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How Not to Close a Restaurant in New York City
In 1985, at age 27, Danny launched Union Square Cafe in New York City. Danny Meyer is the CEO of Union Square Hospitality Group, and his restaurants and their chefs have earned an unprecedented seventeen James Beard Awards. He is the coauthor of The Union Square Cafe Cookbook, Second Helpings from Union Square Cafe, and Setting the Table, and he lives in New York City.
Question: What’s the secret to building and maintaining a brand, especially in New York City?
Danny Meyer: I think the key has been to start every restaurant with a sharp point of view. So we go into each restaurant knowing what it is we’re trying to do. It’s like writing a story but then here’s where it’s different from a story, it’s a highly interactive experience. So the people who come to the restaurant may like part of your original point of view but they may want you to do things a little bit differently and so then it really becomes an ongoing dialog where you’re listening to how the people who like your restaurant would like it even more if only you shifted a little bit.
So you’re having a dialog with your guests, you’re having a dialog with your staff. I think it’s really important to keep the staff as engaged as possible because at the end of the day the restaurant itself is inanimate object and it’s the human beings who work there that are the reason that people like you either want to come back or not. There is a fine line. I’m knocking on wood right now but in 24 years I’ve never had the experience of closing a restaurant. The real fine line is that you’ve got to give people enough of the things they returned for but you’ve got to give people enough new things so they’ll come back as well. If you take away all the reasons that they came back, they may not want to return, but if you don’t change things, they may not want to return. So there’s the art.
Question: Does social media strengthen or weaken a brand?
Danny Meyer: I think what any of the new media is, is actually very old, which is that it’s human nature to want to recommend things to people you like and to want to denigrate things to people you like that you didn’t like. I think that’s always been human nature; we used to call it word of mouth. Now it’s word of Yelp or word of Twitter, or whatever. So it’s really not a new thing, but I think that anyone who has any kind of a business who’s not paying attention to what the world or what their customers are saying, is making a mistake.
Now, it’s equally important that if you’re a radio you want to have antenna that are sharp enough to pick up the stuff that’s out there. But if you’re antenna are so sensitive that they pick up everything, you’re going to pick up static as well that may not be particularly useful. So it’s such a critical thing to learn to tune in the constructive stuff and tune out the stuff that’s just hurtful.
Question: Eleven Madison Park is 11 years old and recently got raised to four stars by the New York Times. Why?
Danny Meyer: The restaurant will be 11 years old this year and I think the secret of any restaurant is you’ve just got to stick at it. You’ve got to stick to the things that you believe in and you’ve got to listen really carefully. In the case of Eleven Madison Park, we listened very, very carefully and we realized that our early point of view wasn’t necessarily on the money. Rather than people using it when we first opened it as a brasserie, which is pretty much what I had envisioned it as, they said instead of saying this is the best brasserie food I’ve ever had in my life, which it would have been if they wanted to use it as a brasserie, they said this food doesn’t seem to be stacking up against this gorgeous decor.
So in order to make Eleven Madison Park into a restaurant that could fulfill its greatest potential, we had to not only listen to our guests but we had to listen to the architecture because the architecture, the bones of that building are not going to change. It’s a gorgeous, beautiful space with lights streaming in. So I feel like we finally gave the space the restaurant it deserved.
Recorded on September 17, 2009
After 24 years without a closing, Union Square Hospitality group CEO Danny Meyer thinks the key to maintaining a brand is to have a sharp point of view.
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.