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HSBC's Akash Gupta has won over 45 machine learning hackathons to date. The MachineHack Grandmaster has come second thrice in a row and is currently ranked sixth on the platform. "I've always been fascinated by numbers and patterns. I got very curious about algorithms – how they are made, how they work, and what we can do with them– after I took Andrew Ng's machine learning course," said Akash Gupta. The data scientist spoke about his MachineHack journey in an exclusive interview with Analytics India Magazine.

The ACM SIGAI Industry Award for Excellence in Artificial Intelligence (AI) will be given annually to individuals or teams who have transferred original academic research into AI applications in recent years in ways that demonstrate the power of AI techniques via a combination of the following features: originality of the research novelty and technical excellence of the approach; importance of AI techniques to the approach; and actual or predicted societal impact of the application. Awardees receive a plaque accompanied by a prize of $5,000, and will be recognized at the International Joint Conference on Artificial Intelligence through an agreement with the IJCAI Board of Trustees. After decades of progress in the theory, research and development of AI, AI applications are increasingly moving into the commercial sector. A great deal of pioneering application-level work is being done by those transferring research results into industry--from startups to large corporations--and this is influencing commerce and the broad public in a wide variety of ways. This award complements the numerous academic, best-paper and related awards, in that it focuses on innovators of fielded AI applications.

We are pleased to announce that this summer AI4SD will be running a hybrid residential summer school from the 20th-24th June 2022 at the University of Southampton. This summer school will introduce you to basic python programming, different areas of machine learning including mathematical foundations for ML, classification and clustering, kernel methods, introduction to deep learning and case studies in chemistry including reinforcement learning in chemistry. There will also be talks to upskill scientists in other relevant areas including Group Management, Presentation Skills, Research Data Management, Referencing, LaTeX, GitHub and Ethics. The summer school will include a hackathon where students can compete in teams to solve the same problem in the best way. Group presentations will take place on the friday and prizes will be given to the winning team.

Lauren Fitzpatrick Shanks is the founder and CEO of KeepWOL and an award-winning engineer and tech leader, who spent fourteen years working at five Fortune 500 companies, holding various leadership roles in design, system testing, product creation, staffing, software program management, and operations. Lauren is the first Black woman to graduate from The University of Kansas' Aerospace Engineering Department and the first Black woman to win the American Institute of Aeronautics and Astronautics (AIAA) international design competition. KeepWOL is a game-centric talent development platform that combines live multiplayer games, AI technology, and end-to-end learning integration to deeply understand how employees think and what influences their decisions. Could you discuss how you chose engineering as a career path, and even pursued a bachelor's degree in Aerospace Engineering, all while realizing that it was not the best match for you? I wouldn't say that engineering wasn't a perfect match for me. I have an uncanny ability to visualize processes and objects before they are even prototyped or in motion.

This content can also be viewed on the site it originates from. A video posted toward the end of February on the Facebook page of Valerii Zaluzhnyi, the commander-in-chief of Ukraine's armed forces, showed grainy aerial footage of a Russian military convoy approaching the city of Kherson. Russia had invaded Ukraine several days earlier, and Kherson, a shipbuilding hub at the mouth of the Dnieper River, was an important strategic site. At the center of the screen, a targeting system locked onto a vehicle in the middle of the convoy; seconds later, the vehicle exploded, and a tower of burning fuel rose into the sky. The Bayraktar TB2 is a flat, gray unmanned aerial vehicle (U.A.V.), with angled wings and a rear propeller.

"You won't see many people with my background talking about ethics," said Beena Ammanath, executive director of the Global Deloitte AI Institute and head of Trustworthy AI and Ethical Tech at the global consulting company. A computer scientist who worked as a database and SQL developer and held data science- and AI-related technology roles at Bank of America, GE and Hewlett Packard before joining Deloitte in 2019, Ammanath wasn't always gung-ho to talk AI ethics. Then she decided to write a book about it. "There has arguably never been a more exciting time in AI," she wrote in her book "Trustworthy AI." "Alongside the arrival of so much promise and potential, however, the attention placed on AI ethics has been relatively slight." Protocol spoke with Ammanath about why ethical AI practices should be part of every employee's training, the limitations of providing internal guidance inside a sprawling consultancy and why she finally gave in and joined the AI ethics conversation.

Past research on pedestrian trajectory forecasting mainly focused on deterministic predictions which provide only point estimates of future states. These future estimates can help an autonomous vehicle plan its trajectory and avoid collision. However, under dynamic traffic scenarios, planning based on deterministic predictions is not trustworthy. Rather, estimating the uncertainty associated with the predicted states with a certain level of confidence can lead to robust path planning. Hence, the authors propose to quantify this uncertainty during forecasting using stochastic approximation which deterministic approaches fail to capture. The current method is simple and applies Bayesian approximation during inference to standard neural network architectures for estimating uncertainty. The authors compared the predictions between the probabilistic neural network (NN) models with the standard deterministic models. The results indicate that the mean predicted path of probabilistic models was closer to the ground truth when compared with the deterministic prediction. Further, the effect of stochastic dropout of weights and long-term prediction on future state uncertainty has been studied. It was found that the probabilistic models produced better performance metrics like average displacement error (ADE) and final displacement error (FDE). Finally, the study has been extended to multiple datasets providing a comprehensive comparison for each model.

Over the course of her nine-year tenure at LinkedIn, Ya Xu has held technology roles with increasing responsibility. Today, she heads the data function for the online professional networking platform. Ya Xu has been a driving force in transforming LinkedIn into a data-first company since she first joined the organization in 2013. As head of data, she leads a global team of about 1,000 data scientists and AI engineers whose work is at the core of delivering economic opportunities to LinkedIn's members and customers. Xu's emphasis on responsible AI and data science ensures that LinkedIn's AI systems put people first and enables the company to empower its members, better serve its customers, and benefit society. In addition to her work at LinkedIn, Xu has coauthored the book Trustworthy Online Controlled Experiments (Cambridge University Press, 2020), has been named to Fortune's 40 under 40 in tech, and was nominated for VentureBeat's Women in AI Awards. She has delivered countless speeches, including a commencement speech to Stanford's class of 2019 in mathematics, statistics, and mathematical and computational science. Previously, Xu worked at Microsoft and earned a Ph.D. in statistics from Stanford University. Ya joins hosts Sam Ransbotham and Shervin Khodabandeh in this episode of the Me, Myself, and AI podcast, where she discusses AI's essential role in helping LinkedIn create the best "matches" -- content creators with content consumers, job seekers with employers, and buyers with sellers -- within its three key marketplaces. Ya also describes how the company has fostered a data-first culture from the top down, and how its vast amount of economic activity data is helping governments and policy makers worldwide.

What do you think of when you hear "artificial intelligence?" This conjures up images of Hollywood movies like Ex Machina or The Terminator for many people. While these depictions may be a little far-fetched, artificial intelligence is already having a major impact on businesses worldwide. It is impacting every aspect of the business, from marketing to sales to customer service. And many companies are already using AI to automate tasks and make their operations more efficient. As per a report, the global artificial intelligence market size was valued at $93.5 billion in 2021 and is estimated to grow by $1811 billion by 2030.