Artificial Intelligence/Machine Learning Roundup #107

1. What’s wrong with AI? Try asking a human being | Kenan Malik

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2. Forecasting at Uber, Text analysis at Dropbox, How to deliver on ML projects, AI benchmarks, AI frameworks and more

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3. Neural networks don’t understand what optical illusions are

Human vision is an extraordinary facility.

But the visual system also has a well-known set of shortcomings that we experience as optical illusions. In recent years, machines have learned to recognize objects and faces in images and then to create similar images themselves. Read More

4. [1810.05315] Learning to Reason

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5. [1810.05593] Fast Construction of Correcting Ensembles for Legacy Artificial Intelligence Systems: Algorithms and a Case Study

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6. [1710.09762] How to Fool Radiologists with Generative Adversarial Networks? A Visual Turing Test for Lung Cancer Diagnosis

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7. Data Machina – Issue #144

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8. A ladder-climbing robotic snake

13th October 2018

A ladder-climbing robotic snake

At the International Conference on Intelligent Robots and Systems (IROS) held in Madrid earlier this month, researchers presented a flexible snake-like robot that is able to climb ladders. The project was a collaboration between Kyoto University and the University of Electro-Communications in Japan.

The team’s paper includes the following abstract:

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9. Applying Deep Learning to Metastatic Breast Cancer Detection

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10. Robot farms, the sleep economy and more

 

–Vox explores how sleep has become the newest luxury commodity.

–Colleges are opening ‘Trans Closets,’ offering a safe, judgment-free space for transgender, transitioning and non-binary students to shop for clothing, Dazed shares.

–WeWork hopes to rejuvenate retail with a network of in-house stores, “angling its physical assets and membership base to become a retailer in its own right,” says Digiday. Read More

11. Unsupervised Learning via Meta-Learning on ShortScience.org

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12. This Robotic Warehouse Fills Orders in Five Minutes, and Fits in City Centers

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13. AI system creates synthetic brain scans

AI system creates synthetic brain scans

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Artificial intelligence has had a huge impact on how medical images are understood.  Despite this technological assistance, a significant challenge for scientists is still the lack of accessible, accurate and reliable data to train their neural networks. Thanks to researchers at an American technology company NVIDIA, scientists are now using Generative Adversarial Networks (GANs) to generate abnormal brain MRIs that can be used to train neural networks. Read More

14. 2018-2019 Machine Learning Advances and Applications Seminar

The 2018-2019 Machine Learning Advances and Applications Seminar schedule is now posted.

The Fields Institute invites international speakers, academic faculty and industry, to present on a range of topics in machine learning.

Seminars take place from 12:00 p. Read More

15. How was it for you? | What’s Next: Top Trends

There’s an episode of the TV series Black Mirror where the main character becomes obsessed with ‘liking’ everything. And if that isn’t bad enough there’s now news that UK schools are to measure the happiness of their students. You mean ask the students how they are feeling about the endless changes of direction, the obsession with exams (narrow measurement from the age of five in many cases) and generally the stress and anxiety created by education. Read More

16. AI can help us unlock the world’s most complex operating system – the human body

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17. Facebook has built an AI-based tool that fixes the social network when it crashes

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18. You’re Expecting Too Much Out of Boston Dynamics’ Robots

At the WIRED25 festival in San Francisco Sunday evening, Boston Dynamics’ SpotMini robot got onstage and did what no other quadruped robot has done before: It danced the running man like it was born to. It was a bit more, well, robotic than a human, but it illustrated just how far Spot has come: Twenty-five years into both WIRED’s and Boston Dynamics’ lives, robots have finally grown sophisticated enough to dance through our world.

In reality, they’re so far away from doing so that it’s more productive to talk about how climate change will destroy the planet long before then. Read More

19. The Guardian view on artificial intelligence: human learning | Editorial

They not only monitor workers’ actions but are used to choose who should be employed. Yet it emerged last week that the company had scrapped an attempt to use artificial intelligence to select workers on the basis of their CVs, since the results consistently discriminated against women. The technical or operational point is that these programs, no matter how fast they learn, can only learn from the data presented to them. Read More