Tag Archives: virtual reality

#433288 The New AI Tech Turning Heads in Video ...

A new technique using artificial intelligence to manipulate video content gives new meaning to the expression “talking head.”

An international team of researchers showcased the latest advancement in synthesizing facial expressions—including mouth, eyes, eyebrows, and even head position—in video at this month’s 2018 SIGGRAPH, a conference on innovations in computer graphics, animation, virtual reality, and other forms of digital wizardry.

The project is called Deep Video Portraits. It relies on a type of AI called generative adversarial networks (GANs) to modify a “target” actor based on the facial and head movement of a “source” actor. As the name implies, GANs pit two opposing neural networks against one another to create a realistic talking head, right down to the sneer or raised eyebrow.

In this case, the adversaries are actually working together: One neural network generates content, while the other rejects or approves each effort. The back-and-forth interplay between the two eventually produces a realistic result that can easily fool the human eye, including reproducing a static scene behind the head as it bobs back and forth.

The researchers say the technique can be used by the film industry for a variety of purposes, from editing facial expressions of actors for matching dubbed voices to repositioning an actor’s head in post-production. AI can not only produce highly realistic results, but much quicker ones compared to the manual processes used today, according to the researchers. You can read the full paper of their work here.

“Deep Video Portraits shows how such a visual effect could be created with less effort in the future,” said Christian Richardt, from the University of Bath’s motion capture research center CAMERA, in a press release. “With our approach, even the positioning of an actor’s head and their facial expression could be easily edited to change camera angles or subtly change the framing of a scene to tell the story better.”

AI Tech Different Than So-Called “Deepfakes”
The work is far from the first to employ AI to manipulate video and audio. At last year’s SIGGRAPH conference, researchers from the University of Washington showcased their work using algorithms that inserted audio recordings from a person in one instance into a separate video of the same person in a different context.

In this case, they “faked” a video using a speech from former President Barack Obama addressing a mass shooting incident during his presidency. The AI-doctored video injects the audio into an unrelated video of the president while also blending the facial and mouth movements, creating a pretty credible job of lip synching.

A previous paper by many of the same scientists on the Deep Video Portraits project detailed how they were first able to manipulate a video in real time of a talking head (in this case, actor and former California governor Arnold Schwarzenegger). The Face2Face system pulled off this bit of digital trickery using a depth-sensing camera that tracked the facial expressions of an Asian female source actor.

A less sophisticated method of swapping faces using a machine learning software dubbed FakeApp emerged earlier this year. Predictably, the tech—requiring numerous photos of the source actor in order to train the neural network—was used for more juvenile pursuits, such as injecting a person’s face onto a porn star.

The application gave rise to the term “deepfakes,” which is now used somewhat ubiquitously to describe all such instances of AI-manipulated video—much to the chagrin of some of the researchers involved in more legitimate uses.

Fighting AI-Created Video Forgeries
However, the researchers are keenly aware that their work—intended for benign uses such as in the film industry or even to correct gaze and head positions for more natural interactions through video teleconferencing—could be used for nefarious purposes. Fake news is the most obvious concern.

“With ever-improving video editing technology, we must also start being more critical about the video content we consume every day, especially if there is no proof of origin,” said Michael Zollhöfer, a visiting assistant professor at Stanford University and member of the Deep Video Portraits team, in the press release.

Toward that end, the research team is training the same adversarial neural networks to spot video forgeries. They also strongly recommend that developers clearly watermark videos that are edited through AI or otherwise, and denote clearly what part and element of the scene was modified.

To catch less ethical users, the US Department of Defense, through the Defense Advanced Research Projects Agency (DARPA), is supporting a program called Media Forensics. This latest DARPA challenge enlists researchers to develop technologies to automatically assess the integrity of an image or video, as part of an end-to-end media forensics platform.

The DARPA official in charge of the program, Matthew Turek, did tell MIT Technology Review that so far the program has “discovered subtle cues in current GAN-manipulated images and videos that allow us to detect the presence of alterations.” In one reported example, researchers have targeted eyes, which rarely blink in the case of “deepfakes” like those created by FakeApp, because the AI is trained on still pictures. That method would seem to be less effective to spot the sort of forgeries created by Deep Video Portraits, which appears to flawlessly match the entire facial and head movements between the source and target actors.

“We believe that the field of digital forensics should and will receive a lot more attention in the future to develop approaches that can automatically prove the authenticity of a video clip,” Zollhöfer said. “This will lead to ever-better approaches that can spot such modifications even if we humans might not be able to spot them with our own eyes.

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#433278 Outdated Evolution: Updating Our ...

What happens when evolution shapes an animal for tribes of 150 primitive individuals living in a chaotic jungle, and then suddenly that animal finds itself living with millions of others in an engineered metropolis, their pockets all bulging with devices of godlike power?

The result, it seems, is a modern era of tension where archaic forms of governance struggle to keep up with the technological advances of their citizenry, where governmental policies act like constraining bottlenecks rather than spearheads of progress.

Simply put, our governments have failed to adapt to disruptive technologies. And if we are to regain our stability moving forward into a future of even greater disruption, it’s imperative that we understand the issues that got us into this situation and what kind of solutions we can engineer to overcome our governmental weaknesses.

Hierarchy vs. Technological Decentralization
Many of the greatest issues our governments face today come from humanity’s biologically-hardwired desire for centralized hierarchies. This innate proclivity towards building and navigating systems of status and rank were evolutionary gifts handed down to us by our ape ancestors, where each member of a community had a mental map of their social hierarchy. Their nervous systems behaved differently depending on their rank in this hierarchy, influencing their interactions in a way that ensured only the most competent ape would rise to the top to gain access to the best food and mates.

As humanity emerged and discovered the power of language, we continued this practice by ensuring that those at the top of the hierarchies, those with the greatest education and access to information, were the dominant decision-makers for our communities.

However, this kind of structured chain of power is only necessary if we’re operating in conditions of scarcity. But resources, including information, are no longer scarce.

It’s estimated that more than two-thirds of adults in the world now own a smartphone, giving the average citizen the same access to the world’s information as the leaders of our governments. And with global poverty falling from 35.5 percent to 10.9 percent over the last 25 years, our younger generations are growing up seeing automation and abundance as a likely default, where innovations like solar energy, lab-grown meat, and 3D printing are expected to become commonplace.

It’s awareness of this paradigm shift that has empowered the recent rise of decentralization. As information and access to resources become ubiquitous, there is noticeably less need for our inefficient and bureaucratic hierarchies.

For example, if blockchain can prove its feasibility for large-scale systems, it can be used to update and upgrade numerous applications to a decentralized model, including currency and voting. Such innovations would lower the risk of failing banks collapsing the economy like they did in 2008, as well as prevent corrupt politicians from using gerrymandering and long queues at polling stations to deter voter participation.

Of course, technology isn’t a magic wand that should be implemented carelessly. Facebook’s “move fast and break things” approach might have very possibly broken American democracy in 2016, as social media played on some of the worst tendencies humanity can operate on during an election: fear and hostility.

But if decentralized technology, like blockchain’s public ledgers, can continue to spread a sense of security and transparency throughout society, perhaps we can begin to quiet that paranoia and hyper-vigilance our brains evolved to cope with living as apes in dangerous jungles. By decentralizing our power structures, we take away the channels our outdated biological behaviors might use to enact social dominance and manipulation.

The peace of mind this creates helps to reestablish trust in our communities and in our governments. And with trust in the government increased, it’s likely we’ll see our next issue corrected.

From Business and Law to Science and Technology
A study found that 59 percent of US presidents, 68 percent of vice presidents, and 78 percent of secretaries of state were lawyers by education and occupation. That’s more than one out of every two people in the most powerful positions in the American government restricted to a field dedicated to convincing other people (judges) their perspective is true, even if they lack evidence.

And so the scientific method became less important than semantics to our leaders.

Similarly, of the 535 individuals in the American congress, only 24 hold a PhD, only 2 of which are in a STEM field. And so far, it’s not getting better: Trump is the first president since WWII not to name a science advisor.

But if we can use technologies like blockchain to increase transparency, efficiency, and trust in the government, then the upcoming generations who understand decentralization, abundance, and exponential technologies might feel inspired enough to run for government positions. This helps solve that common problem where the smartest and most altruistic people tend to avoid government positions because they don’t want to play the semantic and deceitful game of politics.

By changing this narrative, our governments can begin to fill with techno-progressive individuals who actually understand the technologies that are rapidly reshaping our reality. And this influence of expertise is going to be crucial as our governments are forced to restructure and create new policies to accommodate the incoming disruption.

Clearing Regulations to Begin Safe Experimentation
As exponential technologies become more ubiquitous, we’re likely going to see young kids and garage tinkerers creating powerful AIs and altering genetics thanks to tools like CRISPR and free virtual reality tutorials.

This easy accessibility to such powerful technology means unexpected and rapid progress can occur almost overnight, quickly overwhelming our government’s regulatory systems.

Uber and Airbnb are two of the best examples of our government’s inability to keep up with such technology, both companies achieving market dominance before regulators were even able to consider how to handle them. And when a government has decided against them, they often still continue to operate because people simply choose to keep using the apps.

Luckily, this kind of disruption hasn’t yet posed a major existential threat. But this will change when we see companies begin developing cyborg body parts, brain-computer interfaces, nanobot health injectors, and at-home genetic engineering kits.

For this reason, it’s crucial that we have experts who understand how to update our regulations to be as flexible as is necessary to ensure we don’t create black market conditions like we’ve done with drugs. It’s better to have safe and monitored experimentation, rather than forcing individuals into seedy communities using unsafe products.

Survival of the Most Adaptable
If we hope to be an animal that survives our changing environment, we have to adapt. We cannot cling to the behaviors and systems formed thousands of years ago. We must instead acknowledge that we now exist in an ecosystem of disruptive technology, and we must evolve and update our governments if they’re going to be capable of navigating these transformative impacts.

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#432891 This Week’s Awesome Stories From ...

TRANSPORTATION
Elon Musk Presents His Tunnel Vision to the People of LA
Jack Stewart and Aarian Marshall | Wired
“Now, Musk wants to build this new, 2.1-mile tunnel, near LA’s Sepulveda pass. It’s all part of his broader vision of a sprawling network that could take riders from Sherman Oaks in the north to Long Beach Airport in the south, Santa Monica in the west to Dodger Stadium in the east—without all that troublesome traffic.”

ROBOTICS
Feel What This Robot Feels Through Tactile Expressions
Evan Ackerman | IEEE Spectrum
“Guy Hoffman’s Human-Robot Collaboration & Companionship (HRC2) Lab at Cornell University is working on a new robot that’s designed to investigate this concept of textural communication, which really hasn’t been explored in robotics all that much. The robot uses a pneumatically powered elastomer skin that can be dynamically textured with either goosebumps or spikes, which should help it communicate more effectively, especially if what it’s trying to communicate is, ‘Don’t touch me!’”

VIRTUAL REALITY
In Virtual Reality, How Much Body Do You Need?
Steph Yin | The New York Times
“In a paper published Tuesday in Scientific Reports, they showed that animating virtual hands and feet alone is enough to make people feel their sense of body drift toward an invisible avatar. Their work fits into a corpus of research on illusory body ownership, which has challenged understandings of perception and contributed to therapies like treating pain for amputees who experience phantom limb.”

MEDICINE
How Graphene and Gold Could Help Us Test Drugs and Monitor Cancer
Angela Chen | The Verge
“In today’s study, scientists learned to precisely control the amount of electricity graphene generates by changing how much light they shine on the material. When they grew heart cells on the graphene, they could manipulate the cells too, says study co-author Alex Savtchenko, a physicist at the University of California, San Diego. They could make it beat 1.5 times faster, three times faster, 10 times faster, or whatever they needed.”

DISASTER RELIEF
Robotic Noses Could Be the Future of Disaster Rescue—If They Can Outsniff Search Dogs
Eleanor Cummins | Popular Science
“While canine units are a tried and fairly true method for identifying people trapped in the wreckage of a disaster, analytical chemists have for years been working in the lab to create a robotic alternative. A synthetic sniffer, they argue, could potentially prove to be just as or even more reliable than a dog, more resilient in the face of external pressures like heat and humidity, and infinitely more portable.”

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#432512 How Will Merging Minds and Machines ...

One of the most exciting and frightening outcomes of technological advancement is the potential to merge our minds with machines. If achieved, this would profoundly boost our cognitive capabilities. More importantly, however, it could be a revolution in human identity, emotion, spirituality, and self-awareness.

Brain-machine interface technology is already being developed by pioneers and researchers around the globe. It’s still early and today’s tech is fairly rudimentary, but it’s a fast-moving field, and some believe it will advance faster than generally expected. Futurist Ray Kurzweil has predicted that by the 2030s we will be able to connect our brains to the internet via nanobots that will “provide full-immersion virtual reality from within the nervous system, provide direct brain-to-brain communication over the internet, and otherwise greatly expand human intelligence.” Even if the advances are less dramatic, however, they’ll have significant implications.

How might this technology affect human consciousness? What about its implications on our sentience, self-awareness, or subjective experience of our illusion of self?

Consciousness can be hard to define, but a holistic definition often encompasses many of our most fundamental capacities, such as wakefulness, self-awareness, meta-cognition, and sense of agency. Beyond that, consciousness represents a spectrum of awareness, as seen across various species of animals. Even humans experience different levels of existential awareness.

From psychedelics to meditation, there are many tools we already use to alter and heighten our conscious experience, both temporarily and permanently. These tools have been said to contribute to a richer life, with the potential to bring experiences of beauty, love, inner peace, and transcendence. Relatively non-invasive, these tools show us what a seemingly minor imbalance of neurochemistry and conscious internal effort can do to the subjective experience of being human.

Taking this into account, what implications might emerging brain-machine interface technologies have on the “self”?

The Tools for Self-Transcendence
At the basic level, we are currently seeing the rise of “consciousness hackers” using techniques like non-invasive brain stimulation through EEG, nutrition, virtual reality, and ecstatic experiences to create environments for heightened consciousness and self-awareness. In Stealing Fire, Steven Kotler and Jamie Wheal explore this trillion-dollar altered-states economy and how innovators and thought leaders are “harnessing rare and controversial states of consciousness to solve critical challenges and outperform the competition.” Beyond enhanced productivity, these altered states expose our inner potential and give us a glimpse of a greater state of being.

Expanding consciousness through brain augmentation and implants could one day be just as accessible. Researchers are working on an array of neurotechnologies as simple and non-invasive as electrode-based EEGs to invasive implants and techniques like optogenetics, where neurons are genetically reprogrammed to respond to pulses of light. We’ve already connected two brains via the internet, allowing the two to communicate, and future-focused startups are researching the possibilities too. With an eye toward advanced brain-machine interfaces, last year Elon Musk unveiled Neuralink, a company whose ultimate goal is to merge the human mind with AI through a “neural lace.”

Many technologists predict we will one day merge with and, more speculatively, upload our minds onto machines. Neuroscientist Kenneth Hayworth writes in Skeptic magazine, “All of today’s neuroscience models are fundamentally computational by nature, supporting the theoretical possibility of mind-uploading.” This might include connecting with other minds using digital networks or even uploading minds onto quantum computers, which can be in multiple states of computation at a given time.

In their book Evolving Ourselves, Juan Enriquez and Steve Gullans describe a world where evolution is no longer driven by natural processes. Instead, it is driven by human choices, through what they call unnatural selection and non-random mutation. With advancements in genetic engineering, we are indeed seeing evolution become an increasingly conscious process with an accelerated pace. This could one day apply to the evolution of our consciousness as well; we would be using our consciousness to expand our consciousness.

What Will It Feel Like?
We may be able to come up with predictions of the impact of these technologies on society, but we can only wonder what they will feel like subjectively.

It’s hard to imagine, for example, what our stream of consciousness will feel like when we can process thoughts and feelings 1,000 times faster, or how artificially intelligent brain implants will impact our capacity to love and hate. What will the illusion of “I” feel like when our consciousness is directly plugged into the internet? Overall, what impact will the process of merging with technology have on the subjective experience of being human?

The Evolution of Consciousness
In The Future Evolution of Consciousness, Thomas Lombardo points out, “We are a journey rather than a destination—a chapter in the evolutionary saga rather than a culmination. Just as probable, there will also be a diversification of species and types of conscious minds. It is also very likely that new psychological capacities, incomprehensible to us, will emerge as well.”

Humans are notorious for fearing the unknown. For any individual who has never experienced an altered state, be it spiritual or psychedelic-induced, it is difficult to comprehend the subjective experience of that state. It is why many refer to their first altered-state experience as “waking up,” wherein they didn’t even realize they were asleep.

Similarly, exponential neurotechnology represents the potential of a higher state of consciousness and a range of experiences that are unimaginable to our current default state.

Our capacity to think and feel is set by the boundaries of our biological brains. To transform and expand these boundaries is to transform and expand the first-hand experience of consciousness. Emerging neurotechnology may end up providing the awakening our species needs.

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#432487 Can We Make a Musical Turing Test?

As artificial intelligence advances, we’re encountering the same old questions. How much of what we consider to be fundamentally human can be reduced to an algorithm? Can we create something sufficiently advanced that people can no longer distinguish between the two? This, after all, is the idea behind the Turing Test, which has yet to be passed.

At first glance, you might think music is beyond the realm of algorithms. Birds can sing, and people can compose symphonies. Music is evocative; it makes us feel. Very often, our intense personal and emotional attachments to music are because it reminds us of our shared humanity. We are told that creative jobs are the least likely to be automated. Creativity seems fundamentally human.

But I think above all, we view it as reductionist sacrilege: to dissect beautiful things. “If you try to strangle a skylark / to cut it up, see how it works / you will stop its heart from beating / you will stop its mouth from singing.” A human musician wrote that; a machine might be able to string words together that are happy or sad; it might even be able to conjure up a decent metaphor from the depths of some neural network—but could it understand humanity enough to produce art that speaks to humans?

Then, of course, there’s the other side of the debate. Music, after all, has a deeply mathematical structure; you can train a machine to produce harmonics. “In the teachings of Pythagoras and his followers, music was inseparable from numbers, which were thought to be the key to the whole spiritual and physical universe,” according to Grout in A History of Western Music. You might argue that the process of musical composition cannot be reduced to a simple algorithm, yet musicians have often done so. Mozart, with his “Dice Music,” used the roll of a dice to decide how to order musical fragments; creativity through an 18th-century random number generator. Algorithmic music goes back a very long way, with the first papers on the subject from the 1960s.

Then there’s the techno-enthusiast side of the argument. iTunes has 26 million songs, easily more than a century of music. A human could never listen to and learn from them all, but a machine could. It could also memorize every note of Beethoven. Music can be converted into MIDI files, a nice chewable data format that allows even a character-by-character neural net you can run on your computer to generate music. (Seriously, even I could get this thing working.)

Indeed, generating music in the style of Bach has long been a test for AI, and you can see neural networks gradually learn to imitate classical composers while trying to avoid overfitting. When an algorithm overfits, it essentially starts copying the existing music, rather than being inspired by it but creating something similar: a tightrope the best human artists learn to walk. Creativity doesn’t spring from nowhere; even maverick musical geniuses have their influences.

Does a machine have to be truly ‘creative’ to produce something that someone would find valuable? To what extent would listeners’ attitudes change if they thought they were hearing a human vs. an AI composition? This all suggests a musical Turing Test. Of course, it already exists. In fact, it’s run out of Dartmouth, the school that hosted that first, seminal AI summer conference. This year, the contest is bigger than ever: alongside the PoetiX, LimeriX and LyriX competitions for poetry and lyrics, there’s a DigiKidLit competition for children’s literature (although you may have reservations about exposing your children to neural-net generated content… it can get a bit surreal).

There’s also a pair of musical competitions, including one for original compositions in different genres. Key genres and styles are represented by Charlie Parker for Jazz and the Bach chorales for classical music. There’s also a free composition, and a contest where a human and an AI try to improvise together—the AI must respond to a human spontaneously, in real time, and in a musically pleasing way. Quite a challenge! In all cases, if any of the generated work is indistinguishable from human performers, the neural net has passed the Turing Test.

Did they? Here’s part of 2017’s winning sonnet from Charese Smiley and Hiroko Bretz:

The large cabin was in total darkness.
Come marching up the eastern hill afar.
When is the clock on the stairs dangerous?
Everything seemed so near and yet so far.
Behind the wall silence alone replied.
Was, then, even the staircase occupied?
Generating the rhymes is easy enough, the sentence structure a little trickier, but what’s impressive about this sonnet is that it sticks to a single topic and appears to be a more coherent whole. I’d guess they used associated “lexical fields” of similar words to help generate something coherent. In a similar way, most of the more famous examples of AI-generated music still involve some amount of human control, even if it’s editorial; a human will build a song around an AI-generated riff, or select the most convincing Bach chorale from amidst many different samples.

We are seeing strides forward in the ability of AI to generate human voices and human likenesses. As the latter example shows, in the fake news era people have focused on the dangers of this tech– but might it also be possible to create a virtual performer, trained on a dataset of their original music? Did you ever want to hear another Beatles album, or jam with Miles Davis? Of course, these things are impossible—but could we create a similar experience that people would genuinely value? Even, to the untrained eye, something indistinguishable from the real thing?

And if it did measure up to the real thing, what would this mean? Jaron Lanier is a fascinating technology writer, a critic of strong AI, and a believer in the power of virtual reality to change the world and provide truly meaningful experiences. He’s also a composer and a musical aficionado. He pointed out in a recent interview that translation algorithms, by reducing the amount of work translators are commissioned to do, have, in some sense, profited from stolen expertise. They were trained on huge datasets purloined from human linguists and translators. If you can train an AI on someone’s creative output and it produces new music, who “owns” it?

Although companies that offer AI music tools are starting to proliferate, and some groups will argue that the musical Turing test has been passed already, AI-generated music is hardly racing to the top of the pop charts just yet. Even as the line between human-composed and AI-generated music starts to blur, there’s still a gulf between the average human and musical genius. In the next few years, we’ll see how far the current techniques can take us. It may be the case that there’s something in the skylark’s song that can’t be generated by machines. But maybe not, and then this song might need an extra verse.

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