Rensselaer: Rensselaer Researchers to Address Big Data Challenges. “Simply put, [Dr. Yangyang] Xu’s team will develop groundbreaking algorithms that allow multiple computers to work efficiently together as one. They will also focus on maintaining the security of distributed personal information, and on methods to improve the speed and accuracy of deep learning.”
The Drive: We Found the Full List of All 677,081 Cars Killed in Cash for Clunkers. “The federal scrappage scheme that destroyed almost 700,000 supposedly gas-guzzling vehicles had basic criteria: no cars could be 25 years old or older, the cars must manage 18 mpg combined or worse, driveable, and its rebate and scrap value must be applied to a car that would be registered and insured for one continuous year after purchase. What was taken off the roads has hopefully been recycled several times over, but the truth isn’t lost, as we’ve dug up a little-known, long-lost complete report on every car CFC destroyed.”
University of Oxford: Seeing the light: researchers develop new AI system using light to learn associatively . “Researchers at Oxford University’s Department of Materials, working in collaboration with colleagues from Exeter and Munster have developed an on-chip optical processor capable of detecting similarities in datasets up to 1,000 times faster than conventional machine learning algorithms running on electronic processors.”
Europe PMC: Keeping it under lock and keywords: exploring new ways to open up the web archives with notebooks.. “…the scale of the [UK Government Web Archive] exposes the limits of the current search interface, and there is no facility to understand the archive in aggregate. This article seeks to go beyond the simple keyword search by exploring the data sources available, from APIs to web crawling, for computational analysis of the UKGWA. The article is accompanied by two Python Notebooks which present examples of analysis using each data source. Notebooks lower the technical barriers for the reader to explore and interpret the UKGWA as data, while surfacing the challenges around making web material computationally accessible.”
MIT Technology Review: Why business is booming for military AI startups . “NATO announced on June 30 that it is creating a $1 billion innovation fund that will invest in early-stage startups and venture capital funds developing ‘priority’ technologies such as artificial intelligence, big-data processing, and automation. Since the war started, the UK has launched a new AI strategy specifically for defense, and the Germans have earmarked just under half a billion for research and artificial intelligence within a $100 billion cash injection to the military.”
Scientific Data: A Global Building Occupant Behavior Database . “This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior.”
SlashGear: Study Shows Robots Using Internet-Based AI Exhibit Racist And Sexist Tendencies. “A new study claims robots exhibit racist and sexist stereotyping when the artificial intelligence (AI) that powers them is modeled on data from the internet. The study, which researchers say is the first to prove the concept, was led by Johns Hopkins University, the Georgia Institute of Technology, and the University of Washington, and published by the Association for Computing Machinery (ACM).”
The Guardian: Russian palaces, villas and yachts linked to Putin by email leak – in pictures, maps and video. “An investigation by the the Organised Crime and Corruption Reporting Project and the news website Meduza has identified a group of 86 apparently unconnected companies or not for profit organisations that appear to hold over $4.5bn (£3.7bn) of assets where a common private email address, LLCInvest.ru, appears to be in use.”
EurekAlert: Massive dataset reveals which governments have best responded to COVID-19 pandemic. “[Olga] Shvetsova’s lab compiled a massive database comparing pandemic-related governmental policies in 82 countries on both the national and subnational levels, as part of the COVID-19 Protective Policy Index (PPI) project. The data covers the entire year of 2020, and is publically available for researchers’ use.”
Smashing Magazine: Web Design Done Well: Delightful Data Visualization Examples. “All the data in the world won’t do anyone any good if we can’t make sense of it. Or better yet, make it sing. Here are some stunning examples of data visualization in the wild, and some pointers on how to start making your own.” Smashing Magazine with their usual good work.
Scientific Data: Lexibank, a public repository of standardized wordlists with computed phonological and lexical features . “Inspired by the GenBank database, where scholars can deposit nucleotide sequences publicly, we have created Lexibank, a collection of cross-linguistic datasets in standardized formats, which offers access to word forms, sound inventories, and lexical features for more than 2000 language varieties derived from 100 individual high-quality datasets. The Lexibank wordlist collection is a first attempt to integrate the wealth of language data assembled during the past centuries.”
University of Toronto: AI-powered archaeology draws out hidden evidence of fire use by early humans. “The discovery, described in a study published this week in Proceedings of the National Academy of Sciences, suggests only the sixth location worldwide of evidence of fire more than half a million years old. The researchers employed advanced artificial intelligence (AI) techniques to confirm their hypothesis. The team suggests the method could lead to a more scientific, data-driven type of archaeology, providing a better understanding of the origins of the human story, our most basic traditions and our experimental and innovative nature.”
Star Tribune: John Deere tapping into Apple-like tech model to drive revenue. “In a world with a dwindling number of grain producers and a growing population, Deere and its rivals are developing self-driving equipment loaded with the latest software that is harvesting a new kind of bumper crop: data. All that translates into recurring revenue, something companies like Apple have long enjoyed and industrial manufacturers like Deere hungrily eye.”
Johns Hopkins University: Black Beyond Data. “This is one of [Jessica Marie] Johnson’s passions as a historian. To tell the stories of Black people—particularly Black women—in the Atlantic African diaspora during the centuries of slavery. She highlights the relationships, warmth, and intimacy they created despite the harshest of circumstances, as well as the ways in which they wielded intelligence, creativity, and interpersonal skills to strive for freedom. But Johnson is equally committed to opening access to the myriad amounts of data that contain information about Black life and Black people, both historical and contemporary.”
Arizona State University: Closing the gap for real-time data-intensive intelligence. “The online world fills databases with immense amounts of data. Your local grocery stores, your financial institutions, your streaming services and even your medical providers all maintain vast arrays of information across multiple databases. Managing all this data is a significant challenge. And the process of applying artificial intelligence to make inferences or apply logical rules or interpret information on such data can be urgent, especially when delays, known as latencies, are also a major issue.”
