiences at scale.

Intersectional bias is a bias caused by an overlap of multiple social factors like gender, sexuality, race, disability, religion, etc. A recent study has shown that word embedding models can be laden with biases against intersectional groups like African American females, etc. The first step towards tackling such intersectional biases is to identify them. However, discovering biases against different intersectional groups remains a challenging task. In this work, we present WordBias, an interactive visual tool designed to explore biases against intersectional groups encoded in static word embeddings. Given a pretrained static word embedding, WordBias computes the association of each word along different groups based on race, age, etc. and then visualizes them using a novel interactive interface. Using a case study, we demonstrate how WordBias can help uncover biases against intersectional groups like Black Muslim Males, Poor Females, etc. encoded in word embedding. In addition, we also evaluate our tool using qualitative feedback from expert interviews. The source code for this tool can be publicly accessed for reproducibility at github.com/bhavyaghai/WordBias.

Machine learning provides more and more powerful tools for data analytics. On the other hand, security and privacy attacks increasingly involve data. Therefore, machine learning and security & privacy naturally intersect with each other as they both involve data, and there are many interesting questions at the intersections: i) How machine learning impacts security and privacy analytics design? In this talk, I will first talk about machine learning for security and privacy in social networks, particularly, graph-based collective classification to detect fake accounts in social networks. A long-standing challenge in collective classification is that existing methods cannot learn accurate edge weights, thus resulting in limited detection performance in practice.

Comarch is a provider of complete IT solutions for telecoms, working with some of the worlds leading SPs: Vodafone, T-Mobile, Telefónica, E-Plus, KPN and MTS. For Total Telecom, Comarch are also a key partner at the annual Total Telecom Congress. With the 2021 now firmly underway, Total Telecom caught up with Rajmund Zielinski, IAA Product Manager at Comarch to get his thoughts one of the industries hottest topics: AI. In the wake of the coronavirus, digitalization has accelerated around the world and telcos are required to handle ever more data. How can operators use AI to gain value from this data?

When he was a boy, Mark Solms obsessed over big existential questions. What happens when I die? What makes me who I am? He went on to study neuroscience but soon discovered that neuropsychology had no patience for such open-ended questions about the psyche. So Solms did something unheard of for a budding scientist. He reclaimed Freud as a founding father of neuroscience and launched a new field, neuropsychoanalysis. Solms had one other obstacle in his path. Born in Namibia, where his father worked for a South African diamond mining company, he grew up under apartheid in South Africa. Solms later worked at a hospital in Soweto, where a military occupation tried to clamp down on protesters. "Once you reach the end of your studies, you're required to join the very same army whose victims I was looking after," he told me.

Austin Russell is the 25-year-old founder and CEO of Luminar, a startup in Silicon Valley that makes LIDAR sensors for self-driving cars. LIDAR technology had been used for short-distance mapping, but Luminar claims to have a functioning LIDAR that works at 250 meters, which is a breakthrough. Luminar recently went public, making Austin today's youngest self-made billionaire. And when it comes to self-driving cars, youth is definitely an advantage -- Austin told me we're still years if not decades away from fully self-driving cars, and there's a lot of work to be done to make them safe, effective, and ubiquitous. That work is racing ahead -- Luminar has deals with Volvo, Audi, Toyota, and others -- but building a complete self-driving car is still a long-term project. This transcript has been lightly edited for clarity. I'm very excited to talk to you. You are, as far as the last thing I read, the youngest self-made billionaire in America, your company just went public in a SPAC [special purpose acquisitions company]. And come Pi Day, 26. You were born on Pi Day? So, Luminar, it's a company that makes LIDAR sensors. You have a number of deals to supply LIDAR sensors to major automakers. I want to talk about all of that. One thing that I always get frustrated by in origin stories is no one ever really talks about act two. In 2012 you were at Stanford, you had this idea to do LIDAR sensors. I want to talk about act two for a little bit. Just that middle part of going from "I've got a great idea," to "This company is actually up and running and functional." So give me a sense of, at the beginning you were a student at Stanford, you got a Thiel Fellowship from Peter Thiel. What was the next step? Did you sit down and build a LIDAR sensor?

From Hugh Heffner to Donald Trump, many male celebrities are known for their tendency to date younger women. Now, a new study has revealed that as many as one in five British men choose to date women at least five years younger. Researchers trawled through 120,000 dating profiles to understand whether men really do live up to the stereotype of preferring younger women. Their findings indicate that the stereotype is very much true, with men citing good looks and health as the main reasons they prefer ladies their junior. Many male celebrities are known for their tendency to date younger women.

Your visual cortex does two incredible things, thousands of times a second. First, it takes all the information streaming in through your retinas and passes it through a series of steps – looking first for patches of dark and light, then for features such as lines and edges, then for simple recognisable shapes like this letter'A', working up to household objects like a toaster or kettle, or individual faces, like your grandmother, or the person who you used to see every day at the bus stop on the way to work. The second incredible thing it does is to completely forget that it's done any of that at all. The inner workings of our minds are not accessible to us – and that is one of the things that will always separate us from artificially intelligent machines like the ones depicted in Klara and the Sun, the new novel from British author Kazuo Ishiguro. The book is set in a near-future where robotic humanoids called'Artificial Friends' or'AFs' are the purchase of choice for wealthy teenagers, who – for unspecified reasons – are taught remotely, and rarely get the opportunity to interact with their peers face to face.

The pandemic increased unemployment for several months, but finally, companies are seeing re-employment numbers going up fast again. While this is a positive sign, organizations need to have processes to handle the increased number of applicants the best way possible, especially for industries that had to let go of many employees, to recruit the best candidates. Employees are the company's most important asset, so hiring better is critical for your success. I interviewed Yves Lermusi, Chief Futurist at OutMatch, the leading AI-driven hiring platform, to discuss how AI will impact both recruiters and candidates' hiring experience. OutMatch helps leading companies boost talent acquisition performance and to deliver an engaging hiring experience for all.

The trend toward greater focus on privacy issues has been going on for some time and is starting to come to a head. More restrictions on the sharing and merging of data on individuals has been leading to advertisers to look for effective ways to target and reach consumers, including using the use of behavioral targeting supplemented by the use of artificial intelligence (AI). At a time when privacy regulations are sometimes fragmented and confusing but changing, it is critically important for marketers to monitor changes in the regulatory environment. Against this backdrop, I interviewed Sheri Bachstein, IBM's Global Head of Watson Advertising to get her insights and predictions on the future of privacy regulation and how it will affect advertisers, particularly as regards the use of AI and came away with three major takeaways: The European Union's General Data Protection Regulation and the California Consumer Privacy Act are already leading to the devaluation of traditional third-party cookies and the way many advertisers do business. Yet, the lack of uniform regulation creates a significant gray area for companies who want to scale and use AI in targeting, creating problems for technology companies and marketers. Bachstein believes that federal legislation as opposed to a patchwork of state laws is needed in order to allow for standards that allow marketers to operate effectively while protecting consumer rights.