A.I. Articles of the Week, Feb. 2018 #2

Shan Tang
3 min readFeb 12, 2018

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Sam Rowe for NPR

Just How Shallow is the Artificial Intelligence Talent Pool?

Research from Element AI indicates only 22,000 have right skills globally

Why Deep Learning Needs Standards for Industrialization

“I was recently was posed the question, “how do we define standards for AI?” I am primarily focused in the space of Deep Learning Artificial Intelligence (AI).”

New quantum linear system algorithm could speed up machine learning

The researchers have proposed a new algorithm for solving systems of linear equations that is faster than both the classical and the previous quantum versions, and without restrictions on the kind of data it works for.

Facial Recognition Is Accurate, if You’re a White Guy

When the person in the photo is a white man, the software is right 99 percent of the time. But the darker the skin, the more errors arise — up to nearly 35 percent for images of darker skinned women, according to a new study that breaks fresh ground by measuring how the technology works on people of different races and gender.

Philosophers are building ethical algorithms to help control self-driving cars

Artificial intelligence experts and roboticists aren’t the only ones working on the problem of autonomous vehicles. Philosophers are also paying close attention to the development of what, from their perspective, looks like a myriad of ethical quandaries on wheels.

Making Sense of the Bias / Variance Trade-off in (Deep) Reinforcement Learning

What goes into a stable, accurate reinforcement signal?

A Code of Ethics for Data Science

2.5 quintillion bytes of data are created every day. It’s created by you when you’re commute to work or school, when you’re shopping, when you get a medical treatment, and even when you’re sleeping. It’s created by you, your neighbors, and everyone around you. So, how do we ensure it’s used ethically?

Experts say AI isn’t quite fire or the wheel — yet

Some researchers and business leaders are putting artificial intelligence — in its current and aspirational forms — on the same pedestal of human invention and innovation as fire, electricity and the light bulb. But other experts say we will not know for a long time whether AI will ever merit such lofty imagery.

Can Computers Learn Like Humans?

A List of Chip/IP for Deep Learning (keep updating)

Machine Learning, especially Deep Learning technology is driving the evolution of artificial intelligence (AI). At the beginning, deep learning has primarily been a software play. Start from the year 2016, the need for more efficient hardware acceleration of AI/ML/DL was recognized in academia and industry. This year, we saw more and more players, including world’s top semiconductor companies as well as a number of startups, even tech giants Google, have jumped into the race. I believe that it could be very interesting to look at them together. So, I build this list of AI/ML/DL ICs and IPs on Github and keep updating. If you have any suggestion or new information, please let me know.

Weekly Digest Jan. 2018 #1

Weekly Digest Jan. 2018 #2

Weekly Digest Jan. 2018 #3

Weekly Digest Jan. 2018 #4

Weekly Digest Jan. 2018 #5

Weekly Digest Feb. 2018 #1

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Shan Tang

Since 2000, I worked as engineer, architect or manager in different types of IC projects. From mid-2016, I started working on hardware for Deep Learning.