New Technique Allows for Better Brain-Controlled Prostheses

A new technique that corrects brain readings to allow paralysed people to use a thought-controlled cursor more accurately has been developed by a team led by an Indian-origin researcher.

An interdisciplinary team led by Stanford University electrical engineer Krishna Shenoy has developed a technique to make brain-controlled prostheses more precise.

In essence the prostheses analyse the neuron sample and make dozens of corrective adjustments to the estimate of the brain's electrical pattern - all in the blink of an eye.

Shenoy's team tested a brain-controlled cursor meant to operate a virtual keyboard. The system is intended for people with paralysis and amyotrophic lateral sclerosis (ALS), also called Lou Gehrig's disease.

The thought-controlled keypad would allow a person with paralysis or ALS to run an electronic wheelchair and use a computer or tablet.

"Brain-controlled prostheses will lead to a substantial improvement in quality of life," Shenoy said.

The new corrective technique is based on a recently discovered understanding of how monkeys naturally perform arm movements.

The researchers studied animals that were normal in every way. The monkeys used their arms, hands and fingers to reach for targets presented on a video screen.

What the researchers sought to learn through hundreds of experiments was what the electrical patterns from the 100- to 200-neuron sample looked like during a normal reach.

In short, they came to understand the "brain dynamics" underlying reaching arm movements.

In their current experiments, Shenoy's team distilled their understanding of brain dynamics into an algorithm that could analyse the measured electrical signals that their prosthetic device obtained from the sampled neurons.

The algorithm tweaked these measured signals so that the sample's dynamics were more like the baseline brain dynamics. The goal was to make the thought-controlled prosthetic more precise.

To test this algorithm the researchers trained two monkeys to choose targets on a simplified keypad. The keypad consisted of several rows and columns of blank circles.

When a light flashed on a given circle the monkeys were trained to reach for that circle with their arms.

To set a performance baseline the researchers measured how many targets the monkeys could tap with their fingers in 30 seconds. The monkeys averaged 29 correct finger taps in 30 seconds.

The real experiment only scored virtual taps that came from the monkeys' brain-controlled cursor. Although the monkey may still have moved his fingers, the researchers only counted a hit when the brain-controlled cursor, corrected by the algorithm, sent the virtual cursor to the target.

The prosthetic scored 26 thought-taps in 30 seconds, about 90 percent as quickly as a monkey's finger.

The research was published in the journal Nature Communications.

The new technology set to revolutionise crime fighting

Lateline takes a look at the new 3D technology set to be introduced to Australia which could re-open cold cases and revolutionise court cases.

Transcript

EMMA ALBERICI, PRESENTER: When police charged a man over a series of Family Court-related bombings and murders yesterday that were three decades old, they made it clear new technology had been key in their cold case investigation. In that case, the DNA was the key. Now there's a new case-solving technology that can take police or a jury on a virtual tour of any location where a crime's been committed. Experts use laser scanning to recreate the scene. They can even analyse blood spatters and weapons. Already the Lindt Cafe in Sydney, scene of last year's fatal siege, has been reconstructed in 3D. That evidence is expected to be critical in the current inquest. Lateline's Nikki Tugwell reports. 

PAUL GLIM, FORENSIC ID SERVICES COMMANDER: The sky is the limit into the future when we find out, you know, in three to five years what we will be able to do with this.

SCOTT WEBER, NSW POLICE ASSOC. PRESIDENT: This is what police officers need to deal with crime and terrorism in the 21st Century.

ON-SCREEN TEXT: At a mock crime scene, the NSW police forensic unit explains how 3D laser scanning technology is improving their ability to solve crime.

DOMENIC RANERI, CRIME SCENE OFFICER: What we're leaning towards is a system whereby we can capture a scene in 3D and we can conduct these analyses in space rather than having a practitioner at the crime scene manually with a piece of string, sticking it around the scene. The latest sweeps out at 270 degrees, which means that it's capturing everything except for a very small area immediately below the scanner. Each scan takes about three-and-a-half minutes, maybe five including the colour and photography. We can move through the crime scene taking these scans and overlaying them with photography to create a colour photorealistic rendering of the environment. So where we might need additional detail or resolution, we can use a different type of scanner. So this is a hand-held scanner that actually scans to about a metre away, but captures a much high resolution as well as full colour on the fly. So if we had a scene like this where we wanted to capture, say, that blood pattern, we hook that scanner up to a tablet. And because you can see about a metre away in much more detail, we can start to capture that entire area. So what you've done there is you've applied a photograph of the blood spatter onto the 3D data, which then corrects for the lens distortion and brings it in true to scale and accurate. So we can then take the laser scan data out and just look at that blood spatter. So, then we can go in and look at the blood spatter in much higher detail than we could capture before. And from that point, you can then go on to measure the droplets and perform an analysis of the trajectory. So we can then go back out and look at it in context of the crime scene. And then we can look at where those points of origin might have been. And then an expert can tell us a number of different pieces of information about that, such as, hypothetically, the position of the mallets when the strikes occurred. So the real advantage here is that you can visualise this very 3D data, this 3D evidence within the 3D space and in the context of the original crime scene, which has never been able to be done before.

ON-SCREEN TEXT: The 3D laser scanner is being used in conjunction with CCTV vision to identify and eliminate suspects.

ARNOLD JANSEN, FORENSIC IMAGING COMMANDER: It can be used in a number of ways. We've used it recently to work out the location of a CCTV camera and then show the exact point of view from that camera and we can allow for factors such as the distortion of a lens and that can be very useful when we're comparing a suspect to what's captured on the CCTV image. It's an extremely accurate tool, so from that you can get a very precise measurement of heights of objects and people.

ON-SCREEN TEXT: The technology is also being used to reopen cold cases.

NIKKI TUGWELL, REPORTER: Has it proved beneficial so far with some of those historical cases?

DOMENIC RANERI: We've used it in a number of unsolved homicides and so far we've been able to add a considerable amount of value to those.

PAUL GLIM: There's one circumstances whereby a crime scene I guess that was recorded back in pre-1990. Police have been able to go back to a scene, use the measurements and the forensic examination, the details that were taken at that time and they have been able to recreate, I guess provide a contemporary version of that scene, provided that the building is still as it was at that point in time.

ON-SCREEN TEXT: At the CSIRO in Brisbane, Thomas Lowe is developing aerial and unmanned 3D scanners.

THOMAS LOWE, RESEARCH ENGINEER, CSIRO: We can move this around and not only map what is below us, but you can also map what is above you with this system. It's sort of a multi-pronged approach. In the one hand, we're developing it for unmanned aerial vehicles for aerial mapping of areas. We're also making use of it in real-time, not only for autonomous navigation of aerial vehicles, but also to give you a three-dimensional map as you move around a building. At the same time as that, we're also looking at more accurate and longer range lasers.

ON-SCREEN TEXT: Virtual reality goggles may soon be used to verify witness accounts.

DOMENIC RANERI: One of the things that's very important with this sort of 3D data is actually visualising it. And one of the newer technologies includes virtual reality headsets. So this is a device that's experimental which we're investigating and looking at how we can actually use this to visualise the 3D data that we're capturing. So this is a device that gets strapped onto the user's head and actually immerses you completely in the 3D environment. So you have a true sense of space, a true sense of scale and the ability to look around the scene completely freely and feel immersed in that environment. Our investigators in their offices can move through the scenes and view it as they like with a witness beside them and actually exclude or validate a witness's testimony based on that.

ON-SCREEN TEXT: 3D printers connect to the scanners and replicate evidence used in court.

DOMENIC RANERI: We can take, say, a scan of that mallet on the floor and then put it straight into our 3D printer and produce a replica of it. For cases where there might be complex evidence that needs to be looked at in a very tangible way, some types of evidence can't actually be handled directly by a jury. So we might take that scan data and then 3D print a model of it. So the 3D printer uses plastic to build an object in 3D space from the scan and from a 3D model. So we got this technology on the case of the 3D printer gun a couple of years ago where there was the belief that 3D printers might potentially be used to manufacture firearms.

ON-SCREEN TEXT: All cases in Australia using this technology are still before the courts.

DOMENIC RANERI: We actually get a written report certifying its accuracy at every point that it will count. The hand-held scanner has a certified accuracy as well to about 0.1 of a millimetre. So we're starting to see this sort of evidence reaching our courts and going through the process of admission into evidence.

SCOTT WEBER: It can actually bring the court, it can bring police and the community can highlight what actually occurred in a 3D representation. And we'll be seeing that over the coming months with the Coroner's matter in regards to the Lindt Cafe - where the people were, where the projectory - the projectiles, where the incidents, looking at explosions, looking at ballistics. All that forensic evidence is so vital.

ON-SCREEN TEXT: Police want to use the laser scanners to store 3D imagery of possible terror targets.

SCOTT WEBER: What we actually want is the 3D laser scanners to do some preventative stuff. So that's making sure that we actually scan and have models of all the critical infrastructure. It means that police officers have that diagram, that we can go through training scenarios and be better prepared if a incident does occur.

DOMENIC RANERI: The technology's very dynamic and it's rapidly evolving. There's lots of different devices, different technology out there and we're constantly keeping an eye on everything that's out there and evaluating it and looking at how we can actually use it in the context of our work.

storage technology 1,000x faster than current SSDs

Intel, Micron 

debut 3D XPoint storage technology 1,000x faster than current SSDs

Pronounced "cross-point", this is a new class of memory that can be used both as RAM and storage.

• 
  
• 
  
• 
  
• 
  
• 
  
• 
  

The new 3D XPoint memory technology will change the way we think about storage.

Intel and Micron today unveiled their all-new memory technology called 3D XPoint (pronounced "cross-point"). This is a new class of memory that can be used both as system memory as well as nonvolatile storage. In other words, 3D XPoint can be used to replace both a computer's RAM and its solid-state drive (SSD).

The companies claim that 3D XPoint is a major breakthrough in memory process technology, the first new memory category since the introduction of NAND flash in 1989. It's said to be extremely fast and durable, up to 1,000 times faster (both in read and write speeds), and it will have higher endurance than existing NAND Flash memory currently being used in SSDs. What's more, it also has as much as 10 times greater density, leading to much more storage capacity in the same physical space, while remaining as energy efficient and affordable as existing NAND flash memory.

According to Intel Vice President Rob Crooke, 3D XPoint will initially use PCI Express (PCIe) as its means of connecting to an existing computer, as PCIe currently has the the fastest bus speed of any peripheral interface. However, since PCIe is still not capable of handling the potential speed of 3D XPoint, in the future new ways will be developed to mount it, which will likely require entirely new motherboard architecture.

Clearly, with its ultrahigh performance, 3D XPoint technology will enhance the PC experience tremendously, especially in gaming, as large amounts of data can be loaded into the memory more quickly. On top of that, any applications that require low-latency storage will also benefit from 3D XPoint.

Intel says 3D XPoint results from the company's years of research and development, overcoming many hurdles including the chance that it would not be successful. 3D XPoint stores data in a totally different manner from the means used by existing NAND. It uses the property change of the memory cell itself, instead of storing the cell in a capacitor in the traditional way.

In terms of technology, 3D XPoint memory includes the following characteristics:

• Cross-point array structure: Perpendicular conductors connect 128 billion densely packed memory cells. Each memory cell stores a single bit of data. This compact structure results in high performance as well as high-density bits.
• Stackable: In addition to its tight cross-point array structure, memory cells are stacked in multiple layers. The initial technology stores 128 gigabits per die across two memory layers. Future generations of this technology may increase the number of memory layers, in addition to traditional lithographic pitch scaling, thus further improving system capacities.
• Selector: Memory cells are accessed and written or read by varying the amount of voltage sent to each selector. This eliminates the need for transistors, increasing capacity while reducing cost.
• Fast-switching cell: With its small cell size, fast-switching selector, low-latency cross-point array and fast-write algorithm, the cell is able to switch states faster than any existing nonvolatile memory technology.

3D XPoint technology is now in production and will be sampled later this year with select customers. Intel and Micron are developing individual products based on the technology that are forecast to be available sometime next year.

Google now uses an artificial neural network

Google now uses an artificial neural network to fight spam, debuts Gmail Postmaster Tools to cut false positives

Google today announced it is now using the same artificial intelligence developed for Google Search and Google Now to fight spam. This is on top of the machine learning the company already uses to train Gmail’s filters (every time you click the “Report spam” and “Not spam” buttons, you’re teaching Gmail what does and doesn’t matter).

Gmail’s spam filter now uses an artificial neural network to detect and block “the especially sneaky spam.” That means you should now be less likely to see messages in your inbox that are meant to pass for wanted email.

The spam filter is also now better at recognizing individual preferences. Not everyone likes the same repetitive emails, whether that’s daily jokes, weekly newsletters, monthly reminders, or just notifications from some random service, and Gmail needs to adjust accordingly.

Finally, Gmail’s spam filter can now root out email impersonation. New machine learning signals help the service figure out whether a message actually came from its sender, which at least in theory should reduce the effectiveness of phishing scams.

At the same time, the company today launched Gmail Postmaster Tools, which let companies minimize how many of their important emails get put into Gmail’s spam folder. The goal is to reduce the number of times users have to go looking in their spam folder for that vital message.

Google says that less than 0.1 percent of email in the average Gmail inbox is spam. Meanwhile, the amount of wanted mail landing in the spam folder is even lower, at under 0.05 percent.

Still, Google wants to do better. As the Gmail team puts it, the goal is to give users “The mail you want, not the spam you don’t.” Of course, that’s a very fine line to dance on: You may not want to see the same company email that I do.

As such, instead of simply whitelisting emails from companies, Google is supporting the senders of wanted email, like monthly statements from banks and ticket receipts from airlines. Gmail Postmaster Tools lets “qualified high-volume senders” analyze their email, including data on delivery errors, spam reports, and reputation.

In this way, Google is letting companies diagnose any hiccups that might be inadvertently making Gmail route their emails to your spam folder. The company also offers best practices for bulk email senders, so if you send the same type of email hundreds, thousands, or even millions of times per day, you’ll want to check this out.

MUST READ:The Artificial Intelligence(AI) AK-47

The Artificial Intelligence AK-47

“The endpoint of this technological trajectory is obvious: autonomous weapons will become the Kalashnikovs of tomorrow. The key question for humanity today is whether to start a global AI arms race or to prevent it from starting.”

– Autonomous Weapons: An Open Letter from AI & Robotics Researchers

The Kalashnikov aka the AK-47 is the design classic we don’t talk about that much. It’s the mechanical instrument of murder that has outlived every other ‘gadget’ of its generation. Those who do bring it up as an incredible and awful achievement usually do so to be polemical, but it’s true.

Elon Musk, Professor Stephen Hawking and the 1,000 other AI researchers who signed today’s warning about autonomous weapons are right – grafting AI onto the tools of warfare will produce the AK-47 of the future, an endlessly replicable, increasingly cheaper means of murder. And somewhere out there, today’s equivalent of Mikhail Kalashnikov is already working on it.

                                  Type 2 AK-47, the first machined receiver 

Experiments with recurrent neural networks and other AI structures are already throwing up incredible results. Companies including Google andFacebook are pumping huge amounts of resources into the research.  Intelligence agencies and the military are doing the same. Take it another step and it’s not inconceivable that outright bad actors are exploring those ideas too.

Phillip Killicoat in a working paper for the World Bank [pdf link], published in 2007, estimated that of 500 million firearms worldwide in 2004, approximately 100 million were descendants of Kalashnikov’s designs, three-quarters of those being AK-47s. The first easily replicable AI weapon will spread just as widely and be even more devastating.

The AK-47’s strength was born from constraints. Kalashnikov designed a weapon that could be mass-produced using the production methods available to the war-weary Soviet Union of the late-40s.

The weapon’s design – generous clearances between moving parts, a tapered cartridge case – mean it can continue firing long after other weapons would be gummed up by dirt, dust and grime. The tradeoff is that it is less accurate than rivals.

Weaponry, unlike consumer technology, doesn’t always yoke to the principle that products get smaller, cheaper, faster and better over time.

While the AK-47 has remained the practically open-standard for cheap-to-make, cheap-to-acquire semi-automatic rifles, expensive projects pushed by militaries across the world have failed to match it. The British Army spent over £480 million ($308 million) and 30 years developing its current standard issue rifle, the SA80. Soldiers despise it. It’s unreliable, works poorly in desert conditions and is fragile compared to the Kalashnikov.

Massive bureaucracy and military might may not create the AI weapon that will become the future AK-47. Computing power continues to get cheaper and the ideas around artificial intelligence continue to spread.

A Russian stamp from 2014 commemorating AK-47 designer
 Mikhail  Kalashnikov

The Mikhail Kalashnikov of AI warfare will be an inventor who gets those principles and works around constraints to create something deadly. And unlike his or her predecessors they’ll have tools like 3D-printing and cheap server farms to lean on.

The global autonomous weapons ban Hawking and others are seeking will most likely count for nothing. Someone will make an AI weapon that is replicable and once it is, it will never be stopped.

The concept of drones has spread from huge military applications to handheld consumer options. Artificial intelligence will follow a similar path.

The realm of ‘aggressive’ AI, designed to power and pilot weaponry, will not be limited to traditional nation states and combatants with standing armies and even the most basic respect for international law.

The AI AK-47 is in our future and that’s terrifying.

Read next: Musk and Hawking lead 1,000 strong call for AI weapons ban

Featured image: Shutterstock
Kalashnikov stamp image: bissig / Shutterstock.com 

ripple effect design

As Android L material design has became a new UI inspiration, tried the same ripple effect of Android L in HTML5 and CSS3 using simple animations. So lets get started,

Download Code

First, Create a button markup and bind a click event listener using jquery.

<button class="ripple">AskorB</button>

Now, on clicking, we declare a ‘$div’ variable, and gets its offset. Then, we calculate the position of cursor by event.pageX and event.pageY from button position.

$('.ripple').on('click', function (event) {
event.preventDefault();

var $div = $('<div/>'),
btnOffset = $(this).offset(), //get position of div

//get cursor position
xPos = event.pageX - btnOffset.left,
yPos = event.pageY - btnOffset.top;

//add animation class
$div.addClass('ripple-effect');
var $ripple = $(".ripple-effect");

//set the hight & width of the animation class

$ripple.css("height", $(this).height());
$ripple.css("width", $(this).height());
$div
.css({
top: yPos - ($ripple.height()/2),
left: xPos - ($ripple.width()/2),
background: $(this).data("ripple-color")
})
.appendTo($(this));

window.setTimeout(function(){
$div.remove();
}, 2000);
});

Then the final part is, add CSS3 animation class for its height and width. Finish the animation is 2 seconds.

textpop-up

@keyframes ripple-animation {
from {
transform: scale(1);
opacity: 0.4;
}
to {
transform: scale(100);
opacity: 0;
}
}