Daily Archives: June 29, 2017

The Curiosity Mars Rover is now smart enough to pick its own targets for exploration, according to a new study.

The secret to Curiosity's better brain was a software update sent from the ground in October 2015, called the Autonomous Exploration for Gathering Increased Science (AEGIS). This was the first time artificial intelligence had been tried on a remote probe, and the results have shown that similar AI techniques could be applied to future missions, according to the NASA scientists working on the project.

AEGIS allows the rover to be "trained" to identify rocks with certain characteristics that scientists on the ground want to investigate. This is valuable because Curiosity's human controllers can't be in direct contact with the rover all the time. Instead of waiting for instructions to "go there and sample that piece of rock," Curiosity can now look for targets even when it isn't in contact with its human controllers, according to a new study that describes Curiosity's use of the software. [Amazing Mars Rover Curiosity's Latest Photos]

"We can't be in constant contact with the rover Mars rotates and when [Curiosity is] on the far side we can't get in touch with it," Raymond Francis, lead system engineer for the deployment of AEGIS, told Space.com.

According to the study, once the AEGIS system was deployed, it was used 54 times between May 13, 2016, and April 7, 2017. Without intelligent targeting, Curiosity could be expected to hit a target the scientists were interested in about 24 percent of the time; with AEGIS, the rover managed 93 percent, according to the study.

Even when the rover is in contact, the signals from Earth to Mars take time to get there and back. In May 2016, Mars was the closest it had been to Earth in 11 years 46.8 million miles. A radio signal would take just over 4 minutes to get there and four more to get back. So if there is something planetary scientists want a closer look at, it can take a while to send the commands.

Idle time is often lost science time for the rover mission, and because sending a robot to Mars is expensive and difficult, it's not ideal. A few hours hanging around each day may not seem like much, but it adds up over the course of an entire mission. With AEGIS, the rover could drive to a location, choose targets for investigation and gather data while it waits for radio contact with Earth again. That means Earth-bound scientists are free to choose a new target once they re-establish contact with the rover.

For the study, the NASA team trained Curiosity, with the AEGIS software, to analyze bedrock in a feature called the Murray formation after each drive. The Murray formation is a rocky outcrop with characteristic bands of mudstone, possibly laid down by lakes of liquid water. One question the scientists wanted to answer was whether the chemical composition of the Murray formation changed over time, because that could reveal changes in the water chemistry, divulging more about the history of water on Mars.

This analysis of the Murray formation required taking many samples of the mudstone, but doing them would take time away from other experiments and observations. With AEGIS, Curiosity took care of these repetitive observations when it was out of touch with Earth, and researchers would not be using it for more advanced tasks. One could use AEGIS to train Curiosity to look for other types of rock, Francis said.

The AEGIS system works by using two of the rover's cameras, the Chemistry and Camera instrument (ChemCam) and the navigation cameras. The software uses images captured by the cameras, and tries to recognize edges of objects in the frame, and looks for edges that connect to create a "loop."

"If you find edges that close into a loop you've found an object and on Mars that's usually a rock," Francis said. AEGIS can also look at the relative brightness of the various objects in the frame (the navigation cameras don't have color vision). The combination of edges and brightness allows AEGIS to identify objects.

The science team will have criteria for what kinds of things count as interesting for example, brightly colored bedrock and the rover can then use the cameras to "choose" a target. The ChemCam can then use a powerful instrument called a laser spectrometer that uses light to find out what a target is made of.

There are limitations to AEGIS' abilities; for example, the rover sometimes identified a rock's shadow as part of the rock's outline. Even so, the software has proved a useful tool, the study said.

Francis notes that the autonomy will likely become a fixture for many future robotic missions.

"The farther you go in the solar system, the longer the light time delay, the more decisions need to be made on the spot," he said.

The study appears in the June 21 issue of the journal Science Robotics.

Follow us @Spacedotcom , Facebook and Google+ . Original article on Space.com .

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Curiosity Mars Rover is now using artificial intelligence to pick its own targets - Fox News

From Alexa and self-driving cars to job applicant screening processes, artificial intelligence is fast becoming the norm in business. But it also could start playing far bigger roles in security, helping law enforcement and other protective agents figure out who's up to no good. As Fredrick Kunkle of The Washington Post reports, there's now an AI-based kiosk designed to detect whether travelers are fibbing.

Designed by Aaron Elkins, assistant professor of the Fowler College of Business Administration at San Diego State University, the new AI lie detector goes by the name Automated Virtual Agent for Truth Assessments in Real Time, or AVATAR for short. Once you've scanned your ID or passport, the kiosk asks you a bunch of questions. The inquiries are a good mix of inquiries you could practice (e.g., when were you born) and questions that might throw you if you're faking it (e.g., describe what you did today). You can see some of the process in the video below:

If everything goes well, security personnel should let you go on your way. If the results suggest you're being dishonest, security personnel might detain you for questioning or a search.

As you answer questions from AVATAR, the system uses sensors to gather data your body gives off. More specifically, the system looks at factors like voice (tone, pronoun use, etc.), pupil dilation and eye movement, facial expression (e.g., engagement of muscles around the corners of the eyes and mouth in a Duchenne smile) and posture. The theory is that it takes less effort to tell the truth than to maintain a faade. You subconsciously reveal that effort through physical cues, many of which researchers are still studying and pinning down. The AI is a big step forward from traditional polygraphs, which aren't practical for general, large-scale screening, use more limited physiological data (e.g, heart rate) and generally aren't considered very reliable.

In theory, AVATAR could become a widely applied staple in local law enforcement agencies around the world, helping police sort out a variety of conflicts. But its main intent is for border security checkpoints and airports. These facilities are of concern in part because of the high traffic they receive. But they are also worry points because of the current worldwide focus on terrorism. Although these types of attacks can come from many different individuals or groups and can be domestic or foreign in nature, the increasing activity of the Islamic State of Iraq and Syria (ISIS) has been particularly alarming for leaders around the globe. Attacks have led U.S. President Donald Trump, for instance, to call for a controversial travel ban against travelers from six majority-Muslim countries. AVATAR might one day help screen out individuals associated with ISIS or similar groups.

Right now, AVATAR is still in its infant stages. It's only collecting research data at border crossings in Mexico and Romania. But even at this point, it's a beautiful demonstration of how science and technology can blend toward a practical social good.

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This Artificial Intelligence Kiosk Will Spot Liars at Airports, Keep You Safer - Inc.com

Faculty and staff from several schools at Carnegie Mellon University are joining forces in an effort to accelerate the science of Artificial Intelligence.

University leaders said they hope that by pulling together more than 100 faculty through the creation of CMU AI, it will maintain the universitys role as a leader in the field.

CMU School of Computer Sciencedean Andrew Moore said the confederation of faculty and students from various disciplines, which will allow the school to offer what he calls full stack education and research.

That means [the students] need to be able to hang out and work on projects in labs not just with the technology experts on specific parts of AI, like machine learning or computer vision, but they have seen examples of putting everything together, Moore said.

Moore said the university has been able to build great AI systems that combine technologies from several different disciplines. However, they have been dependent on individual faculty members and students with a special vision.

Were relying on the fact tat weve got a few smart faculty and students whove got the way to do this sitting in their head, Moore said. Its almost an art rather than a technology. By creating CMU AI, were going to turn this into a technology stack so we can educate eventually hundreds of thousands of people to be able to assemble these large robot systems.

The idea was born about a year ago when a group of potential students told him they were impressed by CMU but they wanted to learn about artificial intelligence, not just its parts.

Artificial Intelligence is slowly becoming a part of our every day lives, and Moore said the nation needs this type of confederation to lead the way. He said the mix of educators, researchers and commercial endeavors, such as Uber, in Pittsburgh puts the city in a unique position to be the worlds leader.

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New Artificial Intelligence Hub At CMU Aims To Make Pittsburgh A World Leader In AI - 90.5 WESA

A look at TurboPatents new RoboReview service. (TurboPatent Photo)

Seattle startup TurboPatent is releasing a pair of new products designed to improve the patent application process, with help from artificial intelligence.

TurboPatent, which raised $1.4 millionin funding earlier this year, focuses on corporations and law firms, automating taskslike formatting or document preparation, for example, freeing up people to work on more complex, high-value work. The service is designed to cut costs, save time and lead to more accurate patent documentation.

The new products are called RoboReview and RapidResponse. RoboReview uses AI and predictive analytics to automatically analyze and review draft patent applications. The company says this will reduce to seconds a process that can normally take several people multiple days to complete. RapidResponse helps speed upoffice actions,written correspondence between an applicant and patent examiner during the application process.

Like any procedure that involves people, the review process is subject to human error, said TurboPatent CEO James Billmaier. TurboPatent automates the most tedious and time-consuming parts of the process, which drastically cuts down on the likelihood of potential issues going unnoticed. That leaves humans to decide whether or not to submit a patent and if so, what alterations need to be made.

Formerly known as Patent Navigation, TurboPatent has an experienced team led by co-foundersBillmaier and Charles Mirho. Billmaier was previously CEO of Melodeo, a cloud-based media platform company that sold to HP in 2010. He also teamed up with Paul Allen in 1999 to launchhome-entertainment technology company Digeo, which was eventually sold in 2009 to ARRIS Group Inc.

Mirho, meanwhile, is a patent law veteran, having worked as a patent counsel at Intel and later as a managing partner of a patent law firm. He also has a computer science degree from Rutgers.

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TurboPatent aims to improve the patent process with new artificial ... - GeekWire

Machines capable of carrying out tasks normally reserved for humans will boost global GDP by as much as 14 percent by 2030, according to PwC.

In a report, the global auditing and consulting firm argued that the widespread adoption of artificial intelligence (AI) can contribute $15.7 million to the world economy over the next decade, the equivalent of the current combined output of China and India, as it would vastly increase productivity and spur shoppers to spend more. (See also: Artificial Intelligence.)

According to the firm's calculations, the bulk of these gains, $9.1 trillion, will be generated by consumption-side effects. Shoppers, driven to work by autonomous cars, are expected to use their extra time and resources to buy personalized and higher-quality goods. The U.S. is forecast to be a major beneficiary of this trend PwC reckons that consumption patterns triggered by AI will add $3.7 trillion to the North American economy. (See also: Self-Driving Vehicles Will Create 'Passenger Economy' Worth $7 Trillion: Study.)

China is predicted to be an even bigger beneficiary, particularly as its heavily dependent on manufacturing, an industry that is expected to receive a huge economic boost from the introduction of automated robotic workforces.

The mindset today is man versus machine, Anand Rao, an AI researcher at PwC in Boston, said following the release of the report, according to Bloomberg. What we see as the future is man and machine together can be better than the human.

One of the biggest controversies surrounding AI, aside from fears that robots might one day malfunction and turn on humans, is the risks they pose to jobs. While automated manufacturing processes might save companies plenty over the long-run, it is also true that this process could come at the expense of employees, potentially leaving billions of people out of work.

Some 42 percent of the $15.7 trillion that PwC claims AI can pump into the global economy is expected to be generated by automated machinery in the workplace. If this phenomenon leads to mass job losses, as many predict, the reports argument of stronger consumption patterns suddenly appears less convincing. (See also: Buffett Slams Wealth Inequality, Calls GOP Health Bill 'Relief for the Rich'.)

PwC thinks otherwise, arguing that new jobs will be created to coincide with the rising adoption of AI. The adoption of no-human-in-the-loop technologies will mean that some posts will inevitably become redundant, but others will be created by the shifts in productivity and consumer demand emanating from AI, and through the value chain of AI itself, said the report. In addition to new types of workers who will focus on thinking creatively about how AI can be developed and applied, a new set of personnel will be required to build, maintain, operate, and regulate these emerging technologies.

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Artificial Intelligence Will Add $15.7 Trillion to the Global Economy: PwC - Investopedia