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Today: Before 'Pocahontas,' Trump Went After the Mohawks. Ready for July 4?

Los Angeles Times

Here are some story lines I don't want you to miss today. The ads warned of the evils an Indian casino would bring to the Catskills: "increased crime, broken families, bankruptcies and, in the case of the Mohawks, violence." They were taken out by a self-described anti-gambling group supposedly supported by 12,000 "pro-family" donors. Except virtually all the money for the 2000 campaign, more than 1 million, came from Donald Trump. Take a look at the ads he approved and the elaborate means to conceal his role.


What If We Replaced School With A Bot?

#artificialintelligence

Instead of gathering students into a room and teaching them, everybody learns on their own time, on tablets and guided by artificial intelligence. First, I talk to a Ashok Goel, a computer scientist who developed an artificially intelligent TA named Jill Watson and didn't tell any of his students she wasn't a human. Then I talk to two people building future, app based educational systems. Jessie Woolley-Wilson from DreamBox explains what adaptive learning is, and how it can help create a better learning experience for kids. She also talks about all the data they collect on kids to better serve them (data we'll come back to later in the episode.)


Tesla driver's death using car's 'Autopilot' probed by NHTSA

Associated Press

FILE - In this Monday, April 25, 2016, file photo, a man sits behind the steering wheel of a Tesla Model S electric car on display at the Beijing International Automotive Exhibition in Beijing. Federal officials say the driver of a Tesla S sports car using the vehicle's "autopilot" automated driving system has been killed in a collision with a truck, the first U.S. self-driving car fatality. The National Highway Traffic Safety Administration said preliminary reports indicate the crash occurred when a tractor-trailer made a left turn in front of the Tesla at a highway intersection. NHTSA said the Tesla driver died due to injuries sustained in the crash, which took place on May 7 in Williston, Fla. (AP Photo/Mark Schiefelbein, File) FILE - In this Monday, April 25, 2016, file photo, a man sits behind the steering wheel of a Tesla Model S electric car on display at the Beijing International Automotive Exhibition in Beijing. Federal officials say the driver of a Tesla S sports car using the vehicle's "autopilot" automated driving system has been killed in a collision with a truck, the first U.S. self-driving car fatality.


Tesla driver killed in crash while using car's 'Autopilot'

Associated Press

FILE - In this Monday, April 25, 2016, file photo, a man sits behind the steering wheel of a Tesla Model S electric car on display at the Beijing International Automotive Exhibition in Beijing. Federal officials say the driver of a Tesla S sports car using the vehicle's "autopilot" automated driving system has been killed in a collision with a truck, the first U.S. self-driving car fatality. The National Highway Traffic Safety Administration said preliminary reports indicate the crash occurred when a tractor-trailer made a left turn in front of the Tesla at a highway intersection. NHTSA said the Tesla driver died due to injuries sustained in the crash, which took place on May 7 in Williston, Fla. (AP Photo/Mark Schiefelbein, File) FILE - In this Monday, April 25, 2016, file photo, a man sits behind the steering wheel of a Tesla Model S electric car on display at the Beijing International Automotive Exhibition in Beijing. Federal officials say the driver of a Tesla S sports car using the vehicle's "autopilot" automated driving system has been killed in a collision with a truck, the first U.S. self-driving car fatality.


Machine learning for the future - EE Times Asia

#artificialintelligence

In a keynote talk, Dean outlined the history of machine learning (ML) and neural networks and various ways to programme models to take advantage of raw data coming through in the form of images or audio. He also detailed how ML has taken shape at Google, which recently announced that it will open a machine learning center in Europe. The company developed its own accelerator chips for artificial intelligence it calls tensor processing units (TPUs) after the open source TensorFlow algorithms it released last year.


LOOK: Graceful robotic hottie stuns visitors at Tianjin Davos

#artificialintelligence

An eerily lifelike robotic beauty dressed in traditional Chinese style has attracted quite a bit of attention at the 2016 Summer Davos Forum in Tianjin. The robot, named Jia Jia, is the same size as a real person. It has delicate facial features and intricate details. People have even begun calling it by another name, "Robot goddess," Sina reports. Netizens also commented that her profile earns her a high yanzhi (??) -- Chinese internet slang meaning "attractiveness index."


China factory activity slips again as slowdown weighs

U.S. News

In this June 1, 2016 photo, a worker adjusts a welding robot at a subsidiary of China Offshore Oil Engineering Co. Ltd. in Qingdao in eastern China's Shandong province. An official survey of Chinese manufacturing release Friday, July 1, 2016, shows that activity was flat in June, signaling further weakness in the world's No. 2 economy as it undergoes a prolonged slowdown.


Capacity Building and Development : Essential Evils of Technology (Internet,Internet of things,Artificial Intelligence) 11-05

#artificialintelligence

This should not be construed as a negative article. I am myself a keen learner of technology. I contribute regularly to the research in technology projects of MIT, Mckinsey & Co, Harvard University, others, in projects related to Digital Technology, Artificial Intelligence, and Internet of Things. My concern is that in our enthusiasm to create and move technology forward, we are little less serious on creating safeguards and adversity proof environment. They create the temperature for your body according to the weather.


Tesla driver killed in crash while using car's 'Autopilot'

Associated Press

FILE - In this Monday, April 25, 2016, file photo, a man sits behind the steering wheel of a Tesla Model S electric car on display at the Beijing International Automotive Exhibition in Beijing. Federal officials say the driver of a Tesla S sports car using the vehicle's "autopilot" automated driving system has been killed in a collision with a truck, the first U.S. self-driving car fatality. The National Highway Traffic Safety Administration said preliminary reports indicate the crash occurred when a tractor-trailer made a left turn in front of the Tesla at a highway intersection. NHTSA said the Tesla driver died due to injuries sustained in the crash, which took place on May 7 in Williston, Fla. (AP Photo/Mark Schiefelbein, File) FILE - In this Monday, April 25, 2016, file photo, a man sits behind the steering wheel of a Tesla Model S electric car on display at the Beijing International Automotive Exhibition in Beijing. Federal officials say the driver of a Tesla S sports car using the vehicle's "autopilot" automated driving system has been killed in a collision with a truck, the first U.S. self-driving car fatality.


Efficient and Consistent Robust Time Series Analysis

arXiv.org Machine Learning

We study the problem of robust time series analysis under the standard auto-regressive (AR) time series model in the presence of arbitrary outliers. We devise an efficient hard thresholding based algorithm which can obtain a consistent estimate of the optimal AR model despite a large fraction of the time series points being corrupted. Our algorithm alternately estimates the corrupted set of points and the model parameters, and is inspired by recent advances in robust regression and hard-thresholding methods. However, a direct application of existing techniques is hindered by a critical difference in the time-series domain: each point is correlated with all previous points rendering existing tools inapplicable directly. We show how to overcome this hurdle using novel proof techniques. Using our techniques, we are also able to provide the first efficient and provably consistent estimator for the robust regression problem where a standard linear observation model with white additive noise is corrupted arbitrarily. We illustrate our methods on synthetic datasets and show that our methods indeed are able to consistently recover the optimal parameters despite a large fraction of points being corrupted.