Black Holes and AI


Awesome, not awesome.

“Facebook has promised to use artificial intelligence to stop suggesting users invite their dead friends to parties…“Once an account is memorialised, we use AI to help keep the profile from showing up in places that might cause distress, like recommending that person be invited to events or sending a birthday reminder to their friends.” — Alex Hern, Technology editor Learn More from The Guardian >

#Not Awesome
“Dozens of UK business owners are using artificial intelligence to scrutinise staff behaviour minute-to-minute by harvesting data on who emails whom and when, who accesses and edits files and who meets whom and when…The TUC’s general secretary, Frances O’Grady, said: “Workers want to be trusted to do their jobs. But this kind of high-tech snooping creates fear and distrust. And by undermining morale, it could do businesses more harm than good.” — Robert Booth, Social affairs correspondent Learn More from The Guardian >

What we’re reading.

1/ Dr. Katie Bouman and a team of scientists at MIT build an AI algorithm that reveals the first photograph of a black hole to the world. Learn More from PBS >

2/ Amazon uses machine learning to do everything from forecasting demand for computation for AWS, optimize routes for robots along factory floors, and tracking items that shoppers put in their baskets in the Amazon Go stores. Learn More from The Economist >

3/ The Chinese government wants to use AI as a tool to “improve” social governance — and some of the country’s facial recognition startups are helping it to persecute ethnic minorities. Learn More from ChinAI >

4/ The Pentagon is making major investments in self-driving combat vehicles that take soldiers out of the driver’s seat because “more than half of all battlefield casualties occur when soldiers are delivering fuel, food or other supplies in combat zones.” Learn More from Axios >

5/ Automobile executives fear the Boeing crashes that left hundreds of people dead will be a major setback for the future of autonomous vehicles — it’s unclear that consumers should trust companies and regulators to develop technologies that will keep them out of harms way. Learn More from Quartz >

6/ We need to think twice about the introduction of ML algorithms in medicine and law — humans have been proven to take algorithmic recommendations at face value without doing additional work to verify the results are right (or fair). Learn More from The Economist >

7/ What you say to your Alexa speaker may be a whole lot less private than you think — a team of people may be listening to your words and training the machine learning algorithms that decipher them. Learn More from Bloomberg >

Links from the community.

“Here’s my conversation with @elonmusk on the Artificial Intelligence “ submitted by Avi Eisenberger (@aeisenberger). Learn More from Twitter >

“How and Why I am starting a Machine Learning Career.” by Danstan Onyango Learn More from Noteworthy >

“Artificial Intelligence and the future of writers and novelists.” by Shruti Sinha Learn More from Noteworthy >

“Multiple Object Tracking Algorithms” by Manivannan Murugavel Learn More from Noteworthy >

“Convolutional Neural Network on Nigerian Foods” by Kehinde Ogunyale Learn More from Noteworthy >

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Source: Machine Learnings – Medium

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