Daily Artificial Intelligence News Roundup #147

1. How Coursera uses Data Visualization and Clustering to Categorize Content

Launched in 2012 by Andrew Ng, the content on Coursera has increased multi-fold since.

Courses on Coursera cover topics ranging from photography to probabilistic graphical models to constitutional struggles in the Muslim world. A couple of years ago, we overhauled our course categories and implemented a new categorization system we call domains and subdomains. Read More

2. Thoughts on Recent Research Paper and Associated Article on Amazon Rekognition

We welcome feedback, and indeed get feedback from folks all the time, but this research paper and article are misleading and draw false conclusions. The first capability is facial analysis—for a particular image or video, the service can tell you where a face appears, and certain characteristics of the image (such as if the image contains a smile, glasses, mustache, or the gender of a face). The second capability of Amazon Rekognition is commonly known as facial recognition. Read More

3. Deep Neural Linear Bandits: Overcoming Catastrophic Forgetting through Likelihood Matching

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4. Practical Deep Learning for Coders 2019 · fast.ai

There are seven lessons, each around 2 hours long, and you should plan to spend about 10 hours on assignments for each lesson. Google Cloud and Microsoft Azure have integrated all you need for the courses into their GPU-based platforms, and there are “one-click” platforms available too, such as Crestle and Gradient.

The course assumes you have at least a year of coding experience (preferably in Python, although experienced coders will be able to pick Python up as they go; we have a list of python learning resources available), and have completed high-school math (some university-level math is introduced as needed during the course). Read More

5. Face-scanning A.I. can help doctors spot unusual genetic disorders

Facial recognition can help unlock your phone. Could it also be able to play a far more valuable role in people’s lives by identifying whether or not a person has a rare genetic disorder, based exclusively on their facial features. Its best performance came in distinguishing between different subtypes of a genetic disorder called Noonan syndrome, one of whose symptoms includes mildly unusual facial features. Read More

6. 131: IBM optimizes AI with AI, via ‘NeuNets’; Amazon reveals its Scout delivery robot; Google releases 300k Natural Questions dataset

Amazon is trialing Scout with six robots that will deliver packages throughout the week in  Snohomish County, Washington.   Read more: Meet Scout (Amazon blog). Enter the Robotrix:…New dataset gives researchers high-resolution data over 16 exquisitely detailed environments…What’s better to use for a particular AI research experiment – a small number of simulated environments each accompanied by a large amount of very high-quality data, or a very large number of environments each accompanied by a small amount of low-to-medium quality data. Read More

7. Creating better AI partners: A case for backward compatibility

Sure, we can assume an improvement in accuracy or speed on the part of the agent, a seemingly beneficial change. However, current practices for updating the models used to power AI partners don’t account for how practitioners have learned over time to trust and make use of an agent’s contributions. In the work we’re presenting next week at the Association for the Advancement of Artificial Intelligence’s annual conference (AAAI 2019), we introduce a platform, openly available on GitHub, to help better understand the human-AI dynamics in these types of settings. Read More

8. Mila » CIFAR AI Chairs in machine learning and in the area of AI and ethics

Mila is seeking candidates for CIFAR AI Chairs not just in machine learning but also in the area of AI and ethics. Please communicate with Yoshua Bengio yoshua.

See more information on CIFAR AI Chairs here: https://www. Read More

9. Can AI Tell the Difference Between a Polar Bear and a Can Opener?

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10. Apex.AI Does the Invisible Work That Will Make Self-Driving Cars Possible

Autonomous cars are some of the most complex mobile robots ever developed.

About a decade ago, Willow Garage attempted to solve this problem with the Robot Operating System (ROS), an open source software framework that manages hardware and software integration and communications while also providing libraries, drivers, and software packages for common robot functionality. AI comes in—taking the early framework of ROS 2, and building a system on top of it that automotive companies can develop on today with confidence that they’ll be able to deploy it. Read More

11. The Best of the Physics arXiv (week ending January 26, 2019)


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12. Bricks of the Trade: Techie Harnesses AI Skills to Sort Son’s Legos

Francisco “Paco” Garcia is a dad. This is a dad with a GPU, a GPU he put to use doing what every dad dreams of doing: sorting those Legos out once and for all.

Garcia shared with us how — inspired by a Japanese cucumber farmer — he designed, built, and documented his work building a Lego sorter using TensorFlow, Raspberry Pi, and his NVIDIA GPU. Read More