Tag Archives: sensation

#435806 Boston Dynamics’ Spot Robot Dog ...

Boston Dynamics is announcing this morning that Spot, its versatile quadruped robot, is now for sale. The machine’s animal-like behavior regularly electrifies crowds at tech conferences, and like other Boston Dynamics’ robots, Spot is a YouTube sensation whose videos amass millions of views.

Now anyone interested in buying a Spot—or a pack of them—can go to the company’s website and submit an order form. But don’t pull out your credit card just yet. Spot may cost as much as a luxury car, and it is not really available to consumers. The initial sale, described as an “early adopter program,” is targeting businesses. Boston Dynamics wants to find customers in select industries and help them deploy Spots in real-world scenarios.

“What we’re doing is the productization of Spot,” Boston Dynamics CEO Marc Raibert tells IEEE Spectrum. “It’s really a milestone for us going from robots that work in the lab to these that are hardened for work out in the field.”

Boston Dynamics has always been a secretive company, but last month, in preparation for launching Spot (formerly SpotMini), it allowed our photographers into its headquarters in Waltham, Mass., for a special shoot. In that session, we captured Spot and also Atlas—the company’s highly dynamic humanoid—in action, walking, climbing, and jumping.

You can see Spot’s photo interactives on our Robots Guide. (The Atlas interactives will appear in coming weeks.)

Gif: Bob O’Connor/Robots.ieee.org

And if you’re in the market for a robot dog, here’s everything we know about Boston Dynamics’ plans for Spot.

Who can buy a Spot?
If you’re interested in one, you should go to Boston Dynamics’ website and take a look at the information the company requires from potential buyers. Again, the focus is on businesses. Boston Dynamics says it wants to get Spots out to initial customers that “either have a compelling use case or a development team that we believe can do something really interesting with the robot,” says VP of business development Michael Perry. “Just because of the scarcity of the robots that we have, we’re going to have to be selective about which partners we start working together with.”

What can Spot do?
As you’ve probably seen on the YouTube videos, Spot can walk, trot, avoid obstacles, climb stairs, and much more. The robot’s hardware is almost completely custom, with powerful compute boards for control, and five sensor modules located on every side of Spot’s body, allowing it to survey the space around itself from any direction. The legs are powered by 12 custom motors with a reduction, with a top speed of 1.6 meters per second. The robot can operate for 90 minutes on a charge. In addition to the basic configuration, you can integrate up to 14 kilograms of extra hardware to a payload interface. Among the payload packages Boston Dynamics plans to offer are a 6 degrees-of-freedom arm, a version of which can be seen in some of the YouTube videos, and a ring of cameras called SpotCam that could be used to create Street View–type images inside buildings.

Image: Boston Dynamics

How do you control Spot?
Learning to drive the robot using its gaming-style controller “takes 15 seconds,” says CEO Marc Raibert. He explains that while teleoperating Spot, you may not realize that the robot is doing a lot of the work. “You don’t really see what that is like until you’re operating the joystick and you go over a box and you don’t have to do anything,” he says. “You’re practically just thinking about what you want to do and the robot takes care of everything.” The control methods have evolved significantly since the company’s first quadruped robots, machines like BigDog and LS3. “The control in those days was much more monolithic, and now we have what we call a sequential composition controller,” Raibert says, “which lets the system have control of the dynamics in a much broader variety of situations.” That means that every time one of Spot’s feet touches or doesn’t touch the ground, this different state of the body affects the basic physical behavior of the robot, and the controller adjusts accordingly. “Our controller is designed to understand what that state is and have different controls depending upon the case,” he says.

How much does Spot cost?
Boston Dynamics would not give us specific details about pricing, saying only that potential customers should contact them for a quote and that there is going to be a leasing option. It’s understandable: As with any expensive and complex product, prices can vary on a case by case basis and depend on factors such as configuration, availability, level of support, and so forth. When we pressed the company for at least an approximate base price, Perry answered: “Our general guidance is that the total cost of the early adopter program lease will be less than the price of a car—but how nice a car will depend on the number of Spots leased and how long the customer will be leasing the robot.”

Can Spot do mapping and SLAM out of the box?
The robot’s perception system includes cameras and 3D sensors (there is no lidar), used to avoid obstacles and sense the terrain so it can climb stairs and walk over rubble. It’s also used to create 3D maps. According to Boston Dynamics, the first software release will offer just teleoperation. But a second release, to be available in the next few weeks, will enable more autonomous behaviors. For example, it will be able to do mapping and autonomous navigation—similar to what the company demonstrated in a video last year, showing how you can drive the robot through an environment, create a 3D point cloud of the environment, and then set waypoints within that map for Spot to go out and execute that mission. For customers that have their own autonomy stack and are interested in using those on Spot, Boston Dynamics made it “as plug and play as possible in terms of how third-party software integrates into Spot’s system,” Perry says. This is done mainly via an API.

How does Spot’s API works?
Boston Dynamics built an API so that customers can create application-level products with Spot without having to deal with low-level control processes. “Rather than going and building joint-level kinematic access to the robot,” Perry explains, “we created a high-level API and SDK that allows people who are used to Web app development or development of missions for drones to use that same scope, and they’ll be able to build applications for Spot.”

What applications should we see first?
Boston Dynamics envisions Spot as a platform: a versatile mobile robot that companies can use to build applications based on their needs. What types of applications? The company says the best way to find out is to put Spot in the hands of as many users as possible and let them develop the applications. Some possibilities include performing remote data collection and light manipulation in construction sites; monitoring sensors and infrastructure at oil and gas sites; and carrying out dangerous missions such as bomb disposal and hazmat inspections. There are also other promising areas such as security, package delivery, and even entertainment. “We have some initial guesses about which markets could benefit most from this technology, and we’ve been engaging with customers doing proof-of-concept trials,” Perry says. “But at the end of the day, that value story is really going to be determined by people going out and exploring and pushing the limits of the robot.”

Photo: Bob O'Connor

How many Spots have been produced?
Last June, Boston Dynamics said it was planning to build about a hundred Spots by the end of the year, eventually ramping up production to a thousand units per year by the middle of this year. The company admits that it is not quite there yet. It has built close to a hundred beta units, which it has used to test and refine the final design. This version is now being mass manufactured, but the company is still “in the early tens of robots,” Perry says.

How did Boston Dynamics test Spot?

The company has tested the robots during proof-of-concept trials with customers, and at least one is already using Spot to survey construction sites. The company has also done reliability tests at its facility in Waltham, Mass. “We drive around, not quite day and night, but hundreds of miles a week, so that we can collect reliability data and find bugs,” Raibert says.

What about competitors?
In recent years, there’s been a proliferation of quadruped robots that will compete in the same space as Spot. The most prominent of these is ANYmal, from ANYbotics, a Swiss company that spun out of ETH Zurich. Other quadrupeds include Vision from Ghost Robotics, used by one of the teams in the DARPA Subterranean Challenge; and Laikago and Aliengo from Unitree Robotics, a Chinese startup. Raibert views the competition as a positive thing. “We’re excited to see all these companies out there helping validate the space,” he says. “I think we’re more in competition with finding the right need [that robots can satisfy] than we are with the other people building the robots at this point.”

Why is Boston Dynamics selling Spot now?
Boston Dynamics has long been an R&D-centric firm, with most of its early funding coming from military programs, but it says commercializing robots has always been a goal. Productizing its machines probably accelerated when the company was acquired by Google’s parent company, Alphabet, which had an ambitious (and now apparently very dead) robotics program. The commercial focus likely continued after Alphabet sold Boston Dynamics to SoftBank, whose famed CEO, Masayoshi Son, is known for his love of robots—and profits.

Which should I buy, Spot or Aibo?
Don’t laugh. We’ve gotten emails from individuals interested in purchasing a Spot for personal use after seeing our stories on the robot. Alas, Spot is not a bigger, fancier Aibo pet robot. It’s an expensive, industrial-grade machine that requires development and maintenance. If you’re maybe Jeff Bezos you could probably convince Boston Dynamics to sell you one, but otherwise the company will prioritize businesses.

What’s next for Boston Dynamics?
On the commercial side of things, other than Spot, Boston Dynamics is interested in the logistics space. Earlier this year it announced the acquisition of Kinema Systems, a startup that had developed vision sensors and deep-learning software to enable industrial robot arms to locate and move boxes. There’s also Handle, the mobile robot on whegs (wheels + legs), that can pick up and move packages. Boston Dynamics is hiring both in Waltham, Mass., and Mountain View, Calif., where Kinema was located.

Okay, can I watch a cool video now?
During our visit to Boston Dynamics’ headquarters last month, we saw Atlas and Spot performing some cool new tricks that we unfortunately are not allowed to tell you about. We hope that, although the company is putting a lot of energy and resources into its commercial programs, Boston Dynamics will still find plenty of time to improve its robots, build new ones, and of course, keep making videos. [Update: The company has just released a new Spot video, which we’ve embedded at the top of the post.][Update 2: We should have known. Boston Dynamics sure knows how to create buzz for itself: It has just released a second video, this time of Atlas doing some of those tricks we saw during our visit and couldn’t tell you about. Enjoy!]

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Posted in Human Robots

#435423 Moving Beyond Mind-Controlled Limbs to ...

Brain-machine interface enthusiasts often gush about “closing the loop.” It’s for good reason. On the implant level, it means engineering smarter probes that only activate when they detect faulty electrical signals in brain circuits. Elon Musk’s Neuralink—among other players—are readily pursuing these bi-directional implants that both measure and zap the brain.

But to scientists laboring to restore functionality to paralyzed patients or amputees, “closing the loop” has broader connotations. Building smart mind-controlled robotic limbs isn’t enough; the next frontier is restoring sensation in offline body parts. To truly meld biology with machine, the robotic appendage has to “feel one” with the body.

This month, two studies from Science Robotics describe complementary ways forward. In one, scientists from the University of Utah paired a state-of-the-art robotic arm—the DEKA LUKE—with electrically stimulating remaining nerves above the attachment point. Using artificial zaps to mimic the skin’s natural response patterns to touch, the team dramatically increased the patient’s ability to identify objects. Without much training, he could easily discriminate between the small and large and the soft and hard while blindfolded and wearing headphones.

In another, a team based at the National University of Singapore took inspiration from our largest organ, the skin. Mimicking the neural architecture of biological skin, the engineered “electronic skin” not only senses temperature, pressure, and humidity, but continues to function even when scraped or otherwise damaged. Thanks to artificial nerves that transmit signals far faster than our biological ones, the flexible e-skin shoots electrical data 1,000 times quicker than human nerves.

Together, the studies marry neuroscience and robotics. Representing the latest push towards closing the loop, they show that integrating biological sensibilities with robotic efficiency isn’t impossible (super-human touch, anyone?). But more immediately—and more importantly—they’re beacons of hope for patients who hope to regain their sense of touch.

For one of the participants, a late middle-aged man with speckled white hair who lost his forearm 13 years ago, superpowers, cyborgs, or razzle-dazzle brain implants are the last thing on his mind. After a barrage of emotionally-neutral scientific tests, he grasped his wife’s hand and felt her warmth for the first time in over a decade. His face lit up in a blinding smile.

That’s what scientists are working towards.

Biomimetic Feedback
The human skin is a marvelous thing. Not only does it rapidly detect a multitude of sensations—pressure, temperature, itch, pain, humidity—its wiring “binds” disparate signals together into a sensory fingerprint that helps the brain identify what it’s feeling at any moment. Thanks to over 45 miles of nerves that connect the skin, muscles, and brain, you can pick up a half-full coffee cup, knowing that it’s hot and sloshing, while staring at your computer screen. Unfortunately, this complexity is also why restoring sensation is so hard.

The sensory electrode array implanted in the participant’s arm. Image Credit: George et al., Sci. Robot. 4, eaax2352 (2019)..
However, complex neural patterns can also be a source of inspiration. Previous cyborg arms are often paired with so-called “standard” sensory algorithms to induce a basic sense of touch in the missing limb. Here, electrodes zap residual nerves with intensities proportional to the contact force: the harder the grip, the stronger the electrical feedback. Although seemingly logical, that’s not how our skin works. Every time the skin touches or leaves an object, its nerves shoot strong bursts of activity to the brain; while in full contact, the signal is much lower. The resulting electrical strength curve resembles a “U.”

The LUKE hand. Image Credit: George et al., Sci. Robot. 4, eaax2352 (2019).
The team decided to directly compare standard algorithms with one that better mimics the skin’s natural response. They fitted a volunteer with a robotic LUKE arm and implanted an array of electrodes into his forearm—right above the amputation—to stimulate the remaining nerves. When the team activated different combinations of electrodes, the man reported sensations of vibration, pressure, tapping, or a sort of “tightening” in his missing hand. Some combinations of zaps also made him feel as if he were moving the robotic arm’s joints.

In all, the team was able to carefully map nearly 120 sensations to different locations on the phantom hand, which they then overlapped with contact sensors embedded in the LUKE arm. For example, when the patient touched something with his robotic index finger, the relevant electrodes sent signals that made him feel as if he were brushing something with his own missing index fingertip.

Standard sensory feedback already helped: even with simple electrical stimulation, the man could tell apart size (golf versus lacrosse ball) and texture (foam versus plastic) while blindfolded and wearing noise-canceling headphones. But when the team implemented two types of neuromimetic feedback—electrical zaps that resembled the skin’s natural response—his performance dramatically improved. He was able to identify objects much faster and more accurately under their guidance. Outside the lab, he also found it easier to cook, feed, and dress himself. He could even text on his phone and complete routine chores that were previously too difficult, such as stuffing an insert into a pillowcase, hammering a nail, or eating hard-to-grab foods like eggs and grapes.

The study shows that the brain more readily accepts biologically-inspired electrical patterns, making it a relatively easy—but enormously powerful—upgrade that seamlessly integrates the robotic arms with the host. “The functional and emotional benefits…are likely to be further enhanced with long-term use, and efforts are underway to develop a portable take-home system,” the team said.

E-Skin Revolution: Asynchronous Coded Electronic Skin (ACES)
Flexible electronic skins also aren’t new, but the second team presented an upgrade in both speed and durability while retaining multiplexed sensory capabilities.

Starting from a combination of rubber, plastic, and silicon, the team embedded over 200 sensors onto the e-skin, each capable of discerning contact, pressure, temperature, and humidity. They then looked to the skin’s nervous system for inspiration. Our skin is embedded with a dense array of nerve endings that individually transmit different types of sensations, which are integrated inside hubs called ganglia. Compared to having every single nerve ending directly ping data to the brain, this “gather, process, and transmit” architecture rapidly speeds things up.

The team tapped into this biological architecture. Rather than pairing each sensor with a dedicated receiver, ACES sends all sensory data to a single receiver—an artificial ganglion. This setup lets the e-skin’s wiring work as a whole system, as opposed to individual electrodes. Every sensor transmits its data using a characteristic pulse, which allows it to be uniquely identified by the receiver.

The gains were immediate. First was speed. Normally, sensory data from multiple individual electrodes need to be periodically combined into a map of pressure points. Here, data from thousands of distributed sensors can independently go to a single receiver for further processing, massively increasing efficiency—the new e-skin’s transmission rate is roughly 1,000 times faster than that of human skin.

Second was redundancy. Because data from individual sensors are aggregated, the system still functioned even when any individual receptors are damaged, making it far more resilient than previous attempts. Finally, the setup could easily scale up. Although the team only tested the idea with 240 sensors, theoretically the system should work with up to 10,000.

The team is now exploring ways to combine their invention with other material layers to make it water-resistant and self-repairable. As you might’ve guessed, an immediate application is to give robots something similar to complex touch. A sensory upgrade not only lets robots more easily manipulate tools, doorknobs, and other objects in hectic real-world environments, it could also make it easier for machines to work collaboratively with humans in the future (hey Wall-E, care to pass the salt?).

Dexterous robots aside, the team also envisions engineering better prosthetics. When coated onto cyborg limbs, for example, ACES may give them a better sense of touch that begins to rival the human skin—or perhaps even exceed it.

Regardless, efforts that adapt the functionality of the human nervous system to machines are finally paying off, and more are sure to come. Neuromimetic ideas may very well be the link that finally closes the loop.

Image Credit: Dan Hixson/University of Utah College of Engineering.. Continue reading

Posted in Human Robots

#434792 Extending Human Longevity With ...

Lizards can regrow entire limbs. Flatworms, starfish, and sea cucumbers regrow entire bodies. Sharks constantly replace lost teeth, often growing over 20,000 teeth throughout their lifetimes. How can we translate these near-superpowers to humans?

The answer: through the cutting-edge innovations of regenerative medicine.

While big data and artificial intelligence transform how we practice medicine and invent new treatments, regenerative medicine is about replenishing, replacing, and rejuvenating our physical bodies.

In Part 5 of this blog series on Longevity and Vitality, I detail three of the regenerative technologies working together to fully augment our vital human organs.

Replenish: Stem cells, the regenerative engine of the body
Replace: Organ regeneration and bioprinting
Rejuvenate: Young blood and parabiosis

Let’s dive in.

Replenish: Stem Cells – The Regenerative Engine of the Body
Stem cells are undifferentiated cells that can transform into specialized cells such as heart, neurons, liver, lung, skin and so on, and can also divide to produce more stem cells.

In a child or young adult, these stem cells are in large supply, acting as a built-in repair system. They are often summoned to the site of damage or inflammation to repair and restore normal function.

But as we age, our supply of stem cells begins to diminish as much as 100- to 10,000-fold in different tissues and organs. In addition, stem cells undergo genetic mutations, which reduce their quality and effectiveness at renovating and repairing your body.

Imagine your stem cells as a team of repairmen in your newly constructed mansion. When the mansion is new and the repairmen are young, they can fix everything perfectly. But as the repairmen age and reduce in number, your mansion eventually goes into disrepair and finally crumbles.

What if you could restore and rejuvenate your stem cell population?

One option to accomplish this restoration and rejuvenation is to extract and concentrate your own autologous adult stem cells from places like your adipose (or fat) tissue or bone marrow.

These stem cells, however, are fewer in number and have undergone mutations (depending on your age) from their original ‘software code.’ Many scientists and physicians now prefer an alternative source, obtaining stem cells from the placenta or umbilical cord, the leftovers of birth.

These stem cells, available in large supply and expressing the undamaged software of a newborn, can be injected into joints or administered intravenously to rejuvenate and revitalize.

Think of these stem cells as chemical factories generating vital growth factors that can help to reduce inflammation, fight autoimmune disease, increase muscle mass, repair joints, and even revitalize skin and grow hair.

Over the last decade, the number of publications per year on stem cell-related research has increased 40x, and the stem cell market is expected to increase to $297 billion by 2022.

Rising research and development initiatives to develop therapeutic options for chronic diseases and growing demand for regenerative treatment options are the most significant drivers of this budding industry.

Biologists led by Kohji Nishida at Osaka University in Japan have discovered a new way to nurture and grow the tissues that make up the human eyeball. The scientists are able to grow retinas, corneas, the eye’s lens, and more, using only a small sample of adult skin.

In a Stanford study, seven of 18 stroke victims who agreed to stem cell treatments showed remarkable motor function improvements. This treatment could work for other neurodegenerative conditions such as Alzheimer’s, Parkinson’s, and ALS.

Doctors from the USC Neurorestoration Center and Keck Medicine of USC injected stem cells into the damaged cervical spine of a recently paralyzed 21-year-old man. Three months later, he showed dramatic improvement in sensation and movement of both arms.

In 2019, doctors in the U.K. cured a patient with HIV for the second time ever thanks to the efficacy of stem cells. After giving the cancer patient (who also had HIV) an allogeneic haematopoietic (e.g. blood) stem cell treatment for his Hodgkin’s lymphoma, the patient went into long-term HIV remission—18 months and counting at the time of the study’s publication.

Replace: Organ Regeneration and 3D Printing
Every 10 minutes, someone is added to the US organ transplant waiting list, totaling over 113,000 people waiting for replacement organs as of January 2019.

Countless more people in need of ‘spare parts’ never make it onto the waiting list. And on average, 20 people die each day while waiting for a transplant.

As a result, 35 percent of all US deaths (~900,000 people) could be prevented or delayed with access to organ replacements.

The excessive demand for donated organs will only intensify as technologies like self-driving cars make the world safer, given that many organ donors result from auto and motorcycle accidents. Safer vehicles mean less accidents and donations.

Clearly, replacement and regenerative medicine represent a massive opportunity.

Organ Entrepreneurs
Enter United Therapeutics CEO, Dr. Martine Rothblatt. A one-time aerospace entrepreneur (she was the founder of Sirius Satellite Radio), Rothblatt changed careers in the 1990s after her daughter developed a rare lung disease.

Her moonshot today is to create an industry of replacement organs. With an initial focus on diseases of the lung, Rothblatt set out to create replacement lungs. To accomplish this goal, her company United Therapeutics has pursued a number of technologies in parallel.

3D Printing Lungs
In 2017, United teamed up with one of the world’s largest 3D printing companies, 3D Systems, to build a collagen bioprinter and is paying another company, 3Scan, to slice up lungs and create detailed maps of their interior.

This 3D Systems bioprinter now operates according to a method called stereolithography. A UV laser flickers through a shallow pool of collagen doped with photosensitive molecules. Wherever the laser lingers, the collagen cures and becomes solid.

Gradually, the object being printed is lowered and new layers are added. The printer can currently lay down collagen at a resolution of around 20 micrometers, but will need to achieve resolution of a micrometer in size to make the lung functional.

Once a collagen lung scaffold has been printed, the next step is to infuse it with human cells, a process called recellularization.

The goal here is to use stem cells that grow on scaffolding and differentiate, ultimately providing the proper functionality. Early evidence indicates this approach can work.

In 2018, Harvard University experimental surgeon Harald Ott reported that he pumped billions of human cells (from umbilical cords and diced lungs) into a pig lung stripped of its own cells. When Ott’s team reconnected it to a pig’s circulation, the resulting organ showed rudimentary function.

Humanizing Pig Lungs
Another of Rothblatt’s organ manufacturing strategies is called xenotransplantation, the idea of transplanting an animal’s organs into humans who need a replacement.

Given the fact that adult pig organs are similar in size and shape to those of humans, United Therapeutics has focused on genetically engineering pigs to allow humans to use their organs. “It’s actually not rocket science,” said Rothblatt in her 2015 TED talk. “It’s editing one gene after another.”

To accomplish this goal, United Therapeutics made a series of investments in companies such as Revivicor Inc. and Synthetic Genomics Inc., and signed large funding agreements with the University of Maryland, University of Alabama, and New York Presbyterian/Columbia University Medical Center to create xenotransplantation programs for new hearts, kidneys, and lungs, respectively. Rothblatt hopes to see human translation in three to four years.

In preparation for that day, United Therapeutics owns a 132-acre property in Research Triangle Park and built a 275,000-square-foot medical laboratory that will ultimately have the capability to annually produce up to 1,000 sets of healthy pig lungs—known as xenolungs—from genetically engineered pigs.

Lung Ex Vivo Perfusion Systems
Beyond 3D printing and genetically engineering pig lungs, Rothblatt has already begun implementing a third near-term approach to improve the supply of lungs across the US.

Only about 30 percent of potential donor lungs meet transplant criteria in the first place; of those, only about 85 percent of those are usable once they arrive at the surgery center. As a result, nearly 75 percent of possible lungs never make it to the recipient in need.

What if these lungs could be rejuvenated? This concept informs Dr. Rothblatt’s next approach.

In 2016, United Therapeutics invested $41.8 million in TransMedics Inc., an Andover, Massachusetts company that develops ex vivo perfusion systems for donor lungs, hearts, and kidneys.

The XVIVO Perfusion System takes marginal-quality lungs that initially failed to meet transplantation standard-of-care criteria and perfuses and ventilates them at normothermic conditions, providing an opportunity for surgeons to reassess transplant suitability.

Rejuvenate Young Blood and Parabiosis
In HBO’s parody of the Bay Area tech community, Silicon Valley, one of the episodes (Season 4, Episode 5) is named “The Blood Boy.”

In this installment, tech billionaire Gavin Belson (Matt Ross) is meeting with Richard Hendricks (Thomas Middleditch) and his team, speaking about the future of the decentralized internet. A young, muscled twenty-something disrupts the meeting when he rolls in a transfusion stand and silently hooks an intravenous connection between himself and Belson.

Belson then introduces the newcomer as his “transfusion associate” and begins to explain the science of parabiosis: “Regular transfusions of the blood of a younger physically fit donor can significantly retard the aging process.”

While the sitcom is fiction, that science has merit, and the scenario portrayed in the episode is already happening today.

On the first point, research at Stanford and Harvard has demonstrated that older animals, when transfused with the blood of young animals, experience regeneration across many tissues and organs.

The opposite is also true: young animals, when transfused with the blood of older animals, experience accelerated aging. But capitalizing on this virtual fountain of youth has been tricky.

Ambrosia
One company, a San Francisco-based startup called Ambrosia, recently commenced one of the trials on parabiosis. Their protocol is simple: Healthy participants aged 35 and older get a transfusion of blood plasma from donors under 25, and researchers monitor their blood over the next two years for molecular indicators of health and aging.

Ambrosia’s founder Jesse Karmazin became interested in launching a company around parabiosis after seeing impressive data from animals and studies conducted abroad in humans: In one trial after another, subjects experience a reversal of aging symptoms across every major organ system. “The effects seem to be almost permanent,” he said. “It’s almost like there’s a resetting of gene expression.”

Infusing your own cord blood stem cells as you age may have tremendous longevity benefits. Following an FDA press release in February 2019, Ambrosia halted its consumer-facing treatment after several months of operation.

Understandably, the FDA raised concerns about the practice of parabiosis because to date, there is a marked lack of clinical data to support the treatment’s effectiveness.

Elevian
On the other end of the reputability spectrum is a startup called Elevian, spun out of Harvard University. Elevian is approaching longevity with a careful, scientifically validated strategy. (Full Disclosure: I am both an advisor to and investor in Elevian.)

CEO Mark Allen, MD, is joined by a dozen MDs and Ph.Ds out of Harvard. Elevian’s scientific founders started the company after identifying specific circulating factors that may be responsible for the “young blood” effect.

One example: A naturally occurring molecule known as “growth differentiation factor 11,” or GDF11, when injected into aged mice, reproduces many of the regenerative effects of young blood, regenerating heart, brain, muscles, lungs, and kidneys.

More specifically, GDF11 supplementation reduces age-related cardiac hypertrophy, accelerates skeletal muscle repair, improves exercise capacity, improves brain function and cerebral blood flow, and improves metabolism.

Elevian is developing a number of therapeutics that regulate GDF11 and other circulating factors. The goal is to restore our body’s natural regenerative capacity, which Elevian believes can address some of the root causes of age-associated disease with the promise of reversing or preventing many aging-related diseases and extending the healthy lifespan.

Conclusion
In 1992, futurist Leland Kaiser coined the term “regenerative medicine”:

“A new branch of medicine will develop that attempts to change the course of chronic disease and in many instances will regenerate tired and failing organ systems.”

Since then, the powerful regenerative medicine industry has grown exponentially, and this rapid growth is anticipated to continue.

A dramatic extension of the human healthspan is just over the horizon. Soon, we’ll all have the regenerative superpowers previously relegated to a handful of animals and comic books.

What new opportunities open up when anybody, anywhere, and at anytime can regenerate, replenish, and replace entire organs and metabolic systems on command?

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Posted in Human Robots

#434781 What Would It Mean for AI to Become ...

As artificial intelligence systems take on more tasks and solve more problems, it’s hard to say which is rising faster: our interest in them or our fear of them. Futurist Ray Kurzweil famously predicted that “By 2029, computers will have emotional intelligence and be convincing as people.”

We don’t know how accurate this prediction will turn out to be. Even if it takes more than 10 years, though, is it really possible for machines to become conscious? If the machines Kurzweil describes say they’re conscious, does that mean they actually are?

Perhaps a more relevant question at this juncture is: what is consciousness, and how do we replicate it if we don’t understand it?

In a panel discussion at South By Southwest titled “How AI Will Design the Human Future,” experts from academia and industry discussed these questions and more.

Wait, What Is AI?
Most of AI’s recent feats—diagnosing illnesses, participating in debate, writing realistic text—involve machine learning, which uses statistics to find patterns in large datasets then uses those patterns to make predictions. However, “AI” has been used to refer to everything from basic software automation and algorithms to advanced machine learning and deep learning.

“The term ‘artificial intelligence’ is thrown around constantly and often incorrectly,” said Jennifer Strong, a reporter at the Wall Street Journal and host of the podcast “The Future of Everything.” Indeed, one study found that 40 percent of European companies that claim to be working on or using AI don’t actually use it at all.

Dr. Peter Stone, associate chair of computer science at UT Austin, was the study panel chair on the 2016 One Hundred Year Study on Artificial Intelligence (or AI100) report. Based out of Stanford University, AI100 is studying and anticipating how AI will impact our work, our cities, and our lives.

“One of the first things we had to do was define AI,” Stone said. They defined it as a collection of different technologies inspired by the human brain to be able to perceive their surrounding environment and figure out what actions to take given these inputs.

Modeling on the Unknown
Here’s the crazy thing about that definition (and about AI itself): we’re essentially trying to re-create the abilities of the human brain without having anything close to a thorough understanding of how the human brain works.

“We’re starting to pair our brains with computers, but brains don’t understand computers and computers don’t understand brains,” Stone said. Dr. Heather Berlin, cognitive neuroscientist and professor of psychiatry at the Icahn School of Medicine at Mount Sinai, agreed. “It’s still one of the greatest mysteries how this three-pound piece of matter can give us all our subjective experiences, thoughts, and emotions,” she said.

This isn’t to say we’re not making progress; there have been significant neuroscience breakthroughs in recent years. “This has been the stuff of science fiction for a long time, but now there’s active work being done in this area,” said Amir Husain, CEO and founder of Austin-based AI company Spark Cognition.

Advances in brain-machine interfaces show just how much more we understand the brain now than we did even a few years ago. Neural implants are being used to restore communication or movement capabilities in people who’ve been impaired by injury or illness. Scientists have been able to transfer signals from the brain to prosthetic limbs and stimulate specific circuits in the brain to treat conditions like Parkinson’s, PTSD, and depression.

But much of the brain’s inner workings remain a deep, dark mystery—one that will have to be further solved if we’re ever to get from narrow AI, which refers to systems that can perform specific tasks and is where the technology stands today, to artificial general intelligence, or systems that possess the same intelligence level and learning capabilities as humans.

The biggest question that arises here, and one that’s become a popular theme across stories and films, is if machines achieve human-level general intelligence, does that also mean they’d be conscious?

Wait, What Is Consciousness?
As valuable as the knowledge we’ve accumulated about the brain is, it seems like nothing more than a collection of disparate facts when we try to put it all together to understand consciousness.

“If you can replace one neuron with a silicon chip that can do the same function, then replace another neuron, and another—at what point are you still you?” Berlin asked. “These systems will be able to pass the Turing test, so we’re going to need another concept of how to measure consciousness.”

Is consciousness a measurable phenomenon, though? Rather than progressing by degrees or moving through some gray area, isn’t it pretty black and white—a being is either conscious or it isn’t?

This may be an outmoded way of thinking, according to Berlin. “It used to be that only philosophers could study consciousness, but now we can study it from a scientific perspective,” she said. “We can measure changes in neural pathways. It’s subjective, but depends on reportability.”

She described three levels of consciousness: pure subjective experience (“Look, the sky is blue”), awareness of one’s own subjective experience (“Oh, it’s me that’s seeing the blue sky”), and relating one subjective experience to another (“The blue sky reminds me of a blue ocean”).

“These subjective states exist all the way down the animal kingdom. As humans we have a sense of self that gives us another depth to that experience, but it’s not necessary for pure sensation,” Berlin said.

Husain took this definition a few steps farther. “It’s this self-awareness, this idea that I exist separate from everything else and that I can model myself,” he said. “Human brains have a wonderful simulator. They can propose a course of action virtually, in their minds, and see how things play out. The ability to include yourself as an actor means you’re running a computation on the idea of yourself.”

Most of the decisions we make involve envisioning different outcomes, thinking about how each outcome would affect us, and choosing which outcome we’d most prefer.

“Complex tasks you want to achieve in the world are tied to your ability to foresee the future, at least based on some mental model,” Husain said. “With that view, I as an AI practitioner don’t see a problem implementing that type of consciousness.”

Moving Forward Cautiously (But Not too Cautiously)
To be clear, we’re nowhere near machines achieving artificial general intelligence or consciousness, and whether a “conscious machine” is possible—not to mention necessary or desirable—is still very much up for debate.

As machine intelligence continues to advance, though, we’ll need to walk the line between progress and risk management carefully.

Improving the transparency and explainability of AI systems is one crucial goal AI developers and researchers are zeroing in on. Especially in applications that could mean the difference between life and death, AI shouldn’t advance without people being able to trace how it’s making decisions and reaching conclusions.

Medicine is a prime example. “There are already advances that could save lives, but they’re not being used because they’re not trusted by doctors and nurses,” said Stone. “We need to make sure there’s transparency.” Demanding too much transparency would also be a mistake, though, because it will hinder the development of systems that could at best save lives and at worst improve efficiency and free up doctors to have more face time with patients.

Similarly, self-driving cars have great potential to reduce deaths from traffic fatalities. But even though humans cause thousands of deadly crashes every day, we’re terrified by the idea of self-driving cars that are anything less than perfect. “If we only accept autonomous cars when there’s zero probability of an accident, then we will never accept them,” Stone said. “Yet we give 16-year-olds the chance to take a road test with no idea what’s going on in their brains.”

This brings us back to the fact that, in building tech modeled after the human brain—which has evolved over millions of years—we’re working towards an end whose means we don’t fully comprehend, be it something as basic as choosing when to brake or accelerate or something as complex as measuring consciousness.

“We shouldn’t charge ahead and do things just because we can,” Stone said. “The technology can be very powerful, which is exciting, but we have to consider its implications.”

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Posted in Human Robots

#434685 How Tech Will Let You Learn Anything, ...

Today, over 77 percent of Americans own a smartphone with access to the world’s information and near-limitless learning resources.

Yet nearly 36 million adults in the US are constrained by low literacy skills, excluding them from professional opportunities, prospects of upward mobility, and full engagement with their children’s education.

And beyond its direct impact, low literacy rates affect us all. Improving literacy among adults is predicted to save $230 billion in national healthcare costs and could result in US labor productivity increases of up to 2.5 percent.

Across the board, exponential technologies are making demonetized learning tools, digital training platforms, and literacy solutions more accessible than ever before.

With rising automation and major paradigm shifts underway in the job market, these tools not only promise to make today’s workforce more versatile, but could play an invaluable role in breaking the poverty cycles often associated with low literacy.

Just three years ago, the Barbara Bush Foundation for Family Literacy and the Dollar General Literacy Foundation joined forces to tackle this intractable problem, launching a $7 million Adult Literacy XPRIZE.

Challenging teams to develop smartphone apps that significantly increase literacy skills among adult learners in just 12 months, the competition brought five prize teams to the fore, each targeting multiple demographics across the nation.

Now, after four years of research, prototyping, testing, and evaluation, XPRIZE has just this week announced two grand prize winners: Learning Upgrade and People ForWords.

In this blog, I’ll be exploring the nuts and bolts of our two winning teams and how exponential technologies are beginning to address rapidly shifting workforce demands.

We’ll discuss:

Meeting 100 percent adult literacy rates
Retooling today’s workforce for tomorrow’s job market
Granting the gift of lifelong learning

Let’s dive in.

Adult Literacy XPRIZE
Emphasizing the importance of accessible mediums and scalability, the Adult Literacy XPRIZE called for teams to create mobile solutions that lower the barrier to entry, encourage persistence, develop relevant learning content, and can scale nationally.

Outperforming the competition in two key demographic groups in aggregate—native English speakers and English language learners—teams Learning Upgrade and People ForWords together claimed the prize.

To win, both organizations successfully generated the greatest gains between a pre- and post-test, administered one year apart to learners in a 12-month field test across Los Angeles, Dallas, and Philadelphia.

Prize money in hand, Learning Upgrade and People ForWords are now scaling up their solutions, each targeting a key demographic in America’s pursuit of adult literacy.

Based in San Diego, Learning Upgrade has developed an Android and iOS app that helps students learn English and math through video, songs, and gamification. Offering a total of 21 courses from kindergarten through adult education, Learning Upgrade touts a growing platform of over 900 lessons spanning English, reading, math, and even GED prep.

To further personalize each student’s learning, Learning Upgrade measures time-on-task and builds out formative performance assessments, granting teachers a quantified, real-time view of each student’s progress across both lessons and criteria.

Specialized in English reading skills, Dallas-based People ForWords offers a similarly delocalized model with its mobile game “Codex: Lost Words of Atlantis.” Based on an archaeological adventure storyline, the app features an immersive virtual environment.

Set in the Atlantis Library (now with a 3D rendering underway), Codex takes its students through narrative-peppered lessons covering everything from letter-sound practice to vocabulary reinforcement in a hidden object game.

But while both mobile apps have recruited initial piloting populations, the key to success is scale.

Using a similar incentive prize competition structure to drive recruitment, the second phase of the XPRIZE is a $1 million Barbara Bush Foundation Adult Literacy XPRIZE Communities Competition. For 15 months, the competition will challenge organizations, communities, and individuals alike to onboard adult learners onto both prize-winning platforms and fellow finalist team apps, AmritaCREATE and Cell-Ed.

Each awarded $125,000 for participation in the Communities Competition, AmritaCREATE and Cell-Ed bring yet other nuanced advantages to the table.

While AmritaCREATE curates culturally appropriate e-content relevant to given life skills, Cell-Ed takes a learn-on-the-go approach, offering micro-lessons, on-demand essential skills training, and individualized coaching on any mobile device, no internet required.

Although all these cases target slightly different demographics and problem niches, they converge upon common phenomena: mobility, efficiency, life skill relevance, personalized learning, and practicability.

And what better to scale these benefits than AI and immersive virtual environments?

In the case of education’s growing mobility, 5G and the explosion of connectivity speeds will continue to drive a learn-anytime-anywhere education model, whereby adult users learn on the fly, untethered to web access or rigid time strictures.

As I’ve explored in a previous blog on AI-crowd collaboration, we might also see the rise of AI learning consultants responsible for processing data on how you learn.

Quantifying and analyzing your interaction with course modules, where you get stuck, where you thrive, and what tools cause you ease or frustration, each user’s AI trainer might then issue personalized recommendations based on crowd feedback.

Adding a human touch, each app’s hired teaching consultants would thereby be freed to track many more students’ progress at once, vetting AI-generated tips and adjustments, and offering life coaching along the way.

Lastly, virtual learning environments—and, one day, immersive VR—will facilitate both speed and retention, two of the most critical constraints as learners age.

As I often reference, people generally remember only 10 percent of what we see, 20 percent of what we hear, and 30 percent of what we read…. But over a staggering 90 percent of what we do or experience.

By introducing gamification, immersive testing activities, and visually rich sensory environments, adult literacy platforms have a winning chance at scalability, retention, and user persistence.

Exponential Tools: Training and Retooling a Dynamic Workforce
Beyond literacy, however, virtual and augmented reality have already begun disrupting the professional training market.

As projected by ABI Research, the enterprise VR training market is on track to exceed $6.3 billion in value by 2022.

Leading the charge, Walmart has already implemented VR across 200 Academy training centers, running over 45 modules and simulating everything from unusual customer requests to a Black Friday shopping rush.

Then in September of last year, Walmart committed to a 17,000-headset order of the Oculus Go to equip every US Supercenter, neighborhood market, and discount store with VR-based employee training.

In the engineering world, Bell Helicopter is using VR to massively expedite development and testing of its latest aircraft, FCX-001. Partnering with Sector 5 Digital and HTC VIVE, Bell found it could concentrate a typical six-year aircraft design process into the course of six months, turning physical mockups into CAD-designed virtual replicas.

But beyond the design process itself, Bell is now one of a slew of companies pioneering VR pilot tests and simulations with real-world accuracy. Seated in a true-to-life virtual cockpit, pilots have now tested countless iterations of the FCX-001 in virtual flight, drawing directly onto the 3D model and enacting aircraft modifications in real time.

And in an expansion of our virtual senses, several key players are already working on haptic feedback. In the case of VR flight, French company Go Touch VR is now partnering with software developer FlyInside on fingertip-mounted haptic tech for aviation.

Dramatically reducing time and trouble required for VR-testing pilots, they aim to give touch-based confirmation of every switch and dial activated on virtual flights, just as one would experience in a full-sized cockpit mockup. Replicating texture, stiffness, and even the sensation of holding an object, these piloted devices contain a suite of actuators to simulate everything from a light touch to higher-pressured contact, all controlled by gaze and finger movements.

When it comes to other high-risk simulations, virtual and augmented reality have barely scratched the surface.
Firefighters can now combat virtual wildfires with new platforms like FLAIM Trainer or TargetSolutions. And thanks to the expansion of medical AR/VR services like 3D4Medical or Echopixel, surgeons might soon perform operations on annotated organs and magnified incision sites, speeding up reaction times and vastly improving precision.

But perhaps most urgently, virtual reality will offer an immediate solution to today’s constant industry turnover and large-scale re-education demands.

VR educational facilities with exact replicas of anything from large industrial equipment to minute circuitry will soon give anyone a second chance at the 21st-century job market.

Want to become an electric, autonomous vehicle mechanic at age 44? Throw on a demonetized VR module and learn by doing, testing your prototype iterations at almost zero cost and with no risk of harming others.

Want to be a plasma physicist and play around with a virtual nuclear fusion reactor? Now you’ll be able to simulate results and test out different tweaks, logging Smart Educational Record credits in the process.

As tomorrow’s career model shifts from a “one-and-done graduate degree” to continuous lifelong education, professional VR-based re-education will allow for a continuous education loop, reducing the barrier to entry for anyone wanting to try their hand at a new industry.

Learn Anything, Anytime, at Any Age
As VR and artificial intelligence converge with demonetized mobile connectivity, we are finally witnessing an era in which no one will be left behind.

Whether in pursuit of fundamental life skills, professional training, linguistic competence, or specialized retooling, users of all ages, career paths, income brackets, and goals are now encouraged to be students, no longer condemned to stagnancy.

Traditional constraints need no longer prevent non-native speakers from gaining an equal foothold, or specialists from pivoting into new professions, or low-income parents from staking new career paths.

As exponential technologies drive democratized access, bolstering initiatives such as the Barbara Bush Foundation Adult Literacy XPRIZE are blazing the trail to make education a scalable priority for all.

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Posted in Human Robots