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Superhuman innovators: How experimentation and struggle fuel new ideas
Why Django Reinhardt might just be the greatest musical innovator you've never heard of.
David Epstein is the author of the New York Times bestsellers Range: Why Generalist Triumph in a Specialized World and The Sports Gene. He has master's degrees in environmental science and journalism and has worked as an investigative reporter for ProPublica and a senior writer for Sports Illustrated. He lives in Washington, DC.
DAVID EPSTEIN: One of the most important and influential modern musicians still shows up in the backgrounds of Hollywood blockbusters like The Matrix and hit video games like Bioshock, and yet his name isn't as well known as it probably should be.
Django Reinhardt was a Roma musician, born in Belgium in 1910. He lived, then, in an area of France called La Zone, which actually was where cesspools were emptied from the city. But he grew up surrounded by music. So Roma caravans, there was music everywhere, usually violin because it was so portable. And they would teach in a call and response mode, where adults would play and kids might try to play back to them. And Django did that, but he didn't really like violin, but when he was a boy, someone gave him this kind of hybrid banjo guitar. And then he had found his thing. He got obsessed with it. He would play, he would improvise instruments, use a piece of whale bone to try to play and make different sounds and he went around Paris busking with a hunchback named Lagardére, and improvising on the streets. And he started to get quite good, and eventually got a real guitar.
But when he was a teenager he had an unfortunate accident. His wife was making cellophane flowers, basically, in their wagon and one of them caught fire. And Django was burned over half of his body. For the rest of his life, the pinky and ring finger on Django's left hand, his guitar fretting hand, were useless pieces of dangling flesh. And you would think that his budding guitar career was probably over. But instead, Django taught himself a new way to play the guitar with the still-working fingers of that left hand sprinting up and down the frets and improvising and playing with new fingerings that other people hadn't because he had to invent something different. Django emerged after that accident with a completely new style of music that fused dancehall music from France with styles from jazz in the United States. And it was so indescribable compared to anything else that existed that it was only called, at the time, "Gypsy Jazz". And Django's improvisations, and his virtuosity on the guitar, were really in some ways the start of the modern guitar solo and influenced performers like Jimi Hendrix who had Django's music in his personal collection, and in fact named one of his groups Band of Gypsies.
And Django's story in some ways bears a resemblance to a lot of great musicians in jazz and in other creative forms of music. There's an old joke among jazz musicians that goes like this. One of the musicians asks the other if he can read music. And the musician responds, not enough to hurt my playing. Django couldn't read music. Django couldn't read at all, actually. One of his friends had to teach him how to sign his own name for fans. He was once in a taxi with Les Paul, the inventor of the solid body electric guitar, and Les Paul was a self-taught musician. And Django asked him if he could read music and Les Paul said that he couldn't. And Django laughed hilariously and said that he couldn't either; he didn't even know what a C was, he just played it. And the lesson that really comes from this, though, is something different. If we want people to be able to improvise and be flexible with their skills, they should actually learn things kind of like a baby. When babies learn to talk they get thrown in, they get immersed, they try and fail, and only later you teach the grammar. And that seems to be similar for improvisational forms of music where you kind of want somebody in and struggling and trying and listening before you teach them the more formal grammar. And that seems to lead to better creative outcomes.
- David Epstein recounts the incredible life of 20th-century Roma guitarist Django Reinhardt, who couldn't read or write and who suffered a horrific accident that made two of his fret fingers useless.
- Reinhardt didn't stop playing, instead he invented a new style that revolutionized the music scene and gave birth to the modern guitar solo, inspiring artists like Jimi Hendrix.
- Anyone can innovate, says Epstein, it is in no way dependent on a formal education. In fact, our creative work may fare better if we learn like babies do: through trial, error, and struggle.
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If machines develop consciousness, or if we manage to give it to them, the human-robot dynamic will forever be different.
- Does AI—and, more specifically, conscious AI—deserve moral rights? In this thought exploration, evolutionary biologist Richard Dawkins, ethics and tech professor Joanna Bryson, philosopher and cognitive scientist Susan Schneider, physicist Max Tegmark, philosopher Peter Singer, and bioethicist Glenn Cohen all weigh in on the question of AI rights.
- Given the grave tragedy of slavery throughout human history, philosophers and technologists must answer this question ahead of technological development to avoid humanity creating a slave class of conscious beings.
- One potential safeguard against that? Regulation. Once we define the context in which AI requires rights, the simplest solution may be to not build that thing.
Duke University researchers might have solved a half-century old problem.
- Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
- The blend of three polymers provides enough flexibility and durability to mimic the knee.
- The next step is to test this hydrogel in sheep; human use can take at least three years.
Duke researchers have developed the first gel-based synthetic cartilage with the strength of the real thing. A quarter-sized disc of the material can withstand the weight of a 100-pound kettlebell without tearing or losing its shape.
Photo: Feichen Yang.<p>That's the word from a team in the Department of Chemistry and Department of Mechanical Engineering and Materials Science at Duke University. Their <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/adfm.202003451" target="_blank">new paper</a>, published in the journal,<em> Advanced Functional Materials</em>, details this exciting evolution of this frustrating joint.<br></p><p>Researchers have sought materials strong and versatile enough to repair a knee since at least the seventies. This new hydrogel, comprised of three polymers, might be it. When two of the polymers are stretched, a third keeps the entire structure intact. When pulled 100,000 times, the cartilage held up as well as materials used in bone implants. The team also rubbed the hydrogel against natural cartilage a million times and found it to be as wear-resistant as the real thing. </p><p>The hydrogel has the appearance of Jell-O and is comprised of 60 percent water. Co-author, Feichen Yang, <a href="https://today.duke.edu/2020/06/lab-first-cartilage-mimicking-gel-strong-enough-knees" target="_blank">says</a> this network of polymers is particularly durable: "Only this combination of all three components is both flexible and stiff and therefore strong." </p><p> As with any new material, a lot of testing must be conducted. They don't foresee this hydrogel being implanted into human bodies for at least three years. The next step is to test it out in sheep. </p><p>Still, this is an exciting step forward in the rehabilitation of one of our trickiest joints. Given the potential reward, the wait is worth it. </p><p><span></span>--</p><p><em>Stay in touch with Derek on <a href="http://www.twitter.com/derekberes" target="_blank">Twitter</a>, <a href="https://www.facebook.com/DerekBeresdotcom" target="_blank">Facebook</a> and <a href="https://derekberes.substack.com/" target="_blank">Substack</a>. His next book is</em> "<em>Hero's Dose: The Case For Psychedelics in Ritual and Therapy."</em></p>
What would it be like to experience the 4th dimension?
Physicists have understood at least theoretically, that there may be higher dimensions, besides our normal three. The first clue came in 1905 when Einstein developed his theory of special relativity. Of course, by dimensions we’re talking about length, width, and height. Generally speaking, when we talk about a fourth dimension, it’s considered space-time. But here, physicists mean a spatial dimension beyond the normal three, not a parallel universe, as such dimensions are mistaken for in popular sci-fi shows.
An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.
- 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
- Early treatment is available but there's been no way to tell who needs it.
- Using clinical data already being collected, machine learning can identify who's at risk.
The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.
In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.
That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.
70 data points and machine learning
Image source: Creators Collective/Unsplash
Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:
"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."
The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.
Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."
Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.
Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.
On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.
Image source: Külli Kittus/Unsplash
Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."
"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.
The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.