|
Post by swamprat on Jun 8, 2018 20:41:18 GMT
Fred (the one with his brain out) is a humanoid robot built by UK firm, Engineered Arts, one of the world’s leading makers of such machines. Bio-mechanical robots such as Fred are used for entertainment, information, education and research. The robots use specially designed hardware, sensors and software to achieve smooth and lifelike movement.
Credit: Matt Cardy/Getty
We all love Westworld, but its main premise -- that we'll be able to build robots identical to human in the near future -- still seems impossibly far-fetched. That said, a company called Engineered Arts is definitely exploring the edges of the uncanny valley. It has built a number of life-sized, humanoid robots that look incredibly realistic and move smoothly, quietly and relatively naturally.
The company's robots have been sold for research, education and entertainment purposes. However, it recently unveiled its top-of-the line "Mesmer" series, realistic down to the pores and individual hairs. They're "skinned by the best in the TV and film business," Engineered Arts explained in the (Westworld-like) promotional video. (The model above, called "Fred" is being worked on by Engineered Arts' prosthetic expert Mike Humphrey.)
It developed "powerful, silent, high-torque motors" to drive Mesmer's body and head movements, and all the components were designed from scratch so that everything works together perfectly. By contrast, "other companies use a hodgepodge of bits from various vendors that often don't work well together," Engineered Arts claims. Each motor can be controlled independently, and what's more, the main parts (including motors, cameras, depth sensors, LIDAR and microphones) are internet connected devices.
That means that all the robots can be "controlled, monitored, reprogrammed and maintained remotely from anywhere in the world," said Engineered Arts. (Hopefully there's incredibly strong encryption, as they'd be an awfully tempting target for hackers.)
The company also developed browser-based software to control the robots' movements. It works much like the 3D software used to control CG or game characters, allowing for smooth, realistic motion. At the same time, the animation for one character can easily be transferred to another, letting your robots switch loops, if you will.
Finally, and most freakily, the robots can sense your proximity and face in order to maintain eye contact while they chat you up. Mesmer comes with the same telepresense software Engineered Arts has used on its earlier, non-realistic RoboThespian and SociBot models.
So how does it look? The facial animation is not bad, and thanks to the curved mechanical vertebrae, the head movements look pretty decent, too. When he speaks, however, Fred looks like he just had a shot of novocaine in his entire lower face. And the body movements, for the moment, seem limited to stiff gesticulations.
There's no word on the price for the Mesmer series, but the more basic RoboThespian models cost upwards of $79,000. The new bots show that when companies pay attention to facial realism, it's easy to overlook weird facial or body movements and other issues. It's a good start, but looking at the big picture, it's clear that our Westworld fantasies and fears are still a distant dream.
www.engadget.com/2018/05/22/mesmer-robot-engineered-arts-the-big-picture/
|
|
|
Post by HAL on Jun 8, 2018 21:28:20 GMT
|
|
|
Post by swamprat on Jan 1, 2019 17:08:34 GMT
Time for another headache... Times, they are achangin'. GPS, NGA, AI
What is knowledge?
What is meaning?
What is understanding?
What is intelligence?
What is learning?
What is thinking?
These questions excited Plato and Kant, Buddha and Descartes, perhaps out of intellectual or spiritual curiosity. Who’s to say? But the people asking them now are driven, quite literally, by practicalities. They have come to realize that we cannot ride in driverless cars or fly in pilotless plane-taxis, we cannot live in an autonomous, artificially intelligent environment without knowing a bit more exactly what knowledge is, in this brave new world. Without thinking about what thinking may be, for a machine.
Why does this matter to a GPS/GNSS/PNT readership? Because as positioning and navigation engage more deeply with artificial intelligence (AI) generally, and with autonomy in particular, these issues emerge as part of the environment that such solutions explore, and in which they must verify and validate themselves.
Second Wave
We are in the second wave of AI, according to Steven Rogers, senior scientist for sensor fusion at the Air Force Research Laboratory. In the first wave, 60s and 70s, large and complex algorithms, relatively low on data, drove new developments — but they hit real-world problems, hard. Since the mid-80s, we have been in the “classify” stage with relatively simpler programs generating and consuming lots of data. Intense statistical learning will eventually lead to the third wave of AI: Explain.
On a timeline yet to be determined, contextual adaptation will give rise to “explainable” AI, capable of answering unexpected queries. That is, it will have learned how to teach itself.
Some of this stuff gets pretty scary.
Most future knowledge will be machine-generated.
Let’s run through that one more time.
“Most future knowledge on Earth will come from machines extracting it from the environment,” said Rogers. “Machine generation of knowledge is key for autonomy.”
Here’s where the thought processes really started to levitate. “Current sense-making solutions are not keeping pace, not growing as knowledge is growing,” Rogers asserted. And he challenged us with the questions posed at the beginning of this column: in AI, the context we will use to explore much of the future, what is knowledge? What is meaning? And so on.
He gave us one of his answers: “Knowledge is what is used to generate the meaning of the observable for an autonomous system. Correspondingly, machine-generated knowledge is what is used to turn observables into machine-generated meaning.”
NGA official: Artificial intelligence is changing everything, ‘We need a different mentality’ by Sandra Erwin
NGA Deputy Director Justin Poole: “Relevance is now a matter of speed."
WASHINGTON — The U.S. military got its first big taste of artificial intelligence with Project Maven. An Air Force initiative, it began more than a year ago as an experiment using machine learning algorithms developed by Google to analyze full-motion video surveillance.
The project has received high praise within military circles for giving operators in the field instant access to the type of intelligence that typically would have taken a long time for geospatial data analysts to produce.
Project Maven has whetted the military’s appetite for artificial intelligence tools. And this is creating pressure on the National Geospatial-Intelligence Agency to jump on the AI bandwagon and start delivering Maven-like products and services.
“Relevance is now a matter of speed,” NGA Deputy Director Justin Poole told a C4ISRNET conference last week in Arlington, Va.
Data is flowing at unprecedented volumes from government and commercial sensors. There will be more constellations of remote sensing satellites and swarms of spy drones in the future piping in even more data. ‘We must adapt rapidly,” Poole said.
NGA’s answer is what the agency calls its “triple A” strategy: automation, augmentation, AI. “We intend to apply triple A by the end of this year to every image we ingest,” said Poole. It will be a massive undertaking. Just over the past year, NGA ingested more than 12 million images and generated more than 50 million indexed observations.
The agency has to step up the application of machine learning and advanced algorithms so it can provide faster support to forces in the field, Poole said. “We’re partnering with leading commercial vendors to produce next generation high resolution 3D models, 3D geospatial data, battlefield visualization,” said Poole. “As we expand from products to services, we have to push triple A. We have to transform how we interact with customers. We want to become a broker of diverse geospatial content.”
NGA also is modernizing its cloud architecture “to allow our analysts to live in the data,” Poole said. “We need a different mentality within the government. Algorithms can get stale within months if not weeks,” he insisted. “We need to rethink how we partner with industry and academia.”
Poole is overseeing the agency’s acquisition reforms. “We will work within the regulations we have, and we are retooling offices and using other transactions authorities.” OTA is a commercial-like contracting method used to move projects faster.
“How do we change the culture?” Poole asked. “We traditionally think about technology insertion as being done in a corner. I want to introduce technology into the workflow that analysts use today,” he said. “Analysts are more motivated when they can write algorithms.”
During a question-and-answer session, Poole was asked to comment on the controversy surrounding the military’s use of AI technology. Google employees have petitioned the company to end its participation in Project Maven and get out of the “business of war.”
Poole said NGA wants to avoid getting distracted by controversies. “I’ve seen things like this come and go in 27 years with the agency,” he said of the Maven backlash. “If we keep our eye on the ball and understand the importance of what we’re doing, I think we’ll come out ahead in the end.”
Whether it’s Google or any other partner, the Pentagon is determined to exploit the technology at a grander scale. Undersecretary of Defense for Research and Engineering Michael Griffin is taking on a Pentagon-wide effort to accelerate innovations in AI. Undersecretary of Defense for Intelligence Joseph Kernan has championed the use of AI in military operations. At an industry conference in Tampa, Fla., he said Project Maven has been “extraordinarily” useful in overseas conflicts.
spacenews.com/nga-official-artificial-intelligence-is-changing-everything-we-need-a-different-mentality/
|
|
|
Post by swamprat on Jan 1, 2019 17:13:03 GMT
NGA Investing in Big Data, Artificial Intelligence Technology By Yasmin Tadjdeh
The National Geospatial-Intelligence Agency is investing in machine learning technologies as it grapples with a deluge of data, said the agency’s deputy director May 10.
“As the commercial sector steadily fields new devices that enhance and connect our lives, the amount of data and types of data that we can use to drive analytic insight continues to grow,” said Justin Poole.
Poole — speaking at the 17th annual C4ISRNET Conference in Arlington, Virginia — noted that a recent study by Gartner found that by the end of the year, 8.4 billion devices will be connected to the internet, which is an increase of 30 percent from last year.
“It’s predicated that by 2025 these devices will generate over two zettabytes, or two trillion gigabytes of data, … [with] every one of them providing a … continuous stream of geospatial information about the users and their activities,” he said.
For the NGA — which focuses on the collection of location intelligence — that’s a game changer, he said.
Much of these new data streams are being driven by an explosive growth in small satellites and inexpensive drones in the commercial sector, he said. That demands that the agency adapt rapidly to a changing environment, he added.
“Everyone is a sensor, every point on the Earth is readily observed and commercial data is easily accessible by our friends and our foes alike,” he said. “It’s clear that relevance is a matter of speed. Those that can most quickly separate the threat from the noise, especially at machine speeds, will be the ones with the decision advantage in the battlefield.”
The NGA cannot hire enough analysts to meet this demand, and the agency needs to use the workforce it already has to develop new skills and tools to maximize the potential of these unique and nontraditional data sources, Poole said.
To that effect, the agency is investing in big data technology and is pursuing a strategy called Triple A, which stands for automation, augmentation and artificial intelligence, he said.
“NGA intends to apply Triple A to every image that we ingest by this end of this year,” he said while noting that the agency processed more than 12 million images in the past year. “NGA is positioning itself to be a community leader for things like computer vision, machine learning and advanced algorithms.”
Innovation must be approached in a timelier fashion, Poole noted. Technology cycles are dynamic, and algorithms can go stale after a few months, if not a few weeks, he said. A startup based in someone’s basement can go from concept to initial operating capability just as fast, he added.
“This level of refresh and decay demands that our government be in a position to constantly develop, which means that we need to rethink how we partner with industry and academia,” he said. “Our acquisition approach must be more responsive to mission needs.”
The agency is moving away from long development cycles based on static requirements to an iterative "sprint" process that lets it learn and adjust as it fields technology, he said. Additionally, the NGA plans to add more engineering rigor earlier in the acquisition cycle, he said.
For industry, this new approach will entail smaller contracts focused on mission-specific capabilities, he said. However, while they will be smaller procurements there will be more diverse opportunities for traditional and nontraditional companies, he added.
www.nationaldefensemagazine.org/articles/2018/5/11/nga-investing-in-big-data-artificial-intelligence-technology
Other GPS Systems in operation, being used to procure user data:
BeiDou Navigation Satellite System (BDS)
BeiDou, or BDS, is a regional GNSS owned and operated by the People's Republic of China. China is currently expanding the system to provide global coverage with 35 satellites by 2020. BDS was previously called Compass.
Galileo
Galileo is a global GNSS owned and operated by the European Union. The EU declared the start of Galileo Initial Services in 2016 and plans to complete the system of 24+ satellites by 2020. GLONASS GLONASS (Globalnaya Navigazionnaya Sputnikovaya Sistema, or Global Navigation Satellite System) is a global GNSS owned and operated by the Russian Federation. The fully operational system consists of 24+ satellites.
Indian Regional Navigation Satellite System (IRNSS) / Navigation Indian Constellation (NavIC)
IRNSS is a regional GNSS owned and operated by the Government of India. IRNSS is an autonomous system designed to cover the Indian region and 1500 km around the Indian mainland. The system consists of 7 satellites and should be declared operational in 2018. In 2016, India renamed IRNSS as the Navigation Indian Constellation (NavIC, meaning "sailor" or "navigator")
Quasi-Zenith Satellite System (QZSS)
QZSS is a regional GNSS owned by the Government of Japan and operated by QZS System Service Inc. (QSS). QZSS complements GPS to improve coverage in East Asia and Oceania. Japan plans to have an operational constellation of 4 satellites by 2018 and expand it to 7 satellites for autonomous capability by 2023.
And.....................What will the NEXT 30 years bring?
|
|
|
Post by swamprat on Jan 28, 2019 20:04:48 GMT
Look out! Crash Up Ahead!
|
|
|
Post by swamprat on Feb 5, 2019 16:52:22 GMT
Engineers harvest heart's energy to power life-saving devices Harnessing the heartbeat to charge batteries
Date: February 4, 2019
Source: Dartmouth College
Summary:
The heart's motion is so powerful that it can recharge life-saving devices, according to new research. Using a dime-sized invention, the heart's energy can be harnessed to power implantable devices, according to the study. Creating an energy source within the body could save millions of people who rely on pacemakers and other implantable devices from having to undergo surgery to replace batteries.
Dartmouth engineers develop dime-sized device to capture and convert the kinetic energy of the heart into electricity to power a wide-range of implantable devices. Credit: Patricio R. Sarzosa, Thayer School of Engineering
The heart's motion is so powerful that it can recharge devices that save our lives, according to new research from Dartmouth College.
Using a dime-sized invention developed by engineers at the Thayer School of Engineering at Dartmouth, the kinetic energy of the heart can be converted into electricity to power a wide-range of implantable devices, according to the study funded by the National Institutes of Health.
Millions of people rely on pacemakers, defibrillators and other live-saving implantable devices powered by batteries that need to be replaced every five to 10 years. Those replacements require surgery which can be costly and create the possibility of complications and infections.
"We're trying to solve the ultimate problem for any implantable biomedical device," says Dartmouth engineering professor John X.J. Zhang, a lead researcher on the study his team completed alongside clinicians at the University of Texas in San Antonio. "How do you create an effective energy source so the device will do its job during the entire life span of the patient, without the need for surgery to replace the battery?"
"Of equal importance is that the device not interfere with the body's function," adds Dartmouth research associate Lin Dong, first author on the paper. "We knew it had to be biocompatible, lightweight, flexible, and low profile, so it not only fits into the current pacemaker structure but is also scalable for future multi-functionality."
The team's work proposes modifying pacemakers to harness the kinetic energy of the lead wire that's attached to the heart, converting it into electricity to continually charge the batteries. The added material is a type of thin polymer piezoelectric film called "PVDF" and, when designed with porous structures -- either an array of small buckle beams or a flexible cantilever -- it can convert even small mechanical motion to electricity. An added benefit: the same modules could potentially be used as sensors to enable data collection for real-time monitoring of patients.
The results of the three-year study, completed by Dartmouth's engineering researchers along with clinicians at UT Health San Antonio, were just published in the cover story for Advanced Materials Technologies.
The two remaining years of NIH funding plus time to finish the pre-clinical process and obtain regulatory approval puts a self-charging pacemaker approximately five years out from commercialization, according to Zhang.
"We've completed the first round of animal studies with great results which will be published soon," says Zhang. "There is already a lot of expressed interest from the major medical technology companies, and Andrew Closson, one of the study's authors working with Lin Dong and an engineering PhD Innovation Program student at Dartmouth, is learning the business and technology transfer skills to be a cohort in moving forward with the entrepreneurial phase of this effort."
Story Source:
Materials provided by Dartmouth College. Note: Content may be edited for style and length.
Journal Reference:
1. Lin Dong, Xiaomin Han, Zhe Xu, Andrew B. Closson, Yin Liu, Chunsheng Wen, Xi Liu, Gladys Patricia Escobar, Meagan Oglesby, Marc Feldman, Zi Chen, John X. J. Zhang. Energy Harvesting: Flexible Porous Piezoelectric Cantilever on a Pacemaker Lead for Compact Energy Harvesting (Adv. Mater. Technol. 1/2019). Advanced Materials Technologies, 2019; 4 (1): 1970002 DOI: 10.1002/admt.201970002
|
|
|
Post by swamprat on Feb 11, 2019 16:42:10 GMT
Sigh... It's gonna get worse, folks. All ready, whenever I go shopping, my phone asks me, "How was Walmart?", or, "How was Winn-Dixie?" Just think of all the information your car is going to know! Self-driving cars and geospatial data: Who holds the keys? Unlocking geospatial data is key to redefining spaces in our society
Date: February 5, 2019
Source: Dartmouth College
Summary:
As self-driving cars continue to develop, there will be plenty of data amassed through cars' navigational technologies. Questions regarding privacy, ownership, cybersecurity and public safety arise, as heavily guarded mapping data is collected and leveraged by companies. The geospatial data can be used to draw new maps identifying the spaces where we live and travel; yet, is currently housed in technological and corporate black boxes. These black boxes require greater transparency, researchers urge.
As self-driving cars continue to develop, there will be plenty of data amassed through cars' navigational technologies. Questions regarding privacy, ownership, cybersecurity and public safety arise, as heavily guarded mapping data is collected and leveraged by companies. The geospatial data can be used to draw new maps identifying the spaces where we live and travel. That information is currently housed in technological and corporate black boxes. Given the social relevance and impacts of such information, these black boxes require greater transparency, according to a Dartmouth study posted in Cartographic Perspectives.
As autonomous cars strive to make sense of the world around them, they collect massive amounts of data, including traffic and congestion patterns, where pedestrians cross the street, which houses and businesses have Wi-Fi, and other details, which could be monetized. While companies may have intellectual property and other economic interests in protecting geospatial data, local governments, private citizens and other actors also have a vested interest in using that data to inform decisions on managing traffic, urban planning, allocating public funds and other projects, all of which may be of public interest.
"Self-driving cars have the potential to transform our transportation network and society at large. This carries enormous consequences given that the data and technology are likely to fundamentally reshape the way our cities and communities operate," explains study author, Luis F. Alvarez León, an assistant professor of geography at Dartmouth.
"Right now, the geospatial data obtained by a self-driving car exists in technological and corporate black boxes. We don't know who can see the data, appropriate it or profit from it. With insufficient government regulation of data from self-driving cars, this raises significant concerns regarding privacy, security and public safety," Alvarez León adds.
The author discusses how legislation, open source design and hacking are avenues that can be leveraged to help open the black box, enabling consumers and the government to gain access to this corporate collected information. While each of these three approaches has potential risks and rewards, they can help frame the public debate on the ownership and use of geospatial data from self-driving cars.
• Autonomous cars rely on computerized systems to run. User access to this data proves difficult when they are locked in closed networks controlled by automobile manufacturers. The study looks at how legislation could help make this data more accessible. Car manufacturers typically consider themselves the sole arbiters of the information pertaining to their vehicles, claiming that they "own the data" but legislation has provided pushback and the author cites examples, such as debates around the right to repair.
• When autonomous cars, including their components, assembly, operation and data, are designed through an open source framework, data might be more easily available to the public and inform greater understanding about its potential uses and implications, the author suggests.
Companies such as Udacity, an online education company, offers a Self-driving Car Engineer Nanodegree program in which students learn, develop and refine code for autonomous systems. Although there may be economic and intellectual property tradeoffs for the manufacturers, open source design plays an important role in allowing for greater transparency, according to the study.
• In addition to legislation and open source design, hacking is both a systemic risk for autonomous vehicles and an approach that has been deployed to make car data and automated systems more transparent while holding self-driving car companies more accountable. In 2013 and 2015, two security experts remotely hacked into a 2014 Jeep Cherokee, and a Toyota Prius and Ford Escape, respectively, demonstrating the security flaws in vehicles that were not autonomous. Security vulnerabilities are likely to run much deeper with fully autonomous vehicles.
Precisely because hacking is a generalized risk for autonomous vehicles, certain instances of hacking in the context of research and advocacy have shown the importance of building secure systems. Recent security breaches with Equifax and Facebook illustrate the many security risks relating to consumers' digital information. "If we're going to adopt self-driving cars, then we should really make absolutely sure that they are as secure as they can be. This requires input from parties outside of the corporations who are building those very systems, such as government, advocacy groups and civil society at large." says Alvarez León.
In the U.S., Arizona, California and Michigan are currently some of the most hospitable states for self-driving vehicles, serving as testing areas for companies such as Waymo, which started as Google's Self-Driving Car Project. While there are local regulatory battles, and often pushback from citizens and advocacy groups, other states may open their doors to this new mode of transportation in the future. Two weeks ago, Waymo announced that it will be building a manufacturing facility in southeast Michigan, as it looks to grow its fleet. As the study points out, oversight of the self-driving car industry cannot be left to the manufacturers themselves. It is up to the public and government to help define how this new technology and subsequent mapping of our communities will affect our society.
Story Source:
Materials provided by Dartmouth College. Note: Content may be edited for style and length.
www.sciencedaily.com/releases/2019/02/190205151008.htm
|
|
|
Post by HAL on Feb 11, 2019 22:24:38 GMT
Off Topic.
Swamp, You got any of those Burmese pythons in your neck of the swamp ?
HAL.
|
|
|
Post by swamprat on Feb 12, 2019 1:48:16 GMT
I've never seen any, Hal. I think they're down in the Everglades. We have Diamond Back Rattlers and Cottonmouth Moccasins.
Swamp
|
|
|
Post by HAL on Feb 12, 2019 20:43:56 GMT
Just remembered why I never wanted to go to Florida.
HAL;)
|
|
|
Post by moksha on Feb 13, 2019 11:57:42 GMT
Just remembered why I never wanted to go to Florida. HAL;) HAL, but you will miss out on sum fantastic wild life.
|
|
|
Post by HAL on Feb 13, 2019 20:42:22 GMT
|
|
|
Post by swamprat on Mar 5, 2019 16:48:13 GMT
And so it begins..... Human beings are EVIL!The first look at how hacked self-driving cars would affect New York City traffic Date: March 4, 2019
Source: American Physical Society
Summary:
Researchers have analyzed the real-time effect of a large-scale hack on automobiles in a major urban environment. Using percolation theory, they analyzed how a large, disseminated hack on automobiles would affect traffic flow in New York City, and they found that it could create citywide gridlock. However, based on these findings the team also developed a risk-mitigation strategy to prevent mass urban disruption.
Clusters of connected roads. Same color denotes roads that are part of the same cluster, i.e., all connected. When there are no hacked vehicles, all roads are connected (yellow). But as there are more hacked vehicles, more colors show up, and each cluster is inaccessible from the other. When somewhere between 10-20% of vehicles at rush hour hacked, the size of the largest cluster dramatically reduces. We call this threshold (~10-15 hacked vehicles/km/lane) the point of city fragmentation. Essentially half the city is inaccessible from the rest above this threshold. Credit: Skanda Vivek/ Georgia Tech
As automated cars become more commonplace, it is increasingly likely that internet-connected vehicles could be simultaneously disabled. Currently, regulators tend to focus on preventing individual incidents, like the pedestrian who was struck and killed by a self-driving Uber in Arizona last year. However, they fall short of addressing the effects of a large-scale hack in an urban setting.
This week at the 2019 American Physical Society March Meeting in Boston, Skanda Vivek will present his research on the cyber-physical risks of hacked internet-connected vehicles. He will also participate in a press conference describing the work. Information for logging on to watch and ask questions remotely is included at the end of this news release.
Vivek and his team found that even a small-scale hack, affecting only 10 percent of vehicles in Manhattan, could cause citywide gridlock and hinder emergency services. Based on these findings the team also developed a risk-mitigation strategy to prevent mass urban disruption from a few compromised vehicles.
Vivek, a postdoctoral researcher in the Peter Yunker lab at the Georgia Institute of Technology, used agent-based simulations to investigate how hacks could impact traffic flow in New York. He and his team, including Yunker, graduate student David Yanni and Jesse Silverberg, founder of Multiscale Systems Inc., ultimately discovered that by using percolation theory, a mathematical approach based on the statistical analysis of networks, they could quantify how these scenarios would play out in New York City in real time.
Moreover, their analysis helped the team develop a risk-mitigation strategy: using multiple networks for connected vehicles to decrease the number of cars that could be compromised in a single intrusion. "If no more than, say, 5 percent of connected vehicles were compartmentalized to the same network or utilized the same network protocols, the chance of citywide fragmentation would be low," Vivek said.
"Therefore, a hacker with the intention of causing large-scale disruption faced with this compartmentalized multi-network architecture would be required to execute multiple simultaneous intrusions, which increases the difficulty of such an attack and makes it less likely to occur."
Stressing the urgency of this issue, Vivek commented that "compromised vehicles are unlike compromised data. Collisions caused by compromised vehicles present physical danger to the vehicle's occupants, and these disturbances would potentially have broad implications for overall traffic flow." Although there's been public scrutiny on individual collisions, this work is needed because the "likely impacts of a large-scale hack on traffic flow have yet to be quantified," Vivek said.
Speaking to the inevitability of more autonomous systems on the road, "Connected cars are the future," Vivek said. "They hold tremendous potential for positive impact economically, environmentally, and, for former drivers no longer frustrated by congested commutes, psychologically. Our work is not in opposition to the future of connected cars. Rather, the novelty of our work lies in identifying and quantifying the underlying cyber-physical risks when multiple connected vehicles are compromised. By shining a light on these technologies at an early stage, we hope we can help prevent worst-case-scenarios."
Story Source: Materials provided by American Physical Society. Note: Content may be edited for style and length.
www.sciencedaily.com/releases/2019/03/190304121519.htm
|
|
|
Post by HAL on Mar 6, 2019 22:39:18 GMT
Ive said all along that it won't work. But do they listen; Oh no. Just silly old HAL doom mongering again. HAL
|
|
|
Post by swamprat on Mar 9, 2019 16:41:12 GMT
Listening to quantum radio Date: March 8, 2019 Source: Delft University of Technology
Summary:
Researchers have created a quantum circuit that enables them to listen to the weakest radio signal allowed by quantum mechanics. This new quantum circuit opens the door to possible future applications in areas such as radio astronomy and medicine (MRI). It also enables researchers to do experiments that can shed light on the interplay between quantum mechanics and gravity.
This quantum chip (1x1 cm big) allows the researchers to listen to the smallest radio signal allowed by quantum mechanics. Credit: TU Delft
Researchers at Delft University of Technology have created a quantum circuit that enables them to listen to the weakest radio signal allowed by quantum mechanics. This new quantum circuit opens the door to possible future applications in areas such as radio astronomy and medicine (MRI). It also enables researchers to do experiments that can shed light on the interplay between quantum mechanics and gravity.
We have all been annoyed by weak radio signals at some point in our lives: our favourite song in the car turning to noise, being too far away from our wifi router to check our email. Our usual solution is to make the signal bigger, for instance by picking a different radio station or by moving to the other side of the living room. What if, however, we could just listen more carefully?
Weak radio signals are not just a challenge for people trying to find their favourite radio station, but also for magnetic resonance imaging (MRI) scanners at hospitals, as well as for the telescopes scientists use to peer into space.
In a quantum 'leap' in radio frequency detection, researchers in the group of Prof. Gary Steele in Delft demonstrated the detection of photons or quanta of energy, the weakest signals allowed by the theory of quantum mechanics.
Quantum chunks
One of the strange predictions of quantum mechanics is that energy comes in tiny little chunks called 'quanta'. What does this mean? "Say I am pushing a kid on a swing," lead researcher Mario Gely said. "In the classical theory of physics, if I want the kid to go a little bit faster I can give them a small push, giving them more speed and more energy. Quantum mechanics says something different: I can only increase the kid's energy one 'quantum step' at a time. Pushing by half of that amount is not possible."
For a kid on a swing these 'quantum steps' are so tiny that they are too small to notice. Until recently, the same was true for radio waves. However, the research team in Delft developed a circuit that can actually detect these chunks of energy in radio frequency signals, opening up the potential for sensing radio waves at the quantum level.
From quantum radio to quantum gravity?
Beyond applications in quantum sensing, the group in Delft is interested in taking quantum mechanics to the next level: mass. While the theory of quantum electromagnetism was developed nearly 100 years ago, physicists are still puzzled today on how to fit gravity into quantum mechanics.
"Using our quantum radio, we want to try to listen to and control the quantum vibrations of heavy objects, and explore experimentally what happens when you mix quantum mechanics and gravity," Gely said. "Such experiments are hard, but if successful we would be able to test if we can make a quantum superposition of space-time itself, a new concept that would test our understanding of both quantum mechanics and general relativity."
Story Source:
Materials provided by Delft University of Technology. Note: Content may be edited for style and length.
Journal Reference:
Mario F. Gely, Marios Kounalakis, Christian Dickel, Jacob Dalle, Rémy Vatré, Brian Baker, Mark D. Jenkins, Gary A. Steele. Observation and stabilization of photonic Fock states in a hot radio-frequency resonator. Science, 2019; 363 (6431): 1072 DOI: 10.1126/science.aaw3101
www.sciencedaily.com/releases/2019/03/190308102137.htm
|
|