AI

YouTube’s algorithms are being abused

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Awesome, not awesome.

#Awesome
“Researchers at Carnegie Mellon and the University of Pittsburgh analyzed how suicidal individuals think and feel differently about life and death, by looking at patterns of how their brains light up in an fMRI machine. Then they trained a machine learning algorithm to isolate those signals… The computational classifier was able to pick out the suicidal ideators with more than 90 percent accuracy. Furthermore, it was able to distinguish people who had actually attempted self-harm from those who had only thought about it.”— Megan Molteni, Science WriterLearn More on WIRED >

#Not Awesome
“…Any automated computer vision system, whether it be facial recognition, self-driving cars, or even airport security, can be tricked into “seeing” something that’s not actually there. Computer scientists creating this attack say it’s necessary to develop so we can understand what’s possible before someone who means harm can take advantages of the shortcomings of AI.” — Dave Gershgorn, Artificial Intelligence Reporter Learn More on Quartz >

What we’re reading.

1/ YouTube’s machine learning algorithms are supposed to police inappropriate content, but they’re being abused — and young kids have recently been exposed to awful videos. Learn More on The New York Times >

2/ Cash-rich Tech companies drain universities of their AI researchers, and people are fearful that both students and society at large will suffer as a result. Learn More on The Guardian >

3/ As some humans hope to become immortal by “uploading their minds” into virtual realities or robots, it’s not unreasonable to ask if death will be conquered in our lifetime. Learn More on Scientific American >

4/ The collective mind of the Tech community predicted that bots would play a major role in our lives over the coming years — it didn’t predict that they would be “fake-news disseminating agents of Russia.” Learn More on The New York Times >

5/ Machine learning holds great promise for scientists and researchers — helping them to avoid spending times on tedious, repeatable tasks. Learn More on Smithsonian >

6/ Satellite imagery companies are using artificial intelligence algorithms to help companies and organizations do everything from tracking deforestation to estimating the world’s crude oil supply to mapping poverty. Learn More on WIRED >

7/ Machines may never be aware in the same way that we are, but developments in artificial consciousness will force us to reconsider what it truly means to be conscious. Learn More on Motherboard >

What we’re building.

At work, our inboxes fill up quicker than we can empty them, key decisions are posted and immediately lost in Slack, and we forget the thousands of useful articles we’ve read that could help us do our jobs better. Information overload is wreaking havoc on our ability to process information, make decisions, and be productive.

We’re building Journal to help you remember and find all the important conversations, ideas, and knowledge you need to work faster.

Join our waitlist, and you’ll be one of the first people to get free access to our chrome extension. You’ll never forget important information or lose time recreating work again.

Where we’re going.

Highlight from “PART II: Routes to defensibility for your AI Startups”

“…Being able to sell a simple product, to a well defined buyer in order to get access to an initial dataset is absolutely key when scaling an AI startup. I think a good way to view this is to build a parallel with network effects in marketplaces. Having a very good operational team in the early days of a marketplace is theoretically not a long term competitive advantage but it helps marketplaces network effect to kick in…”

Learn More on the Machine Learnings blog >

Louis Coppey
Investor, Point Nine Capital

Links from the community.

“Why Twitter is the Best Social Media Platform for Disinformation” submitted by Mark Philpot (@mark_philpot). Learn More on Motherboard >

“These Students Built The Anti-Bot Algorithm Twitter Desperately Needs” submitted by Avi Eisenberger (@aeisenberger). Learn More on CO.DESIGN >

“The State of Data Science & Machine Learning” submitted by Samiur Rahman (@samiur1204). Learn More on Kaggle >

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Machine Learnings – Medium

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