T.J. Thomson, Queensland University of Technology; Daniel Angus, Queensland University of Technology, and Paula Dootson, Queensland University of Technology

Twitter over the weekend “tagged” as manipulated a video showing US Democratic presidential candidate Joe Biden supposedly forgetting which state he’s in while addressing a crowd.

Biden’s “hello Minnesota” greeting contrasted with prominent signage reading “Tampa, Florida” and “Text FL to 30330”.

The Associated Press’s fact check confirmed the signs were added digitally and the original footage was indeed from a Minnesota rally. But by the time the misleading video was removed it already had more than one million views, The Guardian reports.

If you use social media, the chances are you see (and forward) some of the more than 3.2 billion images and 720,000 hours of video shared daily. When faced with such a glut of content, how can we know what’s real and what’s not?

While one part of the solution is an increased use of content verification tools, it’s equally important we all boost our digital media literacy. Ultimately, one of the best lines of defence — and the only one you can control — is you.

Seeing shouldn’t always be believing

Misinformation (when you accidentally share false content) and disinformation (when you intentionally share it) in any medium can erode trust in civil institutions such as news organisations, coalitions and social movements. However, fake photos and videos are often the most potent.

For those with a vested political interest, creating, sharing and/or editing false images can distract, confuse and manipulate viewers to sow discord and uncertainty (especially in already polarised environments). Posters and platforms can also make money from the sharing of fake, sensationalist content.

Only 11-25% of journalists globally use social media content verification tools, according to the International Centre for Journalists.

Read more:
Facebook is tilting the political playing field more than ever, and it’s no accident

Could you spot a doctored image?

Consider this photo of Martin Luther King Jr.

This altered image clones part of the background over King Jr’s finger, so it looks like he’s flipping off the camera. It has been shared as genuine on Twitter, Reddit and white supremacist websites.

In the original 1964 photo, King flashed the “V for victory” sign after learning the US Senate had passed the civil rights bill.

Beyond adding or removing elements, there’s a whole category of photo manipulation in which images are fused together.

Earlier this year, a photo of an armed man was photoshopped by Fox News, which overlaid the man onto other scenes without disclosing the edits, the Seattle Times reported.

Similarly, the image below was shared thousands of times on social media in January, during Australia’s Black Summer bushfires. The AFP’s fact check confirmed it is not authentic and is actually a combination of several separate photos.

Fully and partially synthetic content

Online, you’ll also find sophisticated “deepfake” videos showing (usually famous) people saying or doing things they never did. Less advanced versions can be created using apps such as Zao and Reface.

Or, if you don’t want to use your photo for a profile picture, you can default to one of several websites offering hundreds of thousands of AI-generated, photorealistic images of people.

Editing pixel values and the (not so) simple crop

Cropping can greatly alter the context of a photo, too.

We saw this in 2017, when a US government employee edited official pictures of Donald Trump’s inauguration to make the crowd appear bigger, according to The Guardian. The staffer cropped out the empty space “where the crowd ended” for a set of pictures for Trump.

But what about edits that only alter pixel values such as colour, saturation or contrast?

One historical example illustrates the consequences of this. In 1994, Time magazine’s cover of OJ Simpson considerably “darkened” Simpson in his police mugshot. This added fuel to a case already plagued by racial tension, to which the magazine responded:

No racial implication was intended, by Time or by the artist.

Tools for debunking digital fakery

For those of us who don’t want to be duped by visual mis/disinformation, there are tools available — although each comes with its own limitations (something we discuss in our recent paper).

Invisible digital watermarking has been proposed as a solution. However, it isn’t widespread and requires buy-in from both content publishers and distributors.

Reverse image search (such as Google’s) is often free and can be helpful for identifying earlier, potentially more authentic copies of images online. That said, it’s not foolproof because it:

• relies on unedited copies of the media already being online
• doesn’t search the entire web
• doesn’t always allow filtering by publication time. Some reverse image search services such as TinEye support this function, but Google’s doesn’t.
• returns only exact matches or near-matches, so it’s not thorough. For instance, editing an image and then flipping its orientation can fool Google into thinking it’s an entirely different one.

Read more:
Instead of showing leadership, Twitter pays lip service to the dangers of deep fakes

Most reliable tools are sophisticated

Meanwhile, manual forensic detection methods for visual mis/disinformation focus mostly on edits visible to the naked eye, or rely on examining features that aren’t included in every image (such as shadows). They’re also time-consuming, expensive and need specialised expertise.

Still, you can access work in this field by visiting sites such as Snopes.com — which has a growing repository of “fauxtography”.

Computer vision and machine learning also offer relatively advanced detection capabilities for images and videos. But they too require technical expertise to operate and understand.

Moreover, improving them involves using large volumes of “training data”, but the image repositories used for this usually don’t contain the real-world images seen in the news.

If you use an image verification tool such as the REVEAL project’s image verification assistant, you might need an expert to help interpret the results.

The good news, however, is that before turning to any of the above tools, there are some simple questions you can ask yourself to potentially figure out whether a photo or video on social media is fake. Think:

• was it originally made for social media?
• how widely and for how long was it circulated?
• what responses did it receive?
• who were the intended audiences?

Quite often, the logical conclusions drawn from the answers will be enough to weed out inauthentic visuals. You can access the full list of questions, put together by Manchester Metropolitan University experts, here.

T.J. Thomson, Senior Lecturer in Visual Communication & Media, Queensland University of Technology; Daniel Angus, Associate Professor in Digital Communication, Queensland University of Technology, and Paula Dootson, Senior Lecturer, Queensland University of Technology

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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While governments are spending billions to build football – sized nuclear fusion reactors — the elusive process of harnessing energy from fusing atoms, rather than breaking them apart — a 12 year old kid from Memphis, Tennessee, just became the youngest person to have ever achieved nuclear fusion, […]

Jackson Oswalt achieved nuclear fusion by fusing two deuterium atoms together in a thermonuclear reactor he built in the playroom of his family’s house.

According to Jackson, he was the sole one that worked on the reactor during both the planning and production stages.

“The temperature in my fusor varies, but it’s approximately 100 million degrees [Kelvin],” Jackson said in the Guinness World Records video accompanying the announcement.
“I have been able to use electricity to accelerate two atoms of deuterium together in order that they fuse together into an atom of helium 3 [isotope], which also releases a neutron which can be used to heat up water and turn a steam engine, which in turn produces electricity,” he explained in the video.

Jackson was inspired by Taylor Wilson, who was the previous record holder at the age of 14.
Building a DIY thermonuclear reactor — albeit not one which will generate more power than you set into it, a grail among energy researchers — may be a challenging but achievable task with a thriving online community around it.

“There were a few moments during the project that I had some reservations,” Jackson’s mother admitted. “I would definitely be googling things before he turned on various stages.”

She also added that “he did a great job of explaining it to us.”

Click here to check out the original story at Futurism

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As the ills of factory farming become more pronounced, people are increasingly gravitating towards vegetarian or pescatarian diets. Besides producing a large percentage of our total greenhouse gas emissions, raising livestock uses up a third of the world’s arable land to grow feed, not to mention that the animals themselves are often terribly mistreated.
Eating fish, then, seems preferable to meat. In fact, according to the Global Aquaculture Alliance, 3.1 billion people around the world now rely on fish and seafood for a fifth of their daily animal protein intake. Fish are also one of our only sources of long-chain omega-3 fatty acids.
But—spoiler—it turns out there are some serious issues with the seafood industry, too.

In Hot Water

Water temperatures are rising, throwing off marine ecosystems’ natural balance and kicking off negative ripple effects throughout their food chains. Overfishing—when we take fish out of their natural habitat at a rate too fast for them to keep up with in terms of replenishing the supply—has depleted wild populations of halibut, monkfish, tuna, and salmon, among others.
Salmon in particular are one of the most crucial species for the ecosystems they inhabit. Since they’re born in freshwater streams but then migrate to the sea to mature, salmon serve as a link between saltwater and freshwater ecosystems, bringing nutrients from the oceans inland and vice versa. They’re also a key food source for bigger animals like bears and whales.
But mass-producing salmon for human consumption has hurt the species’ wild population. Between the 1970s and today, for example, the number of wild Atlantic salmon out there has been cut in half or maybe more, going from 8 to 10 million to just 3 to 4 million. And salmon farms have a recurring problem with parasites called sea lice (I know—gross), which flourish in densely-packed pens and spread to wild fish when farmed fish escape.

Fish Without Fish

A San Francisco-based startup called Wildtype is developing a product that could one day help alleviate the problems caused by fish farming: the company is devoted to producing lab-grown salmon.
Similar to cultured meat like that made by Memphis Meats, Wildtype’s salmon starts with real animal cells and adds a mixture of nutrients, sugars, salts, amino acids, and growth factor to coax the cells to grow as they naturally would inside an animal’s body. Done right, the process can yield animal tissue that contains muscle, blood, and fat, just like you’d get from a farmed fish. Except in some ways it’s even better, because what you don’t get is mercury, microplastics, and the other contaminants that farmed fish are becoming rife with.
Wildtype created its own technology for the “scaffolds” where tissue grows. “This is applicable to other species than the salmon that we have worked on,” Wildtype co-founder Arye Elfenbein told Tech Crunch. “We basically create a scaffold that provides the right guidance…for cells to take up fats in different places or become more striated.”
The company just opened up a pre-order waiting list for its product to chefs around the country, despite commercial production being up to five years away.

Challenges Upstream

Last year the company did a taste test for employees, investors, and a group of chefs and restaurateurs. While the texture of the fish was apparently realistic, its taste was described as “lacking.” And that’s not the only challenge Wildtype will have to overcome; the company estimated that each spicy salmon roll served at the tasting cost $200 to produce.
This is the biggest issue with lab-grown meat, whether beef, pork, or fish—it’s difficult and costly to scale up its production. Wildtype is aiming to lower its costs to seven to eight dollars a pound within a few years. “The dream vision is the cleanest, purest, freshest salmon, without contaminants or antibiotics, for a price lower than farmed Atlantic salmon,” said cofounder Justin Kolbeck.
It’s likely that one day in the future—maybe distant, maybe not so much—we’ll look back in disbelief at the way we used to raise and slaughter entire animals just to get a few cuts of their flesh. It will seem wasteful and barbaric compared to growing exactly the cuts of meat that we want, with no death or pollution involved. It’s still a ways off, but if companies like Wildtype can make their vision a reality, people, animals, and the planet will all be better off for it.
Image Credit: Wildtype
By Vanessa Bates RamirezThis article originally appeared on Singularity Hub, a publication of Singularity University.

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Researchers have created an artificial skin that is capable of reacting to pain just like real human skin. The goal is to improve on prosthetics, allow for better alternatives to skin grafts, and even to “augment or compensate human skin for the development of realistic humanoids,”[…]

No technology has been able to create a feeling of pain until now. When heat, cold, or pressure reaches a painful threshold, this artificial skin will react instantly. So this artificial skin will know the difference between gently touching a sharp knife or cutting yourself with it. This is the first time this distinction has been made electronically.

Lead researcher Professor Madhu Bhaskaran said the pain-sensing prototype was a significant advance towards next-generation biomedical technologies and intelligent robotics.

“Skin is our body’s largest sensory organ, with complex features designed to send rapid-fire warning signals when anything hurts,” Bhaskaran said.

“We’re sensing things all the time through the skin but our pain response only kicks in at a certain point, like when we touch something too hot or too sharp.”

This will be a huge breakthrough for people using prosthetics and the future development of robots. Because who doesn’t want their robots to feel pain? Right?

Read more about wearable robots that are in development here.

Click here to check out the story at Futurism

/disruptivetechnology

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A wearable robotic exoskeleton that gives humans super power. Now there’s a hybrid solution: A Wearable Robotic Exeskeletons (RBOEs) for people to wear on their bodies and walk in place of the traditional body parts, such as legs or arms; they can also be controlled.

Voice of America

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Humans began to develop systems of reading and writing only within the past few thousand years. Our reading abilities set us apart from other animal species. Still, a few thousand years is much too short a timeframe for our brains to have evolved new areas specifically devoted to reading. […]

Humans began to develop systems of reading and writing only within the past few thousand years. Our reading abilities set us aside from other animal species, but a couple of thousand years is far too short a timeframe for our brains to possess evolved new areas specifically dedicated to reading.

To account for the event of this skill, some scientists have hypothesized that parts of the brain that originally evolved for other purposes are “recycled” for reading. together example, they suggest that a neighborhood of the sensory system that’s specialized to perform visual perception has been repurposed for a critical component of reading called orthographic processing – the power to acknowledge written letters and words.

A new study from MIT neuroscientists offers evidence for this hypothesis. The findings suggest that even in nonhuman primates, who don’t skills to read, a neighborhood of the brain called the inferotemporal (IT) cortex is capable of performing tasks like distinguishing words from nonsense words or picking out specific letters from a word.

“This work has opened a possible linkage between our rapidly developing understanding of the neural mechanisms of visual processing and a crucial primate behavior — human reading,” says James DiCarlo, the top of MIT’s Department of Brain and Cognitive Sciences, an investigator within the McGovern Institute for Brain Research and therefore the Center for Brains, Minds, and Machines, and therefore the senior author of the study.

Rishi Rajalingham, an MIT postdoc, is that the lead author of the study, which appears in Nature Communications. Other MIT authors are postdoc Kohitij Kar and technical associate Sachi Sanghavi. The research team also includes Stanislas Dehaene, a professor of experimental psychology at the school de France.

Word recognition Reading may be a complex process that needs recognizing words, assigning aiming to those words, and associating words with their corresponding sound. These functions are believed to be opened up over different parts of the human brain.

Functional resonance imaging (fMRI) studies have identified a neighborhood called the visual form area (VWFA) that lights up when the brain processes a word. This region is involved within the orthographic stage: It discriminates words from jumbled strings of letters or words from unknown alphabets. The VWFA is found within the IT cortex, a neighborhood of the visual area that’s also liable for identifying objects.

DiCarlo and Dehaene took an interest in studying the neural mechanisms behind word recognition after cognitive psychologists in France reported that baboons could learn to discriminate words from nonwords, during a study that appeared in Science in 2012.

Using fMRI, Dehaene’s lab has previously found that parts of the IT cortex that answer objects and faces become highly specialized for recognizing written words once people learn to read.

“However, given the restrictions of human imaging methods, it’s been challenging to characterize these representations at the resolution of individual neurons, and to quantitatively test if and the way these representations could be reused to support orthographic processing,” Dehaene says. “These findings inspired us to ask if nonhuman primates could provide a singular opportunity to research the neuronal mechanisms underlying orthographic processing.”

The researchers hypothesized that if parts of the primate brain are predisposed to process text, they could be ready to find patterns reflecting that within the neural activity of nonhuman primates as they simply check out words.

To test that concept, the researchers recorded neural activity from about 500 neural sites across the IT cortex of macaques as they checked out about 2,000 strings of letters, a number of which were English words and a few of which were nonsensical strings of letters.

“The efficiency of this system is that you simply don’t get to train animals to try to anything,” Rajalingham says. “What you are doing is simply record these patterns of neural activity as you flash a picture ahead of the animal.”

The researchers then fed that neural data into an easy computer model called a linear classifier. This model learns to mix the inputs from each of the five hundred neural sites to predict whether the string of letters that provoked that activity pattern was a word or not. While the animal itself isn’t performing this task, the model acts as a “stand-in” that uses the neural data to get a behavior, Rajalingham says.

Using that neural data, the model was ready to generate accurate predictions for several orthographic tasks, including distinguishing words from nonwords and determining if a specific letter is present during a string of words. The model was about 70 percent accurate at distinguishing words from nonwords, which is extremely almost like the speed reported within the 2012 Science study with baboons. Furthermore, the patterns of errors made by model were virtually like those made by the animals.

Neuronal recycling The researchers also recorded neural activity from a unique brain area that also feeds into IT cortex: V4, which is a component of the visual area. once they fed V4 activity patterns into the linear classifier model, the model poorly predicted (compared to IT) the human or baboon performance on the orthographic processing tasks.

The findings suggest that the IT cortex is especially well-suited to be repurposed for skills that are needed for reading and that they support the hypothesis that a number of the mechanisms of reading are built upon highly evolved mechanisms for visual perception, the researchers say.

The researchers now decide to train animals to perform orthographic tasks and measure how their neural activity changes as they learn the tasks.

Reference Rajalingham et al. (2020). The inferior temporal cortex may be a potential cortical precursor of orthographic processing in untrained monkeys. Nature Communications. DOI: https://doi.org/10.1038/s41467-020-17714-3

This article has been republished from the subsequent materials. Note: material may are edited for length and content. For further information, please contact the cited source.

Original story from the Massachusetts Institute of Technology

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The post How a Recycled Brain Region Helped Humans Learn To Read first appeared on Disruptive Entrepreneur.

At the highest of the interview, he told Wired:

“I’ve made my peace with it. At the top of the day, the match wasn’t a curse but a blessing, because I used to be a neighborhood of something vital. Twenty-two years ago, I might have thought differently. But things happen. We all make mistakes. We lose. What’s important is how we affect our mistakes, with a negative experience.”[…]

Sounds like a man who made an error getting his ass beat by a computer. That said, how Kasparov is handling it actually has some value to the remainder of us: Making a compelling case that he was the primary guy to be truly outwitted in his job by a computer, he’s now become a thinker asking questions of the consequences of A.I. that transcend the sensible or the technical, but more towards the philosophical nature of machinery. A mind like Kasparov’s — one who understands the dynamic nature of grand, sweeping, coordinated, changeable movements, gambits, and calculable variabilities as means towards ends — is that the quite thinking the sector could probably use more of.

For instance, one aside Kasparov gave when Wired asked him how close he believes we are to human-level AI:

“We don’t know exactly what intelligence is. Even the simplest computer experts, the people on the leading edge of computing, they still have doubts about exactly what we’re doing.”

He’s utterly correct, both about the unknown nature of what we’re doing and therefore the very nature of intelligence itself, human or otherwise. the whole thing is worth reading if only to ascertain a man finally come to terms 20 years later with getting his ass beat at chess by a computer.

More on AI:

AI generates fake news articles.

AI Is Inventing Languages Humans Can’t Understand. Should We Stop It?

Original Story on Wired

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WHY IT’S DISRUPTIVE:
Private space travel. Elon Musk’s Space X is preparing to fly a full-scale prototype of its Starship for the first time as it sets its sights on the moon and Mars.

This comes on the heels of Space X’s first successful manned mission to the space station this month.

Better late than never as the adage goes. It’s taken much longer than expected to get to this point as Space 2.0 points out.

“We ’re going to go to the moon, we ’re going to have a base on the moon, we ’re going to send people to Mars and make life multi planetary,” Mr Musk said as he greeted two Nasa astronauts.”[…]

Click here to check out the original story

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a long-deferred dream in aviation — the law will allow them to drive on the states roads, which lawmakers say was not previously legal […]

WHO, WHAT, WHERE & WHY IT’S DISRUPTIVE

What: This new law will allow flying cars to drive on the roads, which was not previously legal in the state.

Who: New Hampshire lawmakers

Where: New Hampshire

Why this is disruptive: This law clears the way for flying cars to drive on the streets without getting sited as an illegal vehicle.

Click here to check out the original story

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