Our change in behavior is breaking their models...

When covid-19 hit, we started buying things we’d never bought before. The shift was sudden: the mainstays of Amazon’s top ten—phone cases, phone chargers, Lego—were knocked off the charts in just a few days. Nozzle, a London-based consultancy specializing in algorithmic advertising for Amazon sellers, captured the rapid change in [a] simple graph...
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But they have also affected artificial intelligence, causing hiccups for the algorithms that run behind the scenes in inventory management, fraud detection, marketing, and more. Machine-learning models trained on normal human behavior are now finding that normal has changed, and some are no longer working as they should. 
Read the rest in the MIT Technology Review - "Our weird behavior during the pandemic is messing with AI models"

AWS Makes a COVID-19 Data Lake available to the public!

Today, we are making a public AWS COVID-19 data lake available – a centralized repository of up-to-date and curated datasets on or related to the spread and characteristics of the novel corona virus (SARS-CoV-2) and its associated illness, COVID-19. Globally, there are several efforts underway to gather this data, and we are working with partners to make this crucial data freely available and keep it up-to-date. Hosted on the AWS cloud, we have seeded our curated data lake with COVID-19 case tracking data from Johns Hopkins and The New York Times, hospital bed availability from Definitive Healthcare, and over 45,000 research articles about COVID-19 and related coronaviruses from the Allen Institute for AI. We will regularly add to this data lake as other reliable sources make their data publicly available.

Read more about the AWS public data Lake

Why The Full Stack Engineer Is Problematic -IT Revolution

One prime complaint from engineers is the consistent interruptions that prevent individuals from completing work during the day. If you can’t do your most important work during business hours, when do you get your work done? The pressure to work during the wee hours of the night on top of one’s regular day job is strong.

Working long hours may come with trendy bragging rights, implying strength and power, but as The Wall Street Journal health writer Melinda Beck says, “Genuine ‘short sleepers’ only need four hours of sleep per night, but they comprise only 1% to 3% of the total population.” So for the 97% to 99% of us who aren’t short sleepers, working the wee hours brings sleep deprivation and mistakes—both are contributors to burnout.


Read more at ITRevolution