This week, we begin with an article that explores the development of a deep learning model that predicts very high-resolution crash risk maps. Next, we have a piece on advantages of integrating data & analytics in fashion and luxury companies according to McKinsey Global Fashion Index. Then, we have an analysis of the importance of data quality for businesses & the high costs to organizations due to bad data or poor quality of data. Following that, we have an article on increasing investments in artificial intelligence solutions by banks to close the tech gap. Next is a story on the public show of sensitive data worth 60GB due to data breach faced by Acer, affecting millions of customers. Finally, we have an essay that gives a comprehensive overview of the Machine Learning, AI and Data (MAD) ecosystem, how start-ups are flourishing in this space, its significance and complexity.
Deep Learning Helps Predict Traffic Crashes Before They Happen
Today’s world is one big maze, connected by layers of concrete and asphalt that afford us the luxury of navigation by vehicle. For many of our road-related advancements — GPS lets us fire fewer neurons thanks to map apps, cameras alert us to potentially costly scrapes and scratches, and electric autonomous cars have lower fuel costs — our safety measures haven’t quite caught up.
Jumpstarting Value Creation With Data And Analytics In Fashion And Luxury
The COVID-19 crisis is first and foremost a humanitarian crisis, but its economic impacts are far-reaching. Fashion is no exception: apparel companies lost 90 percent of their profits in 2020, according to the McKinsey Global Fashion Index. Consumer confidence plummeted during the pandemic, and it has yet to recover.
Flying Blind: How Bad Data Undermines Business
As businesses increasingly adopt data-driven systems, processes and strategies and with leaders seeking to “Moneyball” everything from hiring to software development the importance of maintaining data quality has never been higher. However, with data volumes steadily rising, maintaining the quality of the underlying data that drives decisions is a growing challenge.
AI Is Coming — And You Can Take That To The Bank
More and more in banking, it’s technology that matters. The new challenger banks are actually known as “fintechs”, financial technology companies, rather than banks – and this is understandable. It’s widely believed in some circles that companies such as Starling, Monzo, Revolut et al have managed to achieve large numbers of signups principally because they were first to automate the process of opening a bank account.
Acer Data Breach In India: Delighted Hackers Show-Off Users’ Accounts In Public
Days after a hack that targeted Taiwanese computer manufacturer Acer India resulted in the loss of 60GB worth of sensitive data, hacker group Desorden has reportedly claimed responsibility for the October 5 hack that affected millions of users including Indian customers whose data was stolen from the company’s servers.
The 2021 Machine Learning, AI, And Data Landscape
It’s been a hot, hot year in the world of data, machine learning and AI. Just when you thought it couldn’t grow any more explosively, the data/AI landscape just did: the rapid pace of company creation, exciting new product and project launches, a deluge of VC financing, unicorn creation, IPOs, etc. It has also been a year of multiple threads and stories intertwining.