Posts Tagged ‘The Singularity’

by John H. Richardson

In an ordinary hospital room in Los Angeles, a young woman named Lauren Dickerson waits for her chance to make history.

She’s 25 years old, a teacher’s assistant in a middle school, with warm eyes and computer cables emerging like futuristic dreadlocks from the bandages wrapped around her head. Three days earlier, a neurosurgeon drilled 11 holes through her skull, slid 11 wires the size of spaghetti into her brain, and connected the wires to a bank of computers. Now she’s caged in by bed rails, with plastic tubes snaking up her arm and medical monitors tracking her vital signs. She tries not to move.

The room is packed. As a film crew prepares to document the day’s events, two separate teams of specialists get ready to work—medical experts from an elite neuroscience center at the University of Southern California and scientists from a technology company called Kernel. The medical team is looking for a way to treat Dickerson’s seizures, which an elaborate regimen of epilepsy drugs controlled well enough until last year, when their effects began to dull. They’re going to use the wires to search Dickerson’s brain for the source of her seizures. The scientists from Kernel are there for a different reason: They work for Bryan Johnson, a 40-year-old tech entrepreneur who sold his business for $800 million and decided to pursue an insanely ambitious dream—he wants to take control of evolution and create a better human. He intends to do this by building a “neuroprosthesis,” a device that will allow us to learn faster, remember more, “coevolve” with artificial intelligence, unlock the secrets of telepathy, and maybe even connect into group minds. He’d also like to find a way to download skills such as martial arts, Matrix-style. And he wants to sell this invention at mass-market prices so it’s not an elite product for the rich.

Right now all he has is an algorithm on a hard drive. When he describes the neuroprosthesis to reporters and conference audiences, he often uses the media-friendly expression “a chip in the brain,” but he knows he’ll never sell a mass-market product that depends on drilling holes in people’s skulls. Instead, the algorithm will eventually connect to the brain through some variation of noninvasive interfaces being developed by scientists around the world, from tiny sensors that could be injected into the brain to genetically engineered neurons that can exchange data wirelessly with a hatlike receiver. All of these proposed interfaces are either pipe dreams or years in the future, so in the meantime he’s using the wires attached to Dickerson’s hippo­campus to focus on an even bigger challenge: what you say to the brain once you’re connected to it.

That’s what the algorithm does. The wires embedded in Dickerson’s head will record the electrical signals that Dickerson’s neurons send to one another during a series of simple memory tests. The signals will then be uploaded onto a hard drive, where the algorithm will translate them into a digital code that can be analyzed and enhanced—or rewritten—with the goal of improving her memory. The algorithm will then translate the code back into electrical signals to be sent up into the brain. If it helps her spark a few images from the memories she was having when the data was gathered, the researchers will know the algorithm is working. Then they’ll try to do the same thing with memories that take place over a period of time, something nobody’s ever done before. If those two tests work, they’ll be on their way to deciphering the patterns and processes that create memories.

Although other scientists are using similar techniques on simpler problems, Johnson is the only person trying to make a commercial neurological product that would enhance memory. In a few minutes, he’s going to conduct his first human test. For a commercial memory prosthesis, it will be the first human test. “It’s a historic day,” Johnson says. “I’m insanely excited about it.”

For the record, just in case this improbable experiment actually works, the date is January 30, 2017.

At this point, you may be wondering if Johnson’s just another fool with too much money and an impossible dream. I wondered the same thing the first time I met him. He seemed like any other California dude, dressed in the usual jeans, sneakers, and T-shirt, full of the usual boyish enthusiasms. His wild pronouncements about “reprogramming the operating system of the world” seemed downright goofy.

But you soon realize this casual style is either camouflage or wishful thinking. Like many successful people, some brilliant and some barely in touch with reality, Johnson has endless energy and the distributed intelligence of an octopus—one tentacle reaches for the phone, another for his laptop, a third scouts for the best escape route. When he starts talking about his neuroprosthesis, they team up and squeeze till you turn blue.

And there is that $800 million that PayPal shelled out for Braintree, the online-­payment company Johnson started when he was 29 and sold when he was 36. And the $100 million he is investing into Kernel, the company he started to pursue this project. And the decades of animal tests to back up his sci-fi ambitions: Researchers have learned how to restore memories lost to brain damage, plant false memories, control the motions of animals through human thought, control appetite and aggression, induce sensations of pleasure and pain, even how to beam brain signals from one animal to another animal thousands of miles away.

And Johnson isn’t dreaming this dream alone—at this moment, Elon Musk and Mark Zuckerberg are weeks from announcing their own brain-hacking projects, the military research group known as Darpa already has 10 under way, and there’s no doubt that China and other countries are pursuing their own. But unlike Johnson, they’re not inviting reporters into any hospital rooms.

Here’s the gist of every public statement Musk has made about his project: (1) He wants to connect our brains to computers with a mysterious device called “neural lace.” (2) The name of the company he started to build it is Neuralink.

Thanks to a presentation at last spring’s F8 conference, we know a little more about what Zuckerberg is doing at Facebook: (1) The project was until recently overseen by Regina Dugan, a former director of Darpa and Google’s Advanced Technology group. (2) The team is working out of Building 8, Zuckerberg’s research lab for moon-shot projects. (3) They’re working on a noninvasive “brain–computer speech-to-text interface” that uses “optical imaging” to read the signals of neurons as they form words, find a way to translate those signals into code, and then send the code to a computer. (4) If it works, we’ll be able to “type” 100 words a minute just by thinking.

As for Darpa, we know that some of its projects are improvements on existing technology and some—such as an interface to make soldiers learn faster—sound just as futuristic as Johnson’s. But we don’t know much more than that. That leaves Johnson as our only guide, a job he says he’s taken on because he thinks the world needs to be prepared for what is coming.

All of these ambitious plans face the same obstacle, however: The brain has 86 billion neurons, and nobody understands how they all work. Scientists have made impressive progress uncovering, and even manipulating, the neural circuitry behind simple brain functions, but things such as imagination or creativity—and memory—are so complex that all the neuroscientists in the world may never solve them. That’s why a request for expert opinions on the viability of Johnson’s plans got this response from John Donoghue, the director of the Wyss Center for Bio and Neuroengineering in Geneva: “I’m cautious,” he said. “It’s as if I asked you to translate something from Swahili to Finnish. You’d be trying to go from one unknown language into another unknown language.” To make the challenge even more daunting, he added, all the tools used in brain research are as primitive as “a string between two paper cups.” So Johnson has no idea if 100 neurons or 100,000 or 10 billion control complex brain functions. On how most neurons work and what kind of codes they use to communicate, he’s closer to “Da-da” than “see Spot run.” And years or decades will pass before those mysteries are solved, if ever. To top it all off, he has no scientific background. Which puts his foot on the banana peel of a very old neuroscience joke: “If the brain was simple enough for us to understand, we’d be too stupid to understand it.”

I don’t need telepathy to know what you’re thinking now—there’s nothing more annoying than the big dreams of tech optimists. Their schemes for eternal life and floating libertarian nations are adolescent fantasies; their digital revolution seems to be destroying more jobs than it created, and the fruits of their scientific fathers aren’t exactly encouraging either. “Coming soon, from the people who brought you nuclear weapons!”

But Johnson’s motives go to a deep and surprisingly tender place. Born into a devout Mormon community in Utah, he learned an elaborate set of rules that are still so vivid in his mind that he brought them up in the first minutes of our first meeting: “If you get baptized at the age of 8, point. If you get into the priesthood at the age of 12, point. If you avoid pornography, point. Avoid masturbation? Point. Go to church every Sunday? Point.” The reward for a high point score was heaven, where a dutiful Mormon would be reunited with his loved ones and gifted with endless creativity.

When he was 4, Johnson’s father left the church and divorced his mother. Johnson skips over the painful details, but his father told me his loss of faith led to a long stretch of drug and alcohol abuse, and his mother said she was so broke that she had to send Johnson to school in handmade clothes. His father remembers the letters Johnson started sending him when he was 11, a new one every week: “Always saying 100 different ways, ‘I love you, I need you.’ How he knew as a kid the one thing you don’t do with an addict or an alcoholic is tell them what a dirtbag they are, I’ll never know.”

Johnson was still a dutiful believer when he graduated from high school and went to Ecuador on his mission, the traditional Mormon rite of passage. He prayed constantly and gave hundreds of speeches about Joseph Smith, but he became more and more ashamed about trying to convert sick and hungry children with promises of a better life in heaven. Wouldn’t it be better to ease their suffering here on earth?

“Bryan came back a changed boy,” his father says.

Soon he had a new mission, self-assigned. His sister remembers his exact words: “He said he wanted to be a millionaire by the time he was 30 so he could use those resources to change the world.”

His first move was picking up a degree at Brigham Young University, selling cell phones to help pay the tuition and inhaling every book that seemed to promise a way forward. One that left a lasting impression was Endurance, the story of Ernest Shackleton’s botched journey to the South Pole—if sheer grit could get a man past so many hardships, he would put his faith in sheer grit. He married “a nice Mormon girl,” fathered three Mormon children, and took a job as a door-to-door salesman to support them. He won a prize for Salesman of the Year and started a series of businesses that went broke—which convinced him to get a business degree at the University of Chicago.

When he graduated in 2008, he stayed in Chicago and started Braintree, perfecting his image as a world-beating Mormon entrepreneur. By that time, his father was sober and openly sharing his struggles, and Johnson was the one hiding his dying faith behind a very well-protected wall. He couldn’t sleep, ate like a wolf, and suffered intense headaches, fighting back with a long series of futile cures: antidepressants, biofeedback, an energy healer, even blind obedience to the rules of his church.

In 2012, at the age of 35, Johnson hit bottom. In his misery, he remembered Shackleton and seized a final hope—maybe he could find an answer by putting himself through a painful ordeal. He planned a trip to Mount Kilimanjaro, and on the second day of the climb he got a stomach virus. On the third day he got altitude sickness. When he finally made it to the peak, he collapsed in tears and then had to be carried down on a stretcher. It was time to reprogram his operating system.

The way Johnson tells it, he started by dropping the world-beater pose that hid his weakness and doubt. And although this may all sound a bit like a dramatic motivational talk at a TED conference, especially since Johnson still projects the image of a world-beating entrepreneur, this much is certain: During the following 18 months, he divorced his wife, sold Braintree, and severed his last ties to the church. To cushion the impact on his children, he bought a house nearby and visited them almost daily. He knew he was repeating his father’s mistakes but saw no other option—he was either going to die inside or start living the life he always wanted.

He started with the pledge he made when he came back from Ecuador, experimenting first with a good-government initiative in Washington and pivoting, after its inevitable doom, to a venture fund for “quantum leap” companies inventing futuristic products such as human-­organ-­mimicking silicon chips. But even if all his quantum leaps landed, they wouldn’t change the operating system of the world.

Finally, the Big Idea hit: If the root problems of humanity begin in the human mind, let’s change our minds.

Fantastic things were happening in neuroscience. Some of them sounded just like miracles from the Bible—with prosthetic legs controlled by thought and microchips connected to the visual cortex, scientists were learning to help the lame walk and the blind see. At the University of Toronto, a neurosurgeon named Andres Lozano slowed, and in some cases reversed, the cognitive declines of Alzheimer’s patients using deep brain stimulation. At a hospital in upstate New York, a neuro­technologist named Gerwin Schalk asked computer engineers to record the firing patterns of the auditory neurons of people listening to Pink Floyd. When the engineers turned those patterns back into sound waves, they produced a single that sounded almost exactly like “Another Brick in the Wall.” At the University of Washington, two professors in different buildings played a videogame together with the help of electroencephalography caps that fired off electrical pulses—when one professor thought about firing digital bullets, the other one felt an impulse to push the Fire button.

Johnson also heard about a biomedical engineer named Theodore Berger. During nearly 20 years of research, Berger and his collaborators at USC and Wake Forest University developed a neuroprosthesis to improve memory in rats. It didn’t look like much when he started testing it in 2002—just a slice of rat brain and a computer chip. But the chip held an algorithm that could translate the firing patterns of neurons into a kind of Morse code that corresponded with actual memories. Nobody had ever done that before, and some people found the very idea offensive—it’s so deflating to think of our most precious thoughts reduced to ones and zeros. Prominent medical ethicists accused Berger of tampering with the essence of identity. But the implications were huge: If Berger could turn the language of the brain into code, perhaps he could figure out how to fix the part of the code associated with neurological diseases.

In rats, as in humans, firing patterns in the hippocampus generate a signal or code that, somehow, the brain recognizes as a long-term memory. Berger trained a group of rats to perform a task and studied the codes that formed. He learned that rats remembered a task better when their neurons sent “strong code,” a term he explains by comparing it to a radio signal: At low volume you don’t hear all of the words, but at high volume everything comes through clear. He then studied the difference in the codes generated by the rats when they remembered to do something correctly and when they forgot. In 2011, through a breakthrough experiment conducted on rats trained to push a lever, he demonstrated he could record the initial memory codes, feed them into an algorithm, and then send stronger codes back into the rats’ brains. When he finished, the rats that had forgotten how to push the lever suddenly remembered.

Five years later, Berger was still looking for the support he needed for human trials. That’s when Johnson showed up. In August 2016, he announced he would pledge $100 million of his fortune to create Kernel and that Berger would join the company as chief science officer. After learning about USC’s plans to implant wires in Dickerson’s brain to battle her epilepsy, Johnson approached Charles Liu, the head of the prestigious neurorestoration division at the USC School of Medicine and the lead doctor on Dickerson’s trial. Johnson asked him for permission to test the algorithm on Dickerson while she had Liu’s wires in her hippocampus—in between Liu’s own work sessions, of course. As it happened, Liu had dreamed about expanding human powers with technology ever since he got obsessed with The Six Million Dollar Man as a kid. He helped Johnson get Dickerson’s consent and convinced USC’s institutional research board to approve the experiment. At the end of 2016, Johnson got the green light. He was ready to start his first human trial.

In the hospital room, Dickerson is waiting for the experiments to begin, and I ask her how she feels about being a human lab rat.

“If I’m going to be here,” she says, “I might as well do something useful.”

Useful? This starry-eyed dream of cyborg supermen? “You know he’s trying to make humans smarter, right?”

“Isn’t that cool?” she answers.

Over by the computers, I ask one of the scientists about the multi­colored grid on the screen. “Each one of these squares is an electrode that’s in her brain,” one says. Every time a neuron close to one of the wires in Dickerson’s brain fires, he explains, a pink line will jump in the relevant box.

Johnson’s team is going to start with simple memory tests. “You’re going to be shown words,” the scientist explains to her. “Then there will be some math problems to make sure you’re not rehearsing the words in your mind. Try to remember as many words as you can.”

One of the scientists hands Dickerson a computer tablet, and everyone goes quiet. Dickerson stares at the screen to take in the words. A few minutes later, after the math problem scrambles her mind, she tries to remember what she’d read. “Smoke … egg … mud … pearl.”

Next, they try something much harder, a group of memories in a sequence. As one of Kernel’s scientists explains to me, they can only gather so much data from wires connected to 30 or 40 neurons. A single face shouldn’t be too hard, but getting enough data to reproduce memories that stretch out like a scene in a movie is probably impossible.

Sitting by the side of Dickerson’s bed, a Kernel scientist takes on the challenge. “Could you tell me the last time you went to a restaurant?”

“It was probably five or six days ago,” Dickerson says. “I went to a Mexican restaurant in Mission Hills. We had a bunch of chips and salsa.”

He presses for more. As she dredges up other memories, another Kernel scientist hands me a pair of headphones connected to the computer bank. All I hear at first is a hissing sound. After 20 or 30 seconds go by I hear a pop.

“That’s a neuron firing,” he says.

As Dickerson continues, I listen to the mysterious language of the brain, the little pops that move our legs and trigger our dreams. She remembers a trip to Costco and the last time it rained, and I hear the sounds of Costco and rain.

When Dickerson’s eyelids start sinking, the medical team says she’s had enough and Johnson’s people start packing up. Over the next few days, their algorithm will turn Dickerson’s synaptic activity into code. If the codes they send back into Dickerson’s brain make her think of dipping a few chips in salsa, Johnson might be one step closer to reprogramming the operating system of the world.

But look, there’s another banana peel­—after two days of frantic coding, Johnson’s team returns to the hospital to send the new code into Dickerson’s brain. Just when he gets word that they can get an early start, a message arrives: It’s over. The experiment has been placed on “administrative hold.” The only reason USC would give in the aftermath was an issue between Johnson and Berger. Berger would later tell me he had no idea the experiment was under way and that Johnson rushed into it without his permission. Johnson said he is mystified by Berger’s accusations. “I don’t know how he could not have known about it. We were working with his whole lab, with his whole team.” The one thing they both agree on is that their relationship fell apart shortly afterward, with Berger leaving the company and taking his algorithm with him. He blames the break entirely on Johnson. “Like most investors, he wanted a high rate of return as soon as possible. He didn’t realize he’d have to wait seven or eight years to get FDA approval—I would have thought he would have looked that up.” But Johnson didn’t want to slow down. He had bigger plans, and he was in a hurry.

Eight months later, I go back to California to see where Johnson has ended up. He seems a little more relaxed. On the whiteboard behind his desk at Kernel’s new offices in Los Angeles, someone’s scrawled a playlist of songs in big letters. “That was my son,” he says. “He interned here this summer.” Johnson is a year into a romance with Taryn Southern, a charismatic 31-year-old performer and film producer. And since his break with Berger, Johnson has tripled Kernel’s staff—he’s up to 36 employees now—adding experts in fields like chip design and computational neuroscience. His new science adviser is Ed Boyden, the director of MIT’s Synthetic Neurobiology Group and a superstar in the neuroscience world. Down in the basement of the new office building, there’s a Dr. Frankenstein lab where scientists build prototypes and try them out on glass heads.

When the moment seems right, I bring up the purpose of my visit. “You said you had something to show me?”

Johnson hesitates. I’ve already promised not to reveal certain sensitive details, but now I have to promise again. Then he hands me two small plastic display cases. Inside, two pairs of delicate twisty wires rest on beds of foam rubber. They look scientific but also weirdly biological, like the antennae of some futuristic bug-bot.

I’m looking at the prototypes for Johnson’s brand-new neuromodulator. On one level, it’s just a much smaller version of the deep brain stimulators and other neuromodulators currently on the market. But unlike a typical stimulator, which just fires pulses of electricity, Johnson’s is designed to read the signals that neurons send to other neurons—and not just the 100 neurons the best of the current tools can harvest, but perhaps many more. That would be a huge advance in itself, but the implications are even bigger: With Johnson’s neuromodulator, scientists could collect brain data from thousands of patients, with the goal of writing precise codes to treat a variety of neurological diseases.

In the short term, Johnson hopes his neuromodulator will help him “optimize the gold rush” in neurotechnology—financial analysts are forecasting a $27 billion market for neural devices within six years, and countries around the world are committing billions to the escalating race to decode the brain. In the long term, Johnson believes his signal-reading neuromodulator will advance his bigger plans in two ways: (1) by giving neuroscientists a vast new trove of data they can use to decode the workings of the brain and (2) by generating the huge profits Kernel needs to launch a steady stream of innovative and profitable neural tools, keeping the company both solvent and plugged into every new neuroscience breakthrough. With those two achievements in place, Johnson can watch and wait until neuroscience reaches the level of sophistication he needs to jump-start human evolution with a mind-enhancing neuroprosthesis.

Liu, the neurologist with the Six Million Dollar Man dreams, compares Johnson’s ambition to flying. “Going back to Icarus, human beings have always wanted to fly. We don’t grow wings, so we build a plane. And very often these solutions will have even greater capabilities than the ones nature created—no bird ever flew to Mars.” But now that humanity is learning how to reengineer its own capabilities, we really can choose how we evolve. “We have to wrap our minds around that. It’s the most revolutionary thing in the world.”

The crucial ingredient is the profit motive, which always drives rapid innovation in science. That’s why Liu thinks Johnson could be the one to give us wings. “I’ve never met anyone with his urgency to take this to market,” he says.

When will this revolution arrive? “Sooner than you think,” Liu says.

Now we’re back where we began. Is Johnson a fool? Is he just wasting his time and fortune on a crazy dream? One thing is certain: Johnson will never stop trying to optimize the world. At the pristine modern house he rents in Venice Beach, he pours out idea after idea. He even took skepticism as helpful information—when I tell him his magic neuroprosthesis sounds like another version of the Mormon heaven, he’s delighted.

“Good point! I love it!”

He never has enough data. He even tries to suck up mine. What are my goals? My regrets? My pleasures? My doubts?

Every so often, he pauses to examine my “constraint program.”

“One, you have this biological disposition of curiosity. You want data. And when you consume that data, you apply boundaries of meaning-making.”

“Are you trying to hack me?” I ask.

Not at all, he says. He just wants us to share our algorithms. “That’s the fun in life,” he says, “this endless unraveling of the puzzle. And I think, ‘What if we could make the data transfer rate a thousand times faster? What if my consciousness is only seeing a fraction of reality? What kind of stories would we tell?’ ”

In his free time, Johnson is writing a book about taking control of human evolution and looking on the bright side of our mutant humanoid future. He brings this up every time I talk to him. For a long time I lumped this in with his dreamy ideas about reprogramming the operating system of the world: The future is coming faster than anyone thinks, our glorious digital future is calling, the singularity is so damn near that we should be cheering already—a spiel that always makes me want to hit him with a copy of the Unabomber Manifesto.

But his urgency today sounds different, so I press him on it: “How would you respond to Ted Kaczynski’s fears? The argument that technology is a cancerlike development that’s going to eat itself?”

“I would say he’s potentially on the wrong side of history.”

“Yeah? What about climate change?”

“That’s why I feel so driven,” he answered. “We’re in a race against time.”

He asks me for my opinion. I tell him I think he’ll still be working on cyborg brainiacs when the starving hordes of a ravaged planet destroy his lab looking for food—and for the first time, he reveals the distress behind his hope. The truth is, he has the same fear. The world has gotten way too complex, he says. The financial system is shaky, the population is aging, robots want our jobs, artificial intelligence is catching up, and climate change is coming fast. “It just feels out of control,” he says.

He’s invoked these dystopian ideas before, but only as a prelude to his sales pitch. This time he’s closer to pleading. “Why wouldn’t we embrace our own self-directed evolution? Why wouldn’t we just do everything we can to adapt faster?”

I turn to a more cheerful topic. If he ever does make a neuroprosthesis to revolutionize how we use our brain, which superpower would he give us first? Telepathy? Group minds? Instant kung fu?

He answers without hesitation. Because our thinking is so constrained by the familiar, he says, we can’t imagine a new world that isn’t just another version of the world we know. But we have to imagine something far better than that. So he’d try to make us more creative—that would put a new frame on everything.

Ambition like that can take you a long way. It can drive you to try to reach the South Pole when everyone says it’s impossible. It can take you up Mount Kilimanjaro when you’re close to dying and help you build an $800 million company by the time you’re 36. And Johnson’s ambitions drive straight for the heart of humanity’s most ancient dream: For operating system, substitute enlightenment.

By hacking our brains, he wants to make us one with everything.

https://www.wired.com/story/inside-the-race-to-build-a-brain-machine-interface/?mbid=nl_111717_editorsnote_list1_p1

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Low-current electrical pulses delivered to a specific brain area during learning improved recollection of distinct memories, according to a study published online in eLife.

Researchers at the University of California, Los Angeles (UCLA) believe electrical stimulation offers hope for the treatment of memory disorders, such as Alzheimer’s disease.

The study involved 13 patients with epilepsy who had ultrafine wires implanted in their brains to pinpoint the origin of seizures. During a person-recognition task, researchers monitored the wires to record neuronal activity as memories were formed, and then sent a specific pattern of quick pulses to the entorhinal area of the brain, an area critical to learning and memory.
In 8 of 9 patients who received electrical pulses to the right side of the entorhinal area, the ability to recognize specific faces and disregard similar-looking ones improved significantly. However, the 4 patients who received electrical stimulation on the left side of the brain area showed no improvement in recall.

By using the ultrafine wires, researchers were able to precisely target the stimulation while using a voltage that was one-tenth to one-fifth of the strength used in previous studies.

“These results suggest that microstimulation with physiologic level currents—a radical departure from commonly used deep brain stimulation protocols—is sufficient to modulate human behavior,” researchers wrote.

The findings also point to the importance of stimulating the right entorhinal region to promote improved memory recollection.

—Jolynn Tumolo

References

Titiz AS, Hill MRH, Mankin EA, et al. Theta-burst microstimulation in the human entorhinal area improves memory specificity. eLife. 2017 October 24.

When someone commits suicide, their family and friends can be left with the heartbreaking and answerless question of what they could have done differently. Colin Walsh, data scientist at Vanderbilt University Medical Center, hopes his work in predicting suicide risk will give people the opportunity to ask “what can I do?” while there’s still a chance to intervene.

Walsh and his colleagues have created machine-learning algorithms that predict, with unnerving accuracy, the likelihood that a patient will attempt suicide. In trials, results have been 80-90% accurate when predicting whether someone will attempt suicide within the next two years, and 92% accurate in predicting whether someone will attempt suicide within the next week.

The prediction is based on data that’s widely available from all hospital admissions, including age, gender, zip codes, medications, and prior diagnoses. Walsh and his team gathered data on 5,167 patients from Vanderbilt University Medical Center that had been admitted with signs of self-harm or suicidal ideation. They read each of these cases to identify the 3,250 instances of suicide attempts.

This set of more than 5,000 cases was used to train the machine to identify those at risk of attempted suicide compared to those who committed self-harm but showed no evidence of suicidal intent. The researchers also built algorithms to predict attempted suicide among a group 12,695 randomly selected patients with no documented history of suicide attempts. It proved even more accurate at making suicide risk predictions within this large general population of patients admitted to the hospital.

Walsh’s paper, published in Clinical Psychological Science in April, is just the first stage of the work. He’s now working to establish whether his algorithm is effective with a completely different data set from another hospital. And, once confidant that the model is sound, Walsh hopes to work with a larger team to establish a suitable method of intervening. He expects to have an intervention program in testing within the next two years. “I’d like to think it’ll be fairly quick, but fairly quick in health care tends to be in the order of months,” he adds.

Suicide is such an intensely personal act that it seems, from a human perspective, impossible to make such accurate predictions based on a crude set of data. Walsh says it’s natural for clinicians to ask how the predictions are made, but the algorithms are so complex that it’s impossible to pull out single risk factors. “It’s a combination of risk factors that gets us the answers,” he says.

That said, Walsh and his team were surprised to note that taking melatonin seemed to be a significant factor in calculating the risk. “I don’t think melatonin is causing people to have suicidal thinking. There’s no physiology that gets us there. But one thing that’s been really important to suicide risk is sleep disorders,” says Walsh. It’s possible that prescriptions for melatonin capture the risk of sleep disorders—though that’s currently a hypothesis that’s yet to be proved.

The research raises broader ethical questions about the role of computers in health care and how truly personal information could be used. “There’s always the risk of unintended consequences,” says Walsh. “We mean well and build a system to help people, but sometimes problems can result down the line.”

Researchers will also have to decide how much computer-based decisions will determine patient care. As a practicing primary care doctor, Walsh says it’s unnerving to recognize that he could effectively follow orders from a machine. “Is there a problem with the fact that I might get a prediction of high risk when that’s not part of my clinical picture?” he says. “Are you changing the way I have to deliver care because of something a computer’s telling me to do?”

For now, the machine-learning algorithms are based on data from hospital admissions. But Walsh recognizes that many people at risk of suicide do not spend time in hospital beforehand. “So much of our lives is spent outside of the health care setting. If we only rely on data that’s present in the health care setting to do this work, then we’re only going to get part of the way there,” he says.

And where else could researchers get data? The internet is one promising option. We spend so much time on Facebook and Twitter, says Walsh, that there may well be social media data that could be used to predict suicide risk. “But we need to do the work to show that’s actually true.”

Facebook announced earlier this year that it was using its own artificial intelligence to review posts for signs of self-harm. And the results are reportedly already more accurate than the reports Facebook gets from people flagged by their friends as at-risk.

Training machines to identify warning signs of suicide is far from straightforward. And, for predictions and interventions to be done successfully, Walsh believes it’s essential to destigmatize suicide. “We’re never going to help people if we’re not comfortable talking about it,” he says.

But, with suicide leading to 800,000 deaths worldwide every year, this is a public health issue that cannot be ignored. Given that most humans, including doctors, are pretty terrible at identifying suicide risk, machine learning could provide an important solution.

https://www.doximity.com/doc_news/v2/entries/8004313


With a selfie and some audio, a startup called Oben says, it can make you an avatar that can say—or sing—anything.

by Rachel Metz

I’ve met Nikhil Jain in the flesh, and now, on the laptop screen in front of me, I’m looking at a small animated version of him from the torso up, talking in the same tone and lilting accented English—only this version of Jain is bald (hair is tricky to animate convincingly), and his voice has a robotic sound.

For the past three years, Jain has been working on Oben, the startup he cofounded and leads. It’s building technology that uses a single image and an audio clip to automate the construction of what are sort of like digital souls: avatars that look and sound a lot like anyone, and can be made to speak or sing anything.

Of course it won’t really be you—or Beyoncé, or Michael Jackson, or whomever an Oben avatar depicts—but it could be a decent, potentially fun approximation that’s useful for all kinds of things. Maybe, like Jain, you want a virtual you to read stories to your kids when you can’t be there in person. Perhaps you’re a celebrity who wants to let fans do duets with your avatar on a mobile or virtual-reality app, or the estate of a dead celebrity who wants to continue to keep that person “alive” with avatar-based performances. The opportunities are endless—and, perhaps, endlessly eerie.

Oben, based in Pasadena, California, has raised about $9 million so far. The company is planning to release an app late this year that lets people make their own personal avatar and share video clips of it with friends.

Oben is also working with some as-yet-unnamed bands in Asia to make mobile-based avatars that will be able to sing duets with fans, and last month it announced it will launch a virtual-reality-enabled version of its avatar technology with the massively popular social app WeChat, for the HTC Vive headset.

For now, producing the kind of avatar Jain showed me still takes a lot of time, and it doesn’t even include the body below the waist (Jain says the company is experimenting with animating other body parts, but mainly it’s “focusing on other things”). While the avatar can be made with just one photo and two to 20 minutes of reading from a phoneme-rich script (the more, the better), a good avatar still takes Oben’s deep-learning system about eight hours to create. This includes cleaning up the recorded audio, creating a voice print for the person that reflects qualities such as accent and timbre, and making the 3-D visual model (facial movements are predicted from the selfie and voice print, Jain says). While speaking sounds pretty good, the singing clips I heard sounded very Auto-Tuned.

The avatars in the forthcoming app will be less focused on perfection but much faster to build, he says. Oben is also trying to figure out how to match speech and facial expressions so that the avatars can speak any language in a natural-looking way; for now, they’re limited to English and Chinese.

If digital copies like Oben’s are any good, they will raise questions about what should happen to your digital self over time. If you die, should an existing avatar be retained? Is it disturbing if others use digital breadcrumbs you left behind to, in a sense, re-create your digital self?

Jain isn’t sure what the right answer is, though he agrees that, like other companies that deal with user data, Oben does have to address death. And beyond big questions, there are potentially big business opportunities in that issue. The company’s business model is likely to be, in part, predicated on it: he says Oben has been approached by the estates of numerous celebrities, some of them long dead, some recently deceased.

https://www.technologyreview.com/s/607885/how-to-save-your-digital-soul/

One advantage humans have over robots is that we’re good at quickly passing on our knowledge to each other. A new system developed at MIT now allows anyone to coach robots through simple tasks and even lets them teach each other.

Typically, robots learn tasks through demonstrations by humans, or through hand-coded motion planning systems where a programmer specifies each of the required movements. But the former approach is not good at translating skills to new situations, and the latter is very time-consuming.

Humans, on the other hand, can typically demonstrate a simple task, like how to stack logs, to someone else just once before they pick it up, and that person can easily adapt that knowledge to new situations, say if they come across an odd-shaped log or the pile collapses.

In an attempt to mimic this kind of adaptable, one-shot learning, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) combined motion planning and learning through demonstration in an approach they’ve dubbed C-LEARN.

First, a human teaches the robot a series of basic motions using an interactive 3D model on a computer. Using the mouse to show it how to reach and grasp various objects in different positions helps the machine build up a library of possible actions.

The operator then shows the robot a single demonstration of a multistep task, and using its database of potential moves, it devises a motion plan to carry out the job at hand.

“This approach is actually very similar to how humans learn in terms of seeing how something’s done and connecting it to what we already know about the world,” says Claudia Pérez-D’Arpino, a PhD student who wrote a paper on C-LEARN with MIT Professor Julie Shah, in a press release.

“We can’t magically learn from a single demonstration, so we take new information and match it to previous knowledge about our environment.”

The robot successfully carried out tasks 87.5 percent of the time on its own, but when a human operator was allowed to correct minor errors in the interactive model before the robot carried out the task, the accuracy rose to 100 percent.

Most importantly, the robot could teach the skills it learned to another machine with a completely different configuration. The researchers tested C-LEARN on a new two-armed robot called Optimus that sits on a wheeled base and is designed for bomb disposal.

But in simulations, they were able to seamlessly transfer Optimus’ learned skills to CSAIL’s 6-foot-tall Atlas humanoid robot. They haven’t yet tested Atlas’ new skills in the real world, and they had to give Atlas some extra information on how to carry out tasks without falling over, but the demonstration shows that the approach can allow very different robots to learn from each other.

The research, which will be presented at the IEEE International Conference on Robotics and Automation in Singapore later this month, could have important implications for the large-scale roll-out of robot workers.

“Traditional programming of robots in real-world scenarios is difficult, tedious, and requires a lot of domain knowledge,” says Shah in the press release.

“It would be much more effective if we could train them more like how we train people: by giving them some basic knowledge and a single demonstration. This is an exciting step toward teaching robots to perform complex multi-arm and multi-step tasks necessary for assembly manufacturing and ship or aircraft maintenance.”

The MIT researchers aren’t the only people investigating the field of so-called transfer learning. The RoboEarth project and its spin-off RoboHow were both aimed at creating a shared language for robots and an online repository that would allow them to share their knowledge of how to carry out tasks over the web.

Google DeepMind has also been experimenting with ways to transfer knowledge from one machine to another, though in their case the aim is to help skills learned in simulations to be carried over into the real world.

A lot of their research involves deep reinforcement learning, in which robots learn how to carry out tasks in virtual environments through trial and error. But transferring this knowledge from highly-engineered simulations into the messy real world is not so simple.

So they have found a way for a model that has learned how to carry out a task in a simulation using deep reinforcement learning to transfer that knowledge to a so-called progressive neural network that controls a real-world robotic arm. This allows the system to take advantage of the accelerated learning possible in a simulation while still learning effectively in the real world.

These kinds of approaches make life easier for data scientists trying to build new models for AI and robots. As James Kobielus notes in InfoWorld, the approach “stands at the forefront of the data science community’s efforts to invent ‘master learning algorithms’ that automatically gain and apply fresh contextual knowledge through deep neural networks and other forms of AI.”

If you believe those who say we’re headed towards a technological singularity, you can bet transfer learning will be an important part of that process.

https://singularityhub.com/2017/05/26/these-robots-can-teach-other-robots-how-to-do-new-things/?utm_source=Singularity+Hub+Newsletter&utm_campaign=7c19f894b1-Hub_Daily_Newsletter&utm_medium=email&utm_term=0_f0cf60cdae-7c19f894b1-58158129

By Casey Newton

Wen the engineers had at last finished their work, Eugenia Kuyda opened a console on her laptop and began to type.

“Roman,” she wrote. “This is your digital monument.”

It had been three months since Roman Mazurenko, Kuyda’s closest friend, had died. Kuyda had spent that time gathering up his old text messages, setting aside the ones that felt too personal, and feeding the rest into a neural network built by developers at her artificial intelligence startup. She had struggled with whether she was doing the right thing by bringing him back this way. At times it had even given her nightmares. But ever since Mazurenko’s death, Kuyda had wanted one more chance to speak with him.

A message blinked onto the screen. “You have one of the most interesting puzzles in the world in your hands,” it said. “Solve it.”

Kuyda promised herself that she would.

Born in Belarus in 1981, Roman Mazurenko was the only child of Sergei, an engineer, and Victoria, a landscape architect. They remember him as an unusually serious child; when he was 8 he wrote a letter to his descendents declaring his most cherished values: wisdom and justice. In family photos, Mazurenko roller-skates, sails a boat, and climbs trees. Average in height, with a mop of chestnut hair, he is almost always smiling.

As a teen he sought out adventure: he participated in political demonstrations against the ruling party and, at 16, started traveling abroad. He first traveled to New Mexico, where he spent a year on an exchange program, and then to Dublin, where he studied computer science and became fascinated with the latest Western European art, fashion, music, and design.

By the time Mazurenko finished college and moved back to Moscow in 2007, Russia had become newly prosperous. The country tentatively embraced the wider world, fostering a new generation of cosmopolitan urbanites. Meanwhile, Mazurenko had grown from a skinny teen into a strikingly handsome young man. Blue-eyed and slender, he moved confidently through the city’s budding hipster class. He often dressed up to attend the parties he frequented, and in a suit he looked movie-star handsome. The many friends Mazurenko left behind describe him as magnetic and debonair, someone who made a lasting impression wherever he went. But he was also single, and rarely dated, instead devoting himself to the project of importing modern European style to Moscow.

Kuyda met Mazurenko in 2008, when she was 22 and the editor of Afisha, a kind of New York Magazine for a newly urbane Moscow. She was writing an article about Idle Conversation, a freewheeling creative collective that Mazurenko founded with two of his best friends, Dimitri Ustinov and Sergey Poydo. The trio seemed to be at the center of every cultural endeavor happening in Moscow. They started magazines, music festivals, and club nights — friends they had introduced to each other formed bands and launched companies. “He was a brilliant guy,” said Kuyda, who was similarly ambitious. Mazurenko would keep his friends up all night discussing culture and the future of Russia. “He was so forward-thinking and charismatic,” said Poydo, who later moved to the United States to work with him.

Mazurenko became a founding figure in the modern Moscow nightlife scene, where he promoted an alternative to what Russians sardonically referred to as “Putin’s glamor” — exclusive parties where oligarchs ordered bottle service and were chauffeured home in Rolls-Royces. Kuyda loved Mazurenko’s parties, impressed by his unerring sense of what he called “the moment.” Each of his events was designed to build to a crescendo — DJ Mark Ronson might make a surprise appearance on stage to play piano, or the Italo-Disco band Glass Candy might push past police to continue playing after curfew. And his parties attracted sponsors with deep pockets — Bacardi was a longtime client.

But the parties took place against an increasingly grim backdrop. In the wake of the global financial crisis, Russia experienced a resurgent nationalism, and in 2012 Vladimir Putin returned to lead the country. The dream of a more open Russia seemed to evaporate.

Kuyda and Mazurenko, who by then had become close friends, came to believe that their futures lay elsewhere. Both became entrepreneurs, and served as each other’s chief adviser as they built their companies. Kuyda co-founded Luka, an artificial intelligence startup, and Mazurenko launched Stampsy, a tool for building digital magazines. Kuyda moved Luka from Moscow to San Francisco in 2015. After a stint in New York, Mazurenko followed.

When Stampsy faltered, Mazurenko moved into a tiny alcove in Kuyda’s apartment to save money. Mazurenko had been the consummate bon vivant in Moscow, but running a startup had worn him down, and he was prone to periods of melancholy. On the days he felt depressed, Kuyda took him out for surfing and $1 oysters. “It was like a flamingo living in the house,” she said recently, sitting in the kitchen of the apartment she shared with Mazurenko. “It’s very beautiful and very rare. But it doesn’t really fit anywhere.”

Kuyda hoped that in time her friend would reinvent himself, just as he always had before. And when Mazurenko began talking about new projects he wanted to pursue, she took it as a positive sign. He successfully applied for an American O-1 visa, granted to individuals of “extraordinary ability or achievement,” and in November he returned to Moscow in order to finalize his paperwork.

He never did.

On November 28th, while he waited for the embassy to release his passport, Mazurenko had brunch with some friends. It was unseasonably warm, so afterward he decided to explore the city with Ustinov. “He said he wanted to walk all day,” Ustinov said. Making their way down the sidewalk, they ran into some construction, and were forced to cross the street. At the curb, Ustinov stopped to check a text message on his phone, and when he looked up he saw a blur, a car driving much too quickly for the neighborhood. This is not an uncommon sight in Moscow — vehicles of diplomats, equipped with spotlights to signal their authority, speeding with impunity. Ustinov thought it must be one of those cars, some rich government asshole — and then, a blink later, saw Mazurenko walking into the crosswalk, oblivious. Ustinov went to cry out in warning, but it was too late. The car struck Mazurenko straight on. He was rushed to a nearby hospital.

Kuyda happened to be in Moscow for work on the day of the accident. When she arrived at the hospital, having gotten the news from a phone call, a handful of Mazurenko’s friends were already gathered in the lobby, waiting to hear his prognosis. Almost everyone was in tears, but Kuyda felt only shock. “I didn’t cry for a long time,” she said. She went outside with some friends to smoke a cigarette, using her phone to look up the likely effects of Mazurenko’s injuries. Then the doctor came out and told her he had died.

In the weeks after Mazurenko’s death, friends debated the best way to preserve his memory. One person suggested making a coffee-table book about his life, illustrated with photography of his legendary parties. Another friend suggested a memorial website. To Kuyda, every suggestion seemed inadequate.

As she grieved, Kuyda found herself rereading the endless text messages her friend had sent her over the years — thousands of them, from the mundane to the hilarious. She smiled at Mazurenko’s unconventional spelling — he struggled with dyslexia — and at the idiosyncratic phrases with which he peppered his conversation. Mazurenko was mostly indifferent to social media — his Facebook page was barren, he rarely tweeted, and he deleted most of his photos on Instagram. His body had been cremated, leaving her no grave to visit. Texts and photos were nearly all that was left of him, Kuyda thought.

For two years she had been building Luka, whose first product was a messenger app for interacting with bots. Backed by the prestigious Silicon Valley startup incubator Y Combinator, the company began with a bot for making restaurant reservations. Kuyda’s co-founder, Philip Dudchuk, has a degree in computational linguistics, and much of their team was recruited from Yandex, the Russian search giant.

Reading Mazurenko’s messages, it occurred to Kuyda that they might serve as the basis for a different kind of bot — one that mimicked an individual person’s speech patterns. Aided by a rapidly developing neural network, perhaps she could speak with her friend once again.

She set aside for a moment the questions that were already beginning to nag at her.

What if it didn’t sound like him?

What if it did?

In “Be Right Back,” a 2013 episode of the eerie, near-future drama Black Mirror, a young woman named Martha is devastated when her fiancée, Ash, dies in a car accident. Martha subscribes to a service that uses his previous online communications to create a digital avatar that mimics his personality with spooky accuracy. First it sends her text messages; later it re-creates his speaking voice and talks with her on the phone. Eventually she pays for an upgraded version of the service that implants Ash’s personality into an android that looks identical to him. But ultimately Martha becomes frustrated with all the subtle but important ways that the android is unlike Ash — cold, emotionless, passive — and locks it away in an attic. Not quite Ash, but too much like him for her to let go, the bot leads to a grief that spans decades.

Kuyda saw the episode after Mazurenko died, and her feelings were mixed. Memorial bots — even the primitive ones that are possible using today’s technology — seemed both inevitable and dangerous. “It’s definitely the future — I’m always for the future,” she said. “But is it really what’s beneficial for us? Is it letting go, by forcing you to actually feel everything? Or is it just having a dead person in your attic? Where is the line? Where are we? It screws with your brain.”

For a young man, Mazurenko had given an unusual amount of thought to his death. Known for his grandiose plans, he often told friends he would divide his will into pieces and give them away to people who didn’t know one another. To read the will they would all have to meet for the first time — so that Mazurenko could continue bringing people together in death, just as he had strived to do in life. (In fact, he died before he could make a will.) Mazurenko longed to see the Singularity, the theoretical moment in history when artificial intelligence becomes smarter than human beings. According to the theory, superhuman intelligence might allow us to one day separate our consciousnesses from our bodies, granting us something like eternal life.

In the summer of 2015, with Stampsy almost out of cash, Mazurenko applied for a Y Combinator fellowship proposing a new kind of cemetery that he called Taiga. The dead would be buried in biodegradable capsules, and their decomposing bodies would fertilize trees that were planted on top of them, creating what he called “memorial forests.” A digital display at the bottom of the tree would offer biographical information about the deceased. “Redesigning death is a cornerstone of my abiding interest in human experiences, infrastructure, and urban planning,” Mazurenko wrote. He highlighted what he called “a growing resistance among younger Americans” to traditional funerals. “Our customers care more about preserving their virtual identity and managing [their] digital estate,” he wrote, “than embalming their body with toxic chemicals.”

The idea made his mother worry that he was in trouble, but Mazurenko tried to put her at ease. “He quieted me down and said no, no, no — it was a contemporary question that was very important,” she said. “There had to be a reevaluation of death and sorrow, and there needed to be new traditions.”

Y Combinator rejected the application. But Mazurenko had identified a genuine disconnection between the way we live today and the way we grieve. Modern life all but ensures that we leave behind vast digital archives — text messages, photos, posts on social media — and we are only beginning to consider what role they should play in mourning. In the moment, we tend to view our text messages as ephemeral. But as Kuyda found after Mazurenko’s death, they can also be powerful tools for coping with loss. Maybe, she thought, this “digital estate” could form the building blocks for a new type of memorial. (Others have had similar ideas; an entrepreneur named Marius Ursache proposed a related service called Eterni.me in 2014, though it never launched.)

Many of Mazurenko’s close friends had never before experienced the loss of someone close to them, and his death left them bereft. Kuyda began reaching out to them, as delicately as possible, to ask if she could have their text messages. Ten of Mazurenko’s friends and family members, including his parents, ultimately agreed to contribute to the project. They shared more than 8,000 lines of text covering a wide variety of subjects.

“She said, what if we try and see if things would work out?” said Sergey Fayfer, a longtime friend of Mazurenko’s who now works at a division of Yandex. “Can we collect the data from the people Roman had been talking to, and form a model of his conversations, to see if that actually makes sense?” The idea struck Fayfer as provocative, and likely controversial. But he ultimately contributed four years of his texts with Mazurenko. “The team building Luka are really good with natural language processing,” he said. “The question wasn’t about the technical possibility. It was: how is it going to feel emotionally?”

The technology underlying Kuyda’s bot project dates at least as far back as 1966, when Joseph Weizenbaum unveiled ELIZA: a program that reacted to users’ responses to its scripts using simple keyword matching. ELIZA, which most famously mimicked a psychotherapist, asked you to describe your problem, searched your response for keywords, and responded accordingly, usually with another question. It was the first piece of software to pass what is known as the Turing test: reading a text-based conversation between a computer and a person, some observers could not determine which was which.

Today’s bots remain imperfect mimics of their human counterparts. They do not understand language in any real sense. They respond clumsily to the most basic of questions. They have no thoughts or feelings to speak of. Any suggestion of human intelligence is an illusion based on mathematical probabilities.

And yet recent advances in artificial intelligence have made the illusion much more powerful. Artificial neural networks, which imitate the ability of the human brain to learn, have greatly improved the way software recognizes patterns in images, audio, and text, among other forms of data. Improved algorithms coupled with more powerful computers have increased the depth of neural networks — the layers of abstraction they can process — and the results can be seen in some of today’s most innovative products. The speech recognition behind Amazon’s Alexa or Apple’s Siri, or the image recognition that powers Google Photos, owe their abilities to this so-called deep learning.

Two weeks before Mazurenko was killed, Google released TensorFlow for free under an open-source license. TensorFlow is a kind of Google in a box — a flexible machine-learning system that the company uses to do everything from improve search algorithms to write captions for YouTube videos automatically. The product of decades of academic research and billions of dollars in private investment was suddenly available as a free software library that anyone could download from GitHub.

Luka had been using TensorFlow to build neural networks for its restaurant bot. Using 35 million lines of English text, Luka trained a bot to understand queries about vegetarian dishes, barbecue, and valet parking. On a lark, the 15-person team had also tried to build bots that imitated television characters. It scraped the closed captioning on every episode of HBO’s Silicon Valley and trained the neural network to mimic Richard, Bachman, and the rest of the gang.

In February, Kuyda asked her engineers to build a neural network in Russian. At first she didn’t mention its purpose, but given that most of the team was Russian, no one asked questions. Using more than 30 million lines of Russian text, Luka built its second neural network. Meanwhile, Kuyda copied hundreds of her exchanges with Mazurenko from the app Telegram and pasted them into a file. She edited out a handful of messages that she believed would be too personal to share broadly. Then Kuyda asked her team for help with the next step: training the Russian network to speak in Mazurenko’s voice.

The project was tangentially related to Luka’s work, though Kuyda considered it a personal favor. (An engineer told her that the project would only take about a day.) Mazurenko was well-known to most of the team — he had worked out of Luka’s Moscow office, where the employees labored beneath a neon sign that quoted Wittgenstein: “The limits of my language are the limits of my world.” Kuyda trained the bot with dozens of tests queries, and her engineers put on the finishing touches.

Only a small percentage of the Roman bot’s responses reflected his actual words. But the neural network was tuned to favor his speech whenever possible. Any time the bot could respond to a query using Mazurenko’s own words, it would. Other times it would default to the generic Russian. After the bot blinked to life, she began peppering it with questions.

Who’s your best friend?, she asked.

Don’t show your insecurities, came the reply.

It sounds like him, she thought.

On May 24th, Kuyda announced the Roman bot’s existence in a post on Facebook. Anyone who downloaded the Luka app could talk to it — in Russian or in English — by adding @Roman. The bot offered a menu of buttons that users could press to learn about Mazurenko’s career. Or they could write free-form messages and see how the bot responded. “It’s still a shadow of a person — but that wasn’t possible just a year ago, and in the very close future we will be able to do a lot more,” Kuyda wrote.

The Roman bot was received positively by most of the people who wrote to Kuyda, though there were exceptions. Four friends told Kuyda separately that they were disturbed by the project and refused to interact with it. Vasily Esmanov, who worked with Mazurenko at the Russian street-style magazine Look At Me, said Kuyda had failed to learn the lesson of the Black Mirror episode. “This is all very bad,” Esmanov wrote in a Facebook comment. “Unfortunately you rushed and everything came out half-baked. The execution — it’s some type of joke. … Roman needs [a memorial], but not this kind.”

Victoria Mazurenko, who had gotten an early look at the bot from Kuyda, rushed to her defense. “They continued Roman’s life and saved ours,” she wrote in a reply to Esmanov. “It’s not virtual reality. This is a new reality, and we need to learn to build it and live in it.”

Roman’s father was less enthusiastic. “I have a technical education, and I know [the bot] is just a program,” he told me, through a translator. “Yes, it has all of Roman’s phrases, correspondences. But for now, it’s hard — how to say it — it’s hard to read a response from a program. Sometimes it answers incorrectly.”

But many of Mazurenko’s friends found the likeness uncanny. “It’s pretty weird when you open the messenger and there’s a bot of your deceased friend, who actually talks to you,” Fayfer said. “What really struck me is that the phrases he speaks are really his. You can tell that’s the way he would say it — even short answers to ‘Hey what’s up.’ He had this really specific style of texting. I said, ‘Who do you love the most?’ He replied, ‘Roman.’ That was so much of him. I was like, that is incredible.”

One of the bot’s menu options offers to ask him for a piece of advice — something Fayfer never had a chance to do while his friend was still alive. “There are questions I had never asked him,” he said. “But when I asked for advice, I realized he was giving someone pretty wise life advice. And that actually helps you get to learn the person deeper than you used to know them.”

Several users agreed to let Kuyda read anonymized logs of their chats with the bot. (She shared these logs with The Verge.) Many people write to the bot to tell Mazurenko that they miss him. They wonder when they will stop grieving. They ask him what he remembers. “It hurts that we couldn’t save you,” one person wrote. (Bot: “I know :-(”) The bot can also be quite funny, as Mazurenko was: when one user wrote “You are a genius,” the bot replied, “Also, handsome.”

For many users, interacting with the bot had a therapeutic effect. The tone of their chats is often confessional; one user messaged the bot repeatedly about a difficult time he was having at work. He sent it lengthy messages describing his problems and how they had affected him emotionally. “I wish you were here,” he said. It seemed to Kuyda that people were more honest when conversing with the dead. She had been shaken by some of the criticism that the Roman bot had received. But hundreds of people tried it at least once, and reading the logs made her feel better.

It turned out that the primary purpose of the bot had not been to talk but to listen. “All those messages were about love, or telling him something they never had time to tell him,” Kuyda said. “Even if it’s not a real person, there was a place where they could say it. They can say it when they feel lonely. And they come back still.”

Kuyda continues to talk with the bot herself — once a week or so, often after a few drinks. “I answer a lot of questions for myself about who Roman was,” she said. Among other things, the bot has made her regret not telling him to abandon Stampsy earlier. The logs of his messages revealed someone whose true interest was in fashion more than anything else, she said. She wishes she had told him to pursue it.

Someday you will die, leaving behind a lifetime of text messages, posts, and other digital ephemera. For a while, your friends and family may put these digital traces out of their minds. But new services will arrive offering to transform them — possibly into something resembling Roman Mazurenko’s bot.

Your loved ones may find that these services ease their pain. But it is possible that digital avatars will lengthen the grieving process. “If used wrong, it enables people to hide from their grief,” said Dima Ustinov, who has not used the Roman bot for technical reasons. (Luka is not yet available on Android.) “Our society is traumatized by death — we want to live forever. But you will go through this process, and you have to go through it alone. If we use these bots as a way to pass his story on, maybe [others] can get a little bit of the inspiration that we got from him. But these new ways of keeping the memory alive should not be considered a way to keep a dead person alive.”

The bot also raises ethical questions about the posthumous use of our digital legacies. In the case of Mazurenko, everyone I spoke with agreed he would have been delighted by his friends’ experimentation. You may feel less comfortable with the idea of your texts serving as the basis for a bot in the afterlife — particularly if you are unable to review all the texts and social media posts beforehand. We present different aspects of ourselves to different people, and after infusing a bot with all of your digital interactions, your loved ones may see sides of you that you never intended to reveal.

Reading through the Roman bot’s responses, it’s hard not to feel like the texts captured him at a particularly low moment. Ask about Stampsy and it responds: “This is not [the] Stampsy I want it to be. So far it’s just a piece of shit and not the product I want.” Based on his friends’ descriptions of his final years, this strikes me as a candid self-assessment. But I couldn’t help but wish I had been talking to a younger version of the man — the one who friends say dreamed of someday becoming the cultural minister of Belarus, and inaugurating a democratically elected president with what he promised would be the greatest party ever thrown.

Mazurenko contacted me once before he died, in February of last year. He emailed to ask whether I would consider writing about Stampsy, which was then in beta. I liked its design, but passed on writing an article. I wished him well, then promptly forgot about the exchange. After learning of his bot, I resisted using it for several months. I felt guilty about my lone, dismissive interaction with Mazurenko, and was skeptical a bot could reflect his personality. And yet, upon finally chatting with it, I found an undeniable resemblance between the Mazurenko described by his friends and his digital avatar: charming, moody, sarcastic, and obsessed with his work. “How’s it going?” I wrote. “I need to rest,” It responded. “I’m having trouble focusing since I’m depressed.” I asked the bot about Kuyda and it wordlessly sent me a photo of them together on the beach in wetsuits, holding surfboards with their backs to the ocean, two against the world.

An uncomfortable truth suggested by the Roman bot is that many of our flesh-and-blood relationships now exist primarily as exchanges of text, which are becoming increasingly easy to mimic. Kuyda believes there is something — she is not precisely sure what — in this sort of personality-based texting. Recently she has been steering Luka to develop a bot she calls Replika. A hybrid of a diary and a personal assistant, it asks questions about you and eventually learns to mimic your texting style. Kuyda imagines that this could evolve into a digital avatar that performs all sorts of labor on your behalf, from negotiating the cable bill to organizing outings with friends. And like the Roman bot it would survive you, creating a living testament to the person you were.

In the meantime she is no longer interested in bots that handle restaurant recommendations. Working on the Roman bot has made her believe that commercial chatbots must evoke something emotional in the people who use them. If she succeeds in this, it will be one more improbable footnote to Mazurenko’s life.

Kuyda has continued to add material to the Roman bot — mostly photos, which it will now send you upon request — and recently upgraded the underlying neural network from a “selective” model to a “generative” one. The former simply attempted to match Mazurenko’s text messages to appropriate responses; the latter can take snippets of his texts and recombine them to make new sentences that (theoretically) remain in his voice.

Lately she has begun to feel a sense of peace about Mazurenko’s death. In part that’s because she built a place where she can direct her grief. In a conversation we had this fall, she likened it to “just sending a message to heaven. For me it’s more about sending a message in a bottle than getting one in return.”

It has been less than a year since Mazurenko died, and he continues to loom large in the lives of the people who knew him. When they miss him, they send messages to his avatar, and they feel closer to him when they do. “There was a lot I didn’t know about my child,” Roman’s mother told me. “But now that I can read about what he thought about different subjects, I’m getting to know him more. This gives the illusion that he’s here now.”

Her eyes welled with tears, but as our interview ended her voice was strong. “I want to repeat that I’m very grateful that I have this,” she said.

Our conversation reminded me of something Dima Ustinov had said to me this spring, about the way we now transcend our physical forms. “The person is not just a body, a set of arms and legs, and a computer,” he said. “It’s much more than that.” Ustinov compared Mazurenko’s life to a pebble thrown into a stream — the ripples, he said, continue outward in every direction. His friend had simply taken a new form. “We are still in the process of meeting Roman,” Ustinov said. “It’s beautiful.”

http://www.theverge.com/a/luka-artificial-intelligence-memorial-roman-mazurenko-bot

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by Edd Gent

Wiring our brains up to computers could have a host of exciting applications – from controlling robotic prosthetics with our minds to restoring sight by feeding camera feeds directly into the vision center of our brains.

Most brain-computer interface research to date has been conducted using electroencephalography (EEG) where electrodes are placed on the scalp to monitor the brain’s electrical activity. Achieving very high quality signals, however, requires a more invasive approach.

Integrating electronics with living tissue is complicated, though. Probes that are directly inserted into the gray matter have been around for decades, but while they are capable of highly accurate recording, the signals tend to degrade rapidly due to the buildup of scar tissue. Electrocorticography (ECoG), which uses electrodes placed beneath the skull but on top of the gray matter, has emerged as a popular compromise, as it achieves higher-accuracy recordings with a lower risk of scar formation.

But now researchers from the University of Texas have created new probes that are so thin and flexible, they don’t elicit scar tissue buildup. Unlike conventional probes, which are much larger and stiffer, they don’t cause significant damage to the brain tissue when implanted, and they are also able to comply with the natural movements of the brain.

In recent research published in the journal Science Advances, the team demonstrated that the probes were able to reliably record the electrical activity of individual neurons in mice for up to four months. This stability suggests these probes could be used for long-term monitoring of the brain for research or medical diagnostics as well as controlling prostheses, said Chong Xie, an assistant professor in the university’s department of biomedical engineering who led the research.

“Besides neuroprosthetics, they can possibly be used for neuromodulation as well, in which electrodes generate neural stimulation,” he told Singularity Hub in an email. “We are also using them to study the progression of neurovascular and neurodegenerative diseases such as stroke, Parkinson’s and Alzheimer’s.”

The group actually created two probe designs, one 50 microns long and the other 10 microns long. The smaller probe has a cross-section only a fraction of that of a neuron, which the researchers say is the smallest among all reported neural probes to the best of their knowledge.

Because the probes are so flexible, they can’t be pushed into the brain tissue by themselves, and so they needed to be guided in using a stiff rod called a “shuttle device.” Previous designs of these shuttle devices were much larger than the new probes and often led to serious damage to the brain tissue, so the group created a new carbon fiber design just seven microns in diameter.

At present, though, only 25 percent of the recordings can be tracked down to individual neurons – thanks to the fact that neurons each have characteristic waveforms – with the rest too unclear to distinguish from each other.

“The only solution, in my opinion, is to have many electrodes placed in the brain in an array or lattice so that any neuron can be within a reasonable distance from an electrode,” said Chong. “As a result, all enclosed neurons can be recorded and well-sorted.”

This a challenging problem, according to Chong, but one benefit of the new probes is that their small dimensions make it possible to implant probes just tens of microns apart rather than the few hundred micron distances necessary with conventional probes. This opens up the possibility of overlapping detection ranges between probes, though the group can still only consistently implant probes with an accuracy of 50 microns.

Takashi Kozai, an assistant professor in the University of Pittsburgh’s bioengineering department who has worked on ultra-small neural probes, said that further experiments would need to be done to show that the recordings, gleaned from anaesthetized rats, actually contained useful neural code. This could include visually stimulating the animals and trying to record activity in the visual cortex.

He also added that a lot of computational neuroscience relies on knowing the exact spacing between recording sites. The fact that flexible probes are able to migrate due to natural tissue movements could pose challenges.

But he said the study “does show some important advances forward in technology development, and most importantly, proof-of-concept feasibility,” adding that “there is clearly much more work necessary before this technology becomes widely used or practical.”

Chong actually worked on another promising approach to neural recording in his previous role under Charles M. Lieber at Harvard University. Last June, the group demonstrated a mesh of soft, conductive polymer threads studded with electrodes that could be injected into the skulls of mice with a syringe where it would then unfurl to both record and stimulate neurons.

As 95 percent of the mesh is free, space cells are able to arrange themselves around it, and the study reported no signs of an elevated immune response after five weeks. But the implantation required a syringe 100 microns in diameter, which causes considerably more damage than the new ultra-small probes developed in Chong’s lab.

It could be some time before the probes are tested on humans. “The major barrier is that this is still an invasive surgical procedure, including cranial surgery and implantation of devices into brain tissue,” said Chong. But, he said, the group is considering testing the probes on epilepsy patients, as it is common practice to implant electrodes inside the skulls of those who don’t respond to medication to locate the area of their brains responsible for their seizures.

https://singularityhub.com/2017/02/27/this-neural-probe-is-so-thin-the-brain-doesnt-know-its-there/?utm_source=Singularity+Hub+Newsletter&utm_campaign=ba3974d7b9-Hub_Daily_Newsletter&utm_medium=email&utm_term=0_f0cf60cdae-ba3974d7b9-58158129