Tag: AI

Drone Race: Human Versus Artificial Intelligence

JPL engineers recently finished developing three drones and the artificial intelligence needed for them to navigate an obstacle course by themselves.

In October, NASA’s California-based Jet Propulsion Laboratory pitted a drone controlled by artificial intelligence against a professional human drone pilot named Ken Loo.

According to NASA’s press release, it had been researching autonomous drone technology for the past two years at that point, funded by Google and its interest in JPL’s vision-based navigation work.

The race consisted of a time-trial where the lap times and behaviors of both the A.I.-operated drone and the manually-piloted drone were analyzed and compared. Let’s take a look at the results.

NASA said in its release that the company developed three drones; Batman, Joker, and Nightwing.

Researchers focused mostly on the intricate algorithms required to navigate efficiently through a race like this, namely obstacle avoidance and maximum speed through narrow environments.

These algorithms were then combined with Google’s Tango technology, which JPL had a significant hand in as well.

Task Manager of the JPL project, Rob Reid said, “We pitted our algorithms against a human, who flies a lot more by feel.”

“You can actually see that the A.I. flies the drone smoothly around the course, whereas human pilots tend to accelerate aggressively, so their path is jerkier.”

As it turned out, Loo’s speeds were much higher, and he was able to perform impressive aerial maneuvers to his benefit, but the A.I.-infused drones were more consistent, and never gave in to fatigue.

“This is definitely the densest track I’ve ever flown,” said Loo. “One of my faults as a pilot is I get tired easily. When I get mentally fatigued, I start to get lost, even if I’ve flown the course 10 times.”

Loo averaged 11.1 seconds per lap, while the autonomous unmanned aerial vehicles average 13.9 seconds.

In other words, while Loo managed to reach higher speeds overall, the drones operating autonomously were more consistent, essentially flying a very similar lap and route each time.

Our autonomous drones can fly much faster,” said Reid. “One day you might see them racing professionally!

Of that latter statement, there’s certainly no doubt.

A future where companies like Google and NASA square off in public arenas where their autonomous drones compete against one another is definitely plausible.

It wouldn’t be shocking to see such an event televised, either, as we’re already seeing similar results with the Drone Racing League.

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Pass it on: Popular Science

A Smart City In China Uses AI To Track Every Movement Of Citizens

Chinese e-commerce giant Alibaba Group Holding Limited is aiding the Chinese police state in catching people who break the law, tracking criminals in real time in their new “smart city” of Hangzhou, home to 9 million people.

They are using video feeds and artificial intelligence, tracking things as petty as illegal parking in real time, putting the city under total surveillance.

Using hundreds of thousands of cameras located across the city and artificial intelligence, they were able to do a lot: for the people who control the city, not the residents.

However, the police state implications are the last thing to be mentioned by mainstream science articles covering the issue.

They are falling for it: because if you disregard the immorality of the Chinese government and its laws, and the danger of total surveillance, traffic congestion is allegedly down and other aspects of city life are allegedly more efficient now.

But does efficiency equal happiness for the people, or more profit for those who control the people?

“The stated goal was to improve life in Hangzhou by letting artificial intelligence process this data and use it to control aspects of urban life.”

“It seems to have worked. The trial has been so successful that the company is now packaging the system for export to other places in China – and eventually the rest of the world.

“Using AI to optimise Hangzhou has had many positive effects. Traffic congestion is down, road accidents are automatically detected and responded to faster, and illegal parking is tracked in real time.”

“If someone breaks the law, they too can be tracked throughout the city before being picked up by the police.”

If everything in your city was this tightly controlled, how would you be happy? How could anybody be happy in a “smart city?”

Efficiency does not equal happiness. Life is not improved by efficiency, or even money necessarily. Human happiness cannot possibly be acquired at the expense of everything that a “smart city” would destroy.

Invasive laws in many countries are tolerable now, because they are broken without consequence. If you smoked cannabis illegally, and you would be immediately caught if you tried to smoke for example, would you be happy?

The founder of the company creating this “city brain project” is certainly not subject to the same surveillance that the residents of Hangzhou are.

He’s living it up, a billionaire who is trying to become a movie star. Recently headlines about Alibaba founder Jack Ma read “Billionaire Alibaba founder Jack Ma is going to be a movie star next. Literally.”

An executive from this corporation had the audacity to speak of privacy as if it was some trivial, silly thing that only paranoid people need.

“In China, people have less concern with privacy, which allows us to move faster,” said Xian-Sheng Hua, manager of artificial intelligence at Alibaba, speaking at World Summit AI recently.

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Pass it on: New Scientist

Artificial Intelligence Can Stop Electricity Theft And Meter Misreading

Many developing countries like Brazil, India, Bangladesh, UK have to deal with the electricity crisis. There could be many potential reasons behind this but one of the major ones is electricity theft.

According to a research, UK loses more than 400 million pounds every year due to such malpractices. There are many people who try to save money by stealing electricity.

This kind of practice is mainly adopted in rural areas or in some big factories or mills. But soon this problem could be solved by a team of software developers in Brazil.

The developers tested an AI algorithm on several household’s and the results were very promising.

The developers are not only aiming at stopping electricity theft but they also want to get some crucial information like the peak electricity usage, the general trend in the electricity usage over the course of the year.

All this information could be very useful for the local government and can help them tackle the problem of the electricity crisis.

The algorithm can recognize when energy use at a property was suspiciously low. Developers used the past 5 years electricity consumption data to train the AI.

The algorithm will use the past data against the current consumption. This could help better target physical inspections of properties which could be a hectic process.

According to the researchers, the current algorithm detects the malpractice with a 65% accuracy rate.

Now, researchers are aiming to implement this technology in commercial software that will be used in Latin America.

If the algorithm could work as suggested by the researchers in real life then this could help developing countries boost their development rate.

This would also mean that countries could use the extra money in another task like education, healthcare.

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Pass it on: New Scientist

Facial Recognition Software Can Now Identify People Even If Their Face Is Covered!

A facial recognition system can identify someone even if their face is covered up.

The Disguised Face Identification (DFI) system uses an AI network to map facial points and reveal the identity of people.

It could eventually help to pick out criminals, protesters, or anyone who hides their identity by covering themselves with masks, scarves or sunglasses.

The software could also see the end of public anonymity, sparking privacy concerns from one academic, who has labelled it ‘authoritarian‘.

This is very interesting for law enforcement and other organisations that want to capture criminals,” Amarjot Singh, a researcher at the University of Cambridge who worked on DIF.

The potential applications are beyond imagination.

Led by Mr Singh, the international team of scientists published their research on the pre-print server arXiv.

DFI uses a deep-learning AI neural network that the team trained by feeding it images of people using a variety of disguises to cover their faces.

The images had a mixture of complex and simple backgrounds to challenge the AI in a variety of scenarios.

The AI identifies people by measuring the distances and angles between 14 facial points – ten for the eyes, three for the lips, and one for the nose.

It uses these readings to estimate the hidden facial structure, and then compares this with learned images to unveil the person’s true identity.

In early tests, the algorithm correctly identified people whose faces were covered by hats or scarves 56 per cent of the time.

This accuracy dropped to 43 per cent when the faces were also wearing glasses. The work is still in its early stages, and the algorithm needs to be fed more data before it can be brought into the field.

Despite these hurdles, Mr Singh told Inverse: “We’re close to implementing it practically.”

The DFI team have called on other researchers to help develop the technology using their datasets of covered and uncovered faces.

The research, which has not yet been peer reviewed and is still awaiting publication, has sparked controversy after some raised concerns over privacy rights.

Dr. Zeynep Tufekci, a sociologist at the University of North Carolina, posted the research to Twitter, claiming that the AI is ‘authoritarian’.

He tweeted: ‘The authors claim the system works about half the time even when people wear glasses. And this is just the beginning; first paper.

And this is maybe the third or fourth most worrying ML paper I’ve seen recently re: AI and emergent authoritarianism. Historical crossroads.”

Yes, we can & should nitpick this and all papers but the trend is clear. Ever-increasing new capability that will serve authoritarians well.

The DFI team will present their research at the IEEE International Conference on Computer Vision Workshop in Venice, Italy, next month.

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Pass it on: New Scientist

Facebook Is Using AI To Make Language Translation 9 Times Faster


Artificially intelligent systems are only getting better, and they’re likely to appear in our computers and on our phones more and more often over the next few years.

Facebook has been using artificial intelligence and machine learning for various things like its M digital assistant but now the company is turning to AI for another purpose: translation.

Facebook’s research team has published a report on how artificial intelligence is a hefty nine times faster than traditional language translation software.

Not only that, but the researchers have revealed that the source code for the translation software is open-source, so anyone can get their hands on it to verify the results.

The report highlights the use of convolutional neural networks (CNN) as opposed to recurrent neural networks (RNN), which translate sentences one word at a time in a linear order.


The new architecture, however, can take words further down in the sentence into consideration during the translation process, which helps make the translation far more accurate.

This actually marks the first time a CNN has managed to outperform an RNN in language translation, and Facebook now hopes to expand it to to cover more languages.

“Language translation is important to Facebook’s mission of making the world more open and connected, enabling everyone to consume posts or videos in their preferred language all at the highest possible accuracy and speed,” said the company in a blog post.


Convolutional Neural Networks aren’t a totally new technology, but they haven’t really been applied to translation before.As a result of the new tech, Facebook can compute different aspects of a sentence at the same time, and as a

As a result of the new tech, Facebook can compute different aspects of a sentence at the same time, and as a result it can train its systems using a lot less computational power which in turn results in faster translation.

The system is also open source, meaning translation should get better across the web — not just in Facebook’s offerings.

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Pass it on: Popular Science