‘SpongeBob’ creator Stephen Hillenburg dies at 57
By ANDREW DALTON
AP Entertainment Writer
Tuesday, November 27
LOS ANGELES (AP) — Stephen Hillenburg, who used his dual loves of drawing and marine biology to spawn the absurd undersea world of “SpongeBob SquarePants,” has died, Nickelodeon announced Tuesday.
Hillenburg died Monday of Lou Gehrig’s disease, also known as ALS, the cable network said in a statement. He was 57.
He had announced he had the disease in March 2017. His death comes just weeks after the passing of another cartoon hero in Marvel creator Stan Lee.
Hillenburg conceived, wrote, produced and directed the animated series that began in 1999 and bloomed into hundreds of episodes, movies and a Broadway show.
The absurdly jolly SpongeBob and his yell-along theme song that opened “Who lives in a pineapple under the sea?!” quickly appealed to college kids and parents as much as it did kids.
“The fact that it’s undersea and isolated from our world helps the characters maintain their own culture,” Hillenburg told The Associated Press in 2001. “The essence of the show is that SpongeBob is an innocent in a world of jaded characters. The rest is absurd packaging.”
Its vast cast of oceanic creatures included SpongeBob’s starfish sidekick Patrick, his tightwad boss Mr. Krabs, squirrel pal Sandy Cheeks and always-exasperated neighbor Squidward Tentacles.
While Hillenburg introduced and popularized exotic creatures like the sea sponge (which in the real world is not square,) Bikini Bottom was a realm like no other, real or fictional. SpongeBob can play his nose like a flute and could not possibly be happier to work his fast-seafood job of flipping Krabby Patties.
But he has his troubles, too. He constantly fails his boat-driving test, forcing his frightened blowfish teacher to inflate. In one episode he suffers a broken butt and is afraid to leave his pineapple home for days.
“I don’t want to face my fears,” SpongeBob, voiced by Tom Kenny, says in another episode. “I’m afraid of them!”
Born at his father’s army post in Lawton, Oklahoma, Hillenburg graduated from Humboldt State University in California in 1984 with a degree in natural resource planning with an emphasis on marine resources, and went on to teach marine biology at the Orange County Marine Institute.
While there he drew a comic, “The Intertidal Zone,” that he used as a teaching tool. It featured anthropomorphic ocean creatures that were precursors to the characters on “SpongeBob.”
Hillenburg shifted to drawing and earned a master of fine arts degree in animation from the California Institute of the Arts in 1992.
That same year he created an animated short called “Wormholes” that won festival plaudits and helped land him a job on the Nickelodeon show “Rocko’s Modern Life,” where he worked from 1993 to 1996 before he began to build SpongeBob’s undersea world of Bikini Bottom, which showed off his knowledge of marine life and willingness to throw all the details out the window.
“We know that fish don’t walk,” he told the AP, “and that there is no organized community with roads, where cars are really boats. And if you know much about sponges, you know that living sponges aren’t square.”
The show was an immediate hit that has lost no momentum in the nearly 20 years since its creation and helped define the culture of Nickelodeon.
“He was a beloved friend and long-time creative partner to everyone at Nickelodeon, and our hearts go out to his entire family,” Nickelodeon’s statement said. “His utterly original characters and the world of Bikini Bottom will long stand as a reminder of the value of optimism, friendship and the limitless power of imagination.”
Its nearly 250 episodes have won four Emmy Awards and 15 Kids’ Choice Awards, and led to an endless line of merchandise to rival any other pop cultural phenomenon of the 2000s.
“When you set out to do a show about a sponge, you can’t anticipate this kind of craze,” Hillenburg told the AP in 2002.
In 2004, the show shifted to the big screen with “The SpongeBob SquarePants Movie” and a 2015 sequel, “The SpongeBob Movie: Sponge Out of Water.”
Intensely involved in every aspect of the show initially, Hillenburg after the 2004 film stepped back into an executive producer role on the show, where he remained for the rest of his life.
A musical stage adaptation bowed on Broadway in 2017, with music from such stars as Steven Tyler, Sara Bareilles and John Legend. It earned 12 Tony Award nominations, including one for best performance by a leading actor for Ethan Slater.
“I am heartbroken to hear of the passing of Stephen Hillenburg,” Slater said in an email Tuesday. “Through working on ‘SpongeBob,’ I got to know him not only as a creative genius, but as a truly generous and kind person. He warmly embraced us on Broadway as the newest members of his wonderful ‘SpongeBob’ family, and made it so clear from the get-go why he is so beloved: genuine kindness.”
Hillenburg is survived by his wife of 20 years Karen Hillenburg, son Clay, mother Nancy Hillenburg, and a brother, Brian Kelly Hillenburg.
Follow Andrew Dalton on Twitter: https://twitter.com/andyjamesdalton.
Ohio Insurance Director Secures Leadership Roles in National Regulatory Organizations
COLUMBUS — Ohio Department of Insurance Director Jillian Froment has been chosen to serve in prominent leadership roles in 2019 for two national insurance organizations focused on consumer protection and the modernization of state insurance regulation.
Froment was re-elected to chair the Interstate Insurance Product Regulation Commission, also referred to as the Insurance Compact. In addition, she has been elected as secretary treasurer of the National Association of Insurance Commissioners (NAIC) Midwest Zone – regulators representing all Midwest states participate in the NAIC Midwest Zone group.
“I look forward to working with member states and regulators to ensure there is a focus on consumer protection while supporting a growing industry with consistent and common sense regulatory standards,” Froment said. “Ohio has one of the largest insurance markets in the world, therefore it is important we have a strong voice at a national level when it comes to setting priorities and establishing policies that impact industry and the consumers it serves.”
Officers in the Midwest Zone also serve as members of the NAIC’s executive committee – the group responsible for setting priorities and strategic planning for the NAIC. In addition to being elected to these leadership roles, Froment serves as vice-chair of the NAIC Life and Annuities Insurance Committee and is a member of the Financial Condition Committee.
The Insurance Compact, a collection of most U.S. states, ensures consumer safeguards are in asset protection insurance products such as for life insurance, annuities, disability income and long-term care insurance.
The NAIC is the U.S. standard-setting and regulatory support organization created and governed by the chief insurance regulators from the 50 states, the District of Columbia and five U.S. territories. Through the NAIC, state insurance regulators establish standards and best practices, and coordinate their regulatory oversight.
What big data can tell us about how a book becomes a best-seller
November 28, 2018
Author of The Formula, Linked, and Bursts, Northeastern University
Disclosure statement: Barabási’s research laboratory is funded by several U.S. Federal Agencies and Foundations, and EU Funding Agencies. He is also affiliated with Harvard Medical School and Central European University in Budapest, Hungary.
The average American reads 12 or 13 books a year, but with over 3 million books in print, the choices they face are staggering.
Despite the introduction of 100,000 new titles each year, only a tiny fraction of these attract a large enough readership to make The New York Times best-seller list.
Which raises the questions: How does a book become a best-seller, and which types of books are more likely to make the list?
I’m a data scientist. Recently, with help of Burcu Yucesoy, a postdoc in my lab, I put the reading habits of Americans under our data microscope.
We did so by analyzing the sales patterns of the 2,468 fiction and 2,025 nonfiction titles that made The New York Times best-seller list for hardcovers during the last decade.
Real lives, imaginary action
The first thing the data reminded me is just how few books in my favorite category, science, become best-sellers – a paltry 1.1 percent. Science books compete for a spot on the nonfiction list with everything from business to history, sports to religion.
Yet, on the whole, hardcovers in these categories don’t fly off the shelves, either.
Which nonfiction titles do? Memoir and biographies, with almost half of the 2,025 nonfiction best-sellers falling into this category.
Then we examined the fiction list. Much of the press focuses on literary fiction – books we see debated by critics, lauded as important and culturally relevant, and eventually taught in schools.
But in the past decade, only 800 books categorized as literary fiction made the best-seller list. Most best-sellers – 67 percent of all fiction titles – represent plot-driven genres like mystery or romance or the kind of thrillers that Danielle Steel and Clive Cussler write.
Action sells – there’s no surprise there.
But it was unexpected the degree to which only a handful of authors repeatedly appear: Eight-five percent of best-selling novelists have landed multiple books on the list. Mystery and thriller novelist James Patterson, for example, had 51 books on the best-seller list in the period we explored. James Patterson has sold over 100 million copies of his book, grossing more than US $1 billion in sales.
By contrast, only 14 percent of nonfiction authors had more than one best-selling book. Perhaps this is because the genre often requires expertise on a specific subject matter. If an author primarily writes about football, or neuroscience, or even her own life, it’s difficult to generate 10 books on the topic.
A universal sales curve
Publishers eagerly slap “New York Times Bestseller” stickers on each book that appears on the list’s 15 slots.
A quarter of those, however, have only a cameo appearance, briefly grabbing a spot at the bottom of the list and dropping out after a single week. Only 37 percent have some staying power and spend more than four weeks on the best-seller list. Even fewer – 8 percent – attain the number one spot.
Some rare exceptions can lease out a spot for years: “The Help” by Kathryn Stockett lingered on the fiction list for an astonishing 131 weeks, while Laura Hillenbrand’s “Unbroken” stayed on the nonfiction list for a record 203 weeks.
One big misconception is that you have to write a mega-seller to make the list. The majority of titles on The New York Times best-seller list only sell between 10,000 and 100,000 copies in their first year. “The Slippery Year,” a 2009 memoir by Melanie Gideon, made the list with a yearly sale of fewer than 5,000 copies.
How is this possible?
Our data set shows that just about your only chance of making the list is right after your publication date.
That’s because book sales, we discovered, follow a universal sales curve – there’s a single mathematical formula that captures the weekly sales of all books. And that sales curve has a prominent peak right after the release, meaning you sell the most copies during the first weeks after your book’s release. Fiction sales almost always peak within the first two to six weeks; for nonfiction, the peak can come any time during the first 15 weeks.
While you might assume that there would be overlooked books that build their audiences slowly and eventually make it onto the hallowed list, there really aren’t.
It’s all about the timing
In other words, what happens during a brief window of time can foretell a book’s success.
For this reason, the timing of the release matters a great deal, especially since the threshold to reach the list varies throughout the year.
In February or March, selling a few thousand copies can land a book on the best-seller list; in December – when sales skyrocket during the holidays – selling 10,000 copies a week might not guarantee a book a spot.
So when should authors publish?
It depends on their circumstances. If they lack a strong fan base, and their hope is to simply make it onto the best-seller list, it’s best to aim for February or March.
At the same time, appearing on The New York Times best-seller list doesn’t necessarily guarantee that a book will sell more copies. Research shows that appearing on the list tends to boost sales only for unknown authors, and the effect disappears after one to three weeks.
So for well-known authors or celebrities who already have built-in fan bases, appearing on the best-seller list might not matter as much. Instead, they’ll likely want to maximize sales – in which case, it’s best to publish in late October: The release will coincide with peak sales in December, when bookstores are packed with Christmas shoppers.
The good news is that if you’re like me – and have written several books that didn’t end up as best-sellers – you still have a chance to break through: Our analysis shows that only 14 percent of novelists made the list with their first book.
5 ways to help robots work together with people
November 28, 2018
Making the most of human-robot collaborations will require good teamwork.
Professor of Human Systems Engineering, Arizona State University
Nancy Cooke receives funding from the Office of Naval Research Science of Autonomy program, the Air Force Office of Scientific Research Trust and Influence program and the Army Research Laboratory.
Partners: Arizona State University provides funding as a member of The Conversation US.
For most people today, robots and smart systems are servants that work in the background, vacuuming carpets or turning lights on and off. Or they’re machines that have taken over repetitive human jobs from assembly-line workers and bank tellers. But the technologies are getting good enough that machines will be able work alongside people as teammates – much as human-dog teams handle tasks like hunting and bomb detection.
There are already some early examples of robots and people teaming up. For example, soldiers use drones for surveillance and ground robots for bomb disposal as they carry out military missions. But the U.S. Army envisions increased teaming of soldiers, robots and autonomous systems in the next decade. Beyond the military, these human-robot teams will soon start working in fields as diverse as health care, agriculture, transportation, manufacturing and space exploration.
Researchers and companies are exploring lots of avenues for improving how robots and artificial intelligence systems work – and technical advances are important. As an applied cognitive scientist who has conducted research on human teaming in highly technical settings, I can say human-robot systems won’t be as good as they could be if the designers don’t understand how to engineer technologies that work most effectively with real people. A few basic concepts from the deep body of scholarly research into human teamwork can help develop and manage these new relationships.
1. Different jobs
Teams are necessarily groups of people with separate, though interdependent, roles and responsibilities. A surgical team, for instance, might include a nurse, a surgeon and an anesthesiologist. Similarly, members of a human-robot team should be assembled to take on different elements of a complex task.
Robots should do things they are best at, or that people don’t want to do – like lifting heavy items, testing chemicals and crunching data. That frees up people to do what they’re best at – like adapting to changing situations and coming up with creative solutions to problems.
A human-robot surgical team might have a human surgeon conducting laparoscopic or minimally invasive surgery with assistance from a robot manipulator with cameras that is inserted into the patient and operated externally by the surgeon. The view can be augmented by overlaying medical imaging data on the patient’s internal anatomy on the camera view.
Planning for this sort of division of labor suggests people shouldn’t replicate themselves in machines. In fact, humanoid-shaped robots or robots and AI that mimic human social behavior may mislead their human teammates into having unrealistic expectations of what they can do.
2. Mutual backup
Effective teams’ members know that everyone has a different role – but are available to support each other when necessary. The disastrously fatal response to Hurricane Katrina in 2005 was partly the result of confusion and lack of coordination among government agencies and other groups like the Red Cross.
Teammates need to understand their own roles and those of the rest of the team, and how they fit together. They also need to be able to use this knowledge to avoid stepping on teammates’ toes, while anticipating others’ potential needs. Robots and artificial intelligence need to understand how their parts of the task relate to the parts their teammates are doing, and how they might be able to help as needed.
3. Common understanding
Effective teams share knowledge about the team goals and the current situation and this facilitates their interactions – even when direct communication is not possible.
The benefit of shared knowledge allows all sorts of collaborations and coordinations. For instance, when inflating a hot air balloon, the pilot is at one end, in the basket monitoring the burner. A crew member must be at the far end of the balloon, steadying it by holding a rope attached to its top. They can’t see or hear each other because the balloon blocks the view and the propane burner drowns out any other sound. But if they’re trained well, neither needs to communicate to know what the other is doing, and know what needs to happen next.
The connection team members have comes not only from information they all know, but shared knowledge developed through experience working together. Some scholars have suggested that robots can’t build experience and shared knowledge with humans, while other researchers are working on finding ways to actually do that. Machine learning will likely be a key factor in helping robots develop expectations of their coworkers’ behavior. Coupled with human intelligence, each side will learn about the other’s capabilities, limitations and idiosyncrasies.
4. Effective interaction and communication
Team members need to interact; effective teaming depends greatly on the quality of those interactions. In hospital teams for emergency resuscitation of patients, team interaction and communication are crucial. Those teams are often made up of whatever medical personnel are nearest to the patient, and members need to know right away what happened before the patient’s heart stopped – a life is at stake.
Yet even between people, communication isn’t always seamless. Between people and robots there are even more challenges – like making sure they share understandings of how words are used or what appropriate responses are to questions. Artificial intelligence researchers are making great strides in advancing computers’ ability to understand, and even produce, natural language – as many people experience with their smart assistant devices like Amazon’s Alexa and Google Home, and mobile and car-based GPS directions systems.
It’s not even clear if typical human communication is the best model for human-robot teams. Human-dog teams do fine without the use of natural language. Navy SEALs can work together at highly effective levels without uttering a word. Bees communicate location of resources with a dance. Communication does not have to involve words; it could include sound signals and visual cues. If a robot was tending the patient when their heart stopped, it could indicate what happened on a monitor that all resuscitation team members could see.
5. Mutual trust
Interpersonal trust is important in human teams. If trust breaks down among a team of firefighters, they’ll be less effective and may cost lives – each other’s or members of the public they’re trying to help. The best robot teammates will be trustworthy and reliable – and any breaches in reliability need to be explained.
But even with an explanation, technology that is chronically unreliable is likely to be rejected by human teammates. That’s even more vital in safety-critical technology, like autonomous vehicles.
Robots are not automatically capable of teaming with humans. They need to be assigned effective roles on the team, understand other team roles, train with human team members to develop common understanding, develop an effective way to communicate with humans, and be reliable and trustworthy. Most importantly, humans should not be asked to adapt to their nonhuman teammates. Rather, developers should design and create technology to serve as a good team player alongside people.