After last month’s “all coronavirus, all the time” report, I was concerned that this month would be more of the same. And there is, indeed, a lot of coronavirus. But there are many other trends and interesting items to look at–possibly a sign that people are working effectively from home.
Coronavirus prompts serious discussion of changes to the financial system. There’s no doubt that money’s dirty; and it isn’t terribly useful in the context of “social distancing.” Rethinking our financial system might lead to a public venmo, or even further to a digital dollar. (China is the leader here–by a large margin.)
Coronavirus and game play: Not surprisingly, COVID-19 has led to a big surge in game play and virtual reality. Might surviving isolation during a pandemic be the killer app for VR? (This trend arrived too late to help the VR startup Magic Leap, which appears to be failing.) Fred Wilson says, wisely I think, that social isolation will teach how much we crave being in “real life.”
It’s hardly news that misinformation about Coronavirus is proliferating. The big question is whether automated attempts to stop that proliferation will succeed. YouTube, Twitter, and Facebook (including WhatsApp) are cracking down. Facebook is referring people who see misinformation to “authoritative resources.”
I haven’t heard as much about Citizen Science in the past few years, but it’s making a reappearance. Coronavirus binder designs (proteins that bind to Coronavirus) modeled by citizen scientists, are in the pipeline for testing. Fold-it is a game where you design proteins (protein folding) to achieve some goal–in this case, binding to Coronavirus.
Citizens are also playing a role on the front lines, with community-run COVID-19 testing. (I’ve also seen pleas for citizens willing to help with contact tracing.)
Apple and Google are collaborating on OS-level tools for privacy-protecting contact tracing that will interoperate between Android and iOS. (Apps will be implemented by third parties, presumably healthcare organizations.) Germany was working on its own framework for contact tracing using cell phone apps, but it is now backing the Apple-Google collaboration.
Will we see “re-shoring” of jobs because of coronavirus? Outsourcing isn’t as attractive when lockdowns limit the supply of offshore labor, and it’s impossible to visit overseas contractors. Another consequence will be the increased use of AI, particularly in customer service.
Xenobots are living (literally) programmable robots, assembled from cultured frog skin cells.
Farming is very high tech. A European project called ROMI is developing robots for weeding crops on small (micro) farms; should cost under $5000. Uses AI and computer vision to identify weeds and crop diseases.
Artificial Intelligence and Machine Learning
Good thinking about how tech can build: infusing manufacturing with software and intelligence (IoT); enabling remote work; getting beyond the unicorn mindset.
Microsoft uses machine learning to inspect source code for security vulnerabilities. They claim they can identify high priority security bugs in new code 97% of the time.
Facebook uses AI bots to simulate users for testing new social applications. They start up thousands of bots at a time to experiment with group dynamics, vulnerabilities, and privacy settings.
Splunk announced Remote Work Insights, a network monitoring product for work-at-home companies. It has been criticized as employee surveillance; Splunk has responded that their intent is to monitor connectedness, not activity.
Low-code automation is another aspect of the democratization of technology. The idea is to build tools that can be used by people without requiring a lot of programming experience. The target audiences are all over the place: from unskilled workers to managers, and even to programmers, where these tools will simplify product development.
Microsoft announced IPE, a project that will contribute to the Linux kernel. IPE is for listing allowed binaries, and automatically checking signatures; it is intended for high security versions of Linux. But what’s more important is that this is another sign that Microsoft has changed very deeply.
IBM is offering free COBOL training, in response to state governments’ needs for more programmers to update unemployment systems.
JupyterLab is now a full-fledged, web-based, multi-language IDE for data.
Google is adding differentiable programming to the Swift programming language to simplify development of ML models. This means that their enhanced Swift language has primitives for computing the derivative/gradient of a function; in turn, this greatly simplifies key AI algorithms that involve gradient descent.
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