Awesome, not awesome.
#Awesome
“Applying just a bit of strain to a piece of semiconductor or other crystalline material can deform the orderly arrangement of atoms in its structure enough to cause dramatic changes in its properties, such as the way it conducts electricity, transmits light, or conducts heat. Now, a team of researchers at MIT and in Russia and Singapore have found ways to use artificial intelligence to help predict and control these changes, potentially opening up new avenues of research on advanced materials for future high-tech devices.” — David L. Chandler, Writer Learn More from MIT Technology Review >
#Not Awesome
“Rice University statistician Genevera Allen issued a grave warning at a prominent scientific conference this week: that scientists are leaning on machine learning algorithms to find patterns in data even when the algorithms are just fixating on noise that won’t be reproduced by another experiment… The problem, according to Allen, can arise when scientists collect a large amount of genome data and then use poorly-understood machine learning algorithms to find clusters of similar genomic profiles.” — Jon Christian, Journalist. Learn More from Futurism >
What we’re reading.
1/ YouTube’s algorithms are “enabling the production and distribution of paedophilic content,” and major brands are running ads right alongside it. Learn More from WIRED >
2/ To make sure future generations have an amicable relationship with AI technologies, industry giants should invest heavily in re-training displaced workers and partnerships with educational institutions. Learn More from TechCrunch >
3/ In an attempt to avoid the tech backlash that’s bringing Facebook and Google under fire, AI researchers are trying to establish procedures to make sure their inventions aren’t abused by bad actors. Learn More from Axios >
4/ One researcher argues that in order to keep AI research from being abused, it must be published openly so that all are aware of it. Learn More from The Gradient >
5/ There are virtually not limits to the ways AI technologies will revolutionize the medical field — the question is, “how quickly should we adopt them?” Learn More from The New York Times >
6/ If a machines doesn’t understand the reason for why it’s doing something, can it actually be considered creative? Learn More from MIT Technology Review >
7/ Aid agencies that use AI to predict when and where food shortages are likely to emerge may be able to stop wars before they happen. Learn More from BBC >
Links from the community.
“Let’s make some molecules with machine learning!” by Avi Eisenberger (@flawnsontong1). Learn More from Noteworthy >
“Tutorial: Machine Learning Data Set Preparation, Part 1” submitted by Samiur Rahman (@samiur1204). Learn More from Sean McWillie’s blog >
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