A.I. Articles of the Week, May. 2018 #4

Shan Tang
3 min readMay 22, 2018

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Uh, Did Google Fake Its Big A.I. Demo?

The demo was indeed impressive. It was also pretty unsettling, as many people quickly noted. (“Horrifying,” wrote one critic.) But is it possible that the promise of Google’s advanced artificial-intelligence tech is too good to be true?

A.I. Is Harder Than You Think

The reason Google Duplex is so narrow in scope isn’t that it represents a small but important first step toward such goals. The reason is that the field of A.I. doesn’t yet have a clue how to do any better.

Inside Google, a Debate Rages: Should It Sell Artificial Intelligence to the Military?

To win in the business of cloud computing, the company tiptoes into the business of war. Some staff fear it’s a first step toward autonomous killing machines.

Setting benchmarks in machine learning

Dave Patterson and other industry leaders discuss how MLPerf will define an entire suite of benchmarks to measure performance of software, hardware, and cloud systems.

The World’s Dominant Crypto-Mining Company Wants to Own AI

In a rare interview, Bitmain’s Jihan Wu talks about his plans to take on Nvidia, Intel, and AMD.

HOW TECH CAN TURN DOCTORS INTO CLERICAL WORKERS

THE THREAT THAT ELECTRONIC HEALTH RECORDS AND MACHINE LEARNING POSE TO PHYSICIANS’ CLINICAL JUDGMENT — AND THEIR WELL-BEING.

To Build Truly Intelligent Machines, Teach Them Cause and Effect

Judea Pearl, a pioneering figure in artificial intelligence, argues that AI has been stuck in a decades-long rut. His prescription for progress? Teach machines to understand the question why.

How the Enlightenment Ends

Philosophically, intellectually — in every way — human society is unprepared for the rise of artificial intelligence.

Artificial intelligence will both disrupt and benefit the workplace, Stanford scholar says

Artificial intelligence offers both promise and peril as it revolutionizes the workplace, the economy and personal lives, says James Timbie of the Hoover Institution, who studies artificial intelligence and other technologies.

Employers are monitoring computers, toilet breaks — even emotions. Is your boss watching you?

From microchip implants to wristband trackers and sensors that can detect fatigue and depression, new technology is enabling employers to watch staff in more and more intrusive ways. How worried should we be?

Introduction to Recommender Systems in 2018

In this blog post, we’ll describe the broad types of the most popular recommender systems and give insights into how they work, going through a few examples.

Neural text generation: How to generate text using conditional language models

Here is a toy project: build a Twitter bot that generates dialog in the style of Simpsons characters.

Two-sample t-test and robustness

A two-sample t-test is intended to determine whether there’s evidence that two samples have come from distributions with different means. The test assumes that both samples come from normal distributions.

TF-rex: Playing Google’s T-rex game with TensorFlow

The goal of this project is to play Google’s offline T-rex Dino game using Reinforcement Learning (RL). The RL algorithm is based on the Deep Q-Learning algorithm [1] and is implemented in TensorFlow (TF), hence the name TF-rex ;). Google’s offline game consists of a T-rex striving to dodge obstacles, such as cactuses and birds, and surviving as long as possible. The dino is able to perform three actions: “jumping”, “ducking” and “going forward”

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 Apr. 2018 #1

Weekly Digest Apr. 2018 #2

Weekly Digest Apr. 2018 #3

Weekly Digest Apr. 2018 #4

Weekly Digest May. 2018 #1

Weekly Digest May. 2018 #2

Weekly Digest May. 2018 #3

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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.