After years of data breaches, leaks, and hacks leaving the world desperate for tools to stem the illicit flow of sensitive personal data, a key advance has appeared on the horizon. On Tuesday, MongoDB is announcing “Queryable Encryption,” a feature that will allow database users to search their data while it
Identifying a malfunction in the nation’s power grid can be like trying to find a needle in an enormous haystack. Hundreds of thousands of interrelated sensors spread across the U.S. capture data on electric current, voltage, and other critical information in real-time, often taking multiple recordings per second. Researchers at
The e-commerce platform Shopify has successfully leveraged machine learning through a methodological, five-step strategy. Below we’ll examine each step and detail how it’s helped the company thrive. Shopify’s growth is unparalleled in the e-commerce industry. Collectively, the platform’s merchants make up the 7th largest company in the world in terms of
Data has become both the most abundant and the most valuable resource in today’s business world. According to a recent IDC study, the world generated or replicated an estimated 64.2 zettabytes of data in 2020, with a forecasted compound annual growth rate of 23% through 2025. Data comes in all
Rice University computer scientists have discovered an inexpensive way for tech companies to implement a rigorous form of personal data privacy when using or sharing large databases for machine learning. “There are many cases where machine learning could benefit society if data privacy could be ensured,” said Anshumali Shrivastava, an
Massachusetts Institute of Technology researchers examined the issue of shortcuts in a popular machine learning method and proposed a solution forcing the model to use more data in its decision-making to avoid pitfalls. By removing simpler characteristics, researchers can redirect the model’s focus to more complex features of the data that
When people hear “artificial intelligence,” many envision “big data.” There’s a reason for that: some of the most prominent AI breakthroughs in the past decade have relied on enormous data sets. Image classification made enormous strides in the 2010s thanks to the development of ImageNet, a data set containing millions
From Semiconductor Supply Chains to Dirty Bombs: Summary of the September 2021 OODA Network Member Meeting
The September monthly meeting covered a range of issues, from planning for an upcoming OODA Network wargame exercise to a recent cyber vulnerability and mitigation, future research on CISA and critical infrastructure, and recent events in France surrounding the discovery of IEDs with uranium traces.
Each year, there are one or two books that deeply resonate with me and become sticky in that I’m thinking about the book often, bringing it up in conversations, and sending out unsolicited recommendations for executives and researchers in my network to check it out. Jer Thorp’s “Living in Data: A Citizen’s Guide to a Better Information Future” was that book for me in 2021 so I was delighted to host Jer for a conversation on the OODAcast.
er Thorp is an artist, writer and teacher living in New York City. He is best known for designing the algorithm to place the nearly 3,000 names on the 9/11 Memorial in Manhattan. Jer was the New York Times’ first Data Artist in Residence, is a National Geographic Explorer, and in 2017 and 2018 served as the Innovator in Residence at the Library of Congress. Jer is one of the world’s foremost data artists, and is a leading voice for the ethical use of big data.
Analysis of enterprise data is a dynamic endeavor. As new tools and applications are found to handle business use cases, new data arises that in many cases produces new opportunities, but these may require new approaches to analysis and selection of new tools. This report seeks to provide some planning assumptions in this dynamic world in a way that can serve your decision-making today.