Google

195 posts
Trending hobbies during the pandemic

This past year has seen a rising interest in long-lost hobbies due to shelter-in-place, social distancing, and lockdown orders. Google Trends and Polygraph charted the hobbies that saw the biggest spikes each day of the year. I’m surprised that sourdough or bread-making is on there, but maybe they didn’t fall under the hobby definition they used. Tags: coronavirus, Google, hobbies, Polygraph, trends

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Exploring your Google search history

Search history can say a lot of about a person, like where they’re going, where they want to be, what they want to learn about, or what they’re trying to make — at some point in their life. Search Record, by Jon Packles, is a way to parse through your history. Download your archive, import it into the locally-run tool, and explore. I’m more of DuckDuckGo person, so I can...

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Blob Opera is a machine learning model you can make music with

David Li, in collaboration with Google Arts and Culture, made a fun experiment to play with: We developed a machine learning model trained on the voices of four opera singers in order to create an engaging experiment for everyone, regardless of musical skills. Tenor, Christian Joel, bass Frederick Tong, mezzo‑soprano Joanna Gamble and soprano Olivia Doutney recorded 16 hours of singing. In the experiment you don’t hear their voices, but...

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Google search trends dataset for Covid-19 symptoms

Google released a search trends dataset earlier this month. Using this dataset, Adam Pearce made an explorer to compare search volume over time: The COVID-19 Search Trends symptoms dataset shows aggregated, anonymized trends in Google searches for more than 400 health symptoms, signs, and conditions, such as cough, fever and difficulty breathing. The dataset provides a time series for each region showing the relative volume of searches for each symptom....

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Randomization to preserve anonymity

Adam Pearce and Ellen Jiang for Google’s PAIR, explain how granular data can lead to easy identification of individuals and how randomization can help: Aggregate statistics about private information are valuable, but can be risky to collect. We want researchers to be able to study things like the connection between demographics and health outcomes without revealing our entire medical history to our neighbors. The coin flipping technique in this article,...

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Tic-Tac-Toe the Hard Way is a podcast about the human decisions in building a machine learning system

From Google’s People + AI Research team, David Weinberger and Yannick Assogba build a machine learning system that plays Tic-Tac-Toe. They discuss the choices, not just the technical ones, along the way in the ten-part podcast series: A writer and a software engineer engage in an extended conversation as they take a hands-on approach to exploring how machine learning systems get made and the human choices that shape them. Along...

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This Age is the New Age

30 is the new 20. Wait. 40 is the new 20. No, scratch that. 50 is the new 20. Or is 50 the new 30? Here’s what the Google says, so you know it must be true. Tags: age, Google, search

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Search trends during the pandemic

As you would imagine, what we search for online shifted over the past few months. The unknowns push information gathering. Schema Design, in collaboration with the Google News Initiative and Axios, broke down the main changes in search since January. Using a beeswarm chart, each circle represents a query and the size of a circle represents the rank in a query. I really wanted to mouse over the circles to...

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Change in Google searches since the virus

The coronavirus changed what information we search for. Has anyone been more interested in making masks or hand sanitizer in the history of the world? For The Washington Post, Alyssa Fowers compares search rankings for how, where, what, and how the week of April 5 to 11, for 2019 against 2020. Tags: Alyssa Fowers, coronavirus, Google, search, Washington Post

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Change in foot traffic in outbreak cities

From The Economist, this chart shows the (mostly) decrease in foot traffic in major cities with coronavirus outbreaks. It’s based on data scraped from that section in Google Maps that shows how busy a location is, which I’m kind of surprised the Google limits allowed for. See James Fransham’s thread for more details on their process. Tags: coronavirus, Economist, Google, traffic

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