Category Archives: Creativity

Answers: 3 Ducks or 9 Ducks …. 1 Puppy or 9 Puppies

Source: AsiaOne (Singapore), Mar 2020

The question was asked in picture format for ducks or dogs, rather than explicitly writing “ducks” or “dogs”.

While some of us would count the number of animals as they are without even thinking, but not for this P1 girl. She matched the number of ducks and dogs exactly as how they looked in the picture given.

Alan Kay’s Vision for the iPad

Source: WorryDream, Nov 2011

In 1968 — three years before the invention of the microprocessor — Alan Kay stumbled across Don Bitzer’s early flat-panel display. Its resolution was 16 pixels by 16 pixels — an impressive improvement over their earlier 4 pixel by 4 pixel display

Alan saw those 256 glowing orange squares, and he went home, and he picked up a pen, and he drew a picture of a goddamn iPad.

And then he chased that carrot through decades of groundbreaking research, much of which is responsible for the hardware and software that you’re currently reading this with.

That’s the kind of ambitious, long-range vision I’m talking about. Pictures Under Glass is old news. Let’s start using our hands.

A 4.1/4.0 for his Stanford PhD!

Source: Ed Boyden, Oct 2019

Related Resources:

Huffington Post, Sep 2016

Synthesize new ideas constantly.

Never read passively. Annotate, model, think, and synthesize while you read, even when you’re reading what you conceive to be introductory stuff.

That way, you will always aim towards understanding things at a resolution fine enough for you to be creative

Conversations with Tyler, Apr 2019

we don’t actually have theories — detailed knowledge — enough to make predictive, interesting models, for example, of how we form emotions, of how we make decisions.

… questions about attention-focusing drugs like Ritalin or Adderall. Maybe they make people more focused, but are you sacrificing some of the wandering and creativity that might exist in the brain and be very important for not only personal productivity but the future of humanity?

I think one of the things that I really love about the space of ecological diversity is, if you think of brains as computing things, then ecological diversity might provide many ways of computing the same thing but in different ways that actually yield interesting computational insights or aesthetic outcomes.

I think architecture is very important. I find architecture to be very inspiring for scientific ideas.

My group started at the MIT Media Lab, and now we have half our group over here in the MIT McGovern Institute, but I used to wander the halls of campus late at night to just look at stuff, the posters in the hallway. I get inspiration by trying to connect dots from different fields or disciplines or even entirely separate, unconnected topics. I find a lot of productivity from inspirational environments and connecting dots between random things.

COWEN: Now, you were first hired here by the Media Lab, is that correct?

BOYDEN: I was.

COWEN: They were a different ecosystem, and they saw some reason to hire you, where other groups didn’t see the same reason.

BOYDEN: Yeah. I was writing up these faculty applications to propose to set up a full-time neurotechnology group — let’s control the brain, let’s map the brain. At the time, the majority of the places that I applied to for faculty jobs actually turned me down.

So I went to the Media Lab to talk to people there. I’d been an undergrad researcher there. That’s when I was doing work on quantum computing, for example. It was just sheer dumb luck. They had a job opening that they couldn’t fill, and they said, “Why don’t you apply?”

COWEN: A job opening for what?

BOYDEN: I can’t recall the details. It might have been a professor of education or something. I forget what it was. But they said, “You know what? We’re the Media Lab. Maybe our new mission is to hire misfits.”

It’s a great place for people between one field and another where there’s sort of some space. But you know what? It could be an entire new discipline. Now, flash forward 12 years later, we actually started a center for neuroengineering here at MIT that I co-direct.

I think I learn more from individuals and their variability than from categories of people. For example, in our group at MIT, I have two PhD students. Neither finished college, actually. I can’t think of any other neuroscience groups on Earth where that’s true.

COWEN: And you hired them.

BOYDEN: I did, yeah.

COWEN: Knowing they didn’t finish college. And that was a plus? Or, “I’ll hire them in spite of this”?

BOYDEN: Well, one of them had been a Thiel fellow and then decided that it could be good to have an ecosystem in academia to support a long-term biotechnology play, and it’s hard to do biotechnology all by yourself. The other was a college dropout who was working as a computer tech support person next door, and both of them are now leading very independent projects.

Again, I try to look more at the individual, and I try to get to know people over a long period of time to learn what they’re good at and how they can maybe make a contribution based upon their unique experience. That’s different from what people have done traditionally.

BOYDEN: I think there’s so much crosstalk nowadays. I read a statistic that 40 percent of the professors at MIT trained at one point in their career at Stanford, Harvard, or MIT. So there’s a lot of crosstalk that goes back and forth. I think one of the themes in science is that you end up learning different things and bringing multiple things to bear.

COWEN: How should we improve the funding of science in this country?

BOYDEN: I like to look at the history of science to learn about its future, and one thing I’ve learned a lot over the last couple years — and it’s even happened to me — is that it’s really hard to fund pioneering ideas.

The third thing I would do is I would go looking for trouble. I would go looking for serendipity.

One idea is, how do we find the diamonds in the rough, the big ideas but they’re kind of hidden in plain sight? I think we see this a lot. Machine learning, deep learning, is one of the hot topics of our time, but a lot of the math was worked out decades ago — backpropagation, for example, in the 1980s and 1990s. What has changed since then is, no doubt, some improvements in the mathematics, but largely, I think we’d all agree, better compute power and a lot more data.

So how could we find the treasure that’s hiding in plain sight? One of the ideas is to have sort of a SWAT team of people who go around looking for how to connect the dots all day long in these serendipitous ways.

COWEN: Does that mean fewer committees and more individuals?

BOYDEN: Or maybe individuals that can dynamically bring together committees. “Hey, you’re a yogurt scientist that’s curious about this weird CRISPR molecule you just found. Here’s some bioinformaticists who are looking to find patterns. Here’s some protein engineers who love — ”

COWEN: But should the evaluators be fewer committees and more individuals? The people doing the work will always be groups, but committees, arguably, are more conservative. Should we have people with more dukedoms and fiefdoms? They just hand out money based on what they think?

BOYDEN: A committee of people who have multiple non-overlapping domains of knowledge can be quite productive.

But in economics and in other fields, it also seems like people are trying to make better maps of things and how they interact.

BOYDEN: One way to think of it is that, if a scientific topic is really popular and everybody’s doing it, then I don’t need to be part of that. What’s the benefit of being the 100,000th person working on something?

So I read a lot of old papers. I read a lot of things that might be forgotten because I think that there’s a lot of treasure hiding in plain sight. As we discussed earlier, optogenetics and expansion microscopy both begin from papers from other fields, some of which are quite old and which mostly had been ignored by other people.

I sometimes practice what I call failure rebooting. We tried something, or somebody else tried something, and it didn’t work. But you know what?

Something happened that made the world different. Maybe somebody found a new gene. Maybe computers are faster. Maybe some other discovery from left field has changed how we think about things. And you know what? That old failed idea might be ready for prime time.

With optogenetics, people were trying to control brain cells with light going back to 1971. I was actually reading some earlier papers. There were people playing around with controlling brain cells with light going back to the 1940s. What is different? Well, this class of molecules that we put into neurons hadn’t been discovered yet.

COWEN: The same is true in economics, I think. Most of behavioral economics you find in Adam Smith and Pigou, who are centuries old.

BOYDEN: Wow. I almost think search engines like Google often are trying to look at the most popular things, and to advance science, what we almost need is a search engine for the most important unpopular things.

COWEN: Last question. As a researcher, what could and would you do with more money?

BOYDEN: Well, I’m always looking for new serendipitous things, connecting the dots between different fields. These ideas always seem a bit crazy and are hard to get funded. I see that both in my group but also in many other groups.

I think if I was given a pile of money right now, what I would like to do is to find a way — not just in our group but across many groups — to try to find those unfundable projects where, number one, if we think about the logic of it, “Hey, there’s a non-zero chance it could be revolutionary.”

Number two, we can really, in a finite amount of time, test the idea. And if it works, we can dynamically allocate more money to it. But if it doesn’t work, then we can de-allocate money to it.

I would like to go out and treasure hunt. Let’s look at the old literature. Let’s look at people who might be on the fringes of science, but they don’t have the right connections, like the people who I talked about earlier. They’re not quite in the right place to achieve the rapid scale-up of the project. But by connecting the dots between people and topics, you know what? We could design an amazing project together.

China’s Dilemma: Control vs Creativity

Source: Economist, Dec 2019

Related Resource: QZ, Dec 2019

Fudan University, a prestigious Chinese university known for its liberal atmosphere, recently deleted “freedom of thought” from its charter and added paragraphs pledging loyalty to the Chinese Communist Party, further eroding academic freedom in China.

In a notice (link in Chinese) revealing the revised version of its 2014 constitution submitted by Fudan that was published on the education ministry’s website yesterday (Dec. 17), the Shanghai university was found to have made more than 40 revisions to its bylaws. The changes went into effect in early December, according to the notice. In

the original version, the university said that its “educational philosophy” was in accordance to the values advocated in its school song (video in Chinese), which are “academic independence and freedom of thought.” In the revised version, “freedom of thought” was taken out.

Established in 1905 by Ma Xiangbo, a famous Chinese Jesuit priest and educator, Fudan got its name from the Confucian quotation “heavenly light shines day after day.” The school is known particularly for its education, medicine, and sociology departments, and has produced many of the country’s most famous politicians.

On Chinese social network Weibo, users expressed their disbelief at the revisions and concerns that it spells the beginning of Fudan’s decline. “I am really worried that children in the future will never know that Fudan had a period of valuing ‘freedom of thought’ and ‘academic independence’,” said one user (link in Chinese)

Conversations with Tyler, Dec 2019

what makes China exceptional is that — like no other despotic, extractive society in history — it has a complete obsession with innovation and technology.

China is the first society that’s really systematically trying to do that. China wants to keep the despotic control of the Chinese Communist Party while at the same time be a leader in digital technology, leader in Telecom, leader in AI, and it’s pouring a lot of resources. It’s providing incentives, and the question is whether this is going to succeed. My view is, it is not a complete failure, but it’s not going to be a huge success.

there are tensions. You really need — you called it individualism. I’m happy to call it that. I would have called it something differently. But you need that individualism spark. You need that experimentation for the most radical type of innovations to take place, and China is missing that. It’s going to try to pour more and more resources to make up for it, but I’m not sure whether it’s going to work.

https://www.inkstonenews.com/education/chinese-college-professor-qu-weiguos-full-graduation-speech/article/3015786

Claude Shannon on Creative Thinking

Source: Creativity Post, Aug 2017

A very small percentage of the population produces the greatest proportion of the important ideas.

I think we could set down three things that are fairly necessary for scientific research or for any sort of inventing or mathematics or physics or anything along that line. I don’t think a person can get along without any one of these three.

The first one is obvious — training and experience. You don’t expect a lawyer, however bright he may be, to give you a new theory of physics these days or mathematics or engineering.

The second thing is a certain amount of intelligence or talent. In other words, you have to have an IQ that is fairly high to do good research work. I don’t think that there is any good engineer or scientist that can get along on an IQ of 100, which is the average for human beings. In other words, he has to have an IQ higher than that. Everyone in this room is considerably above that. This, we might say, is a matter of environment; intelligence is a matter of heredity.

Those two I don’t think are sufficient. I think there is a third constituent here, a third component which is the one that makes an Einstein or an Isaac Newton.

For want of a better word, we will call it motivation. In other words, you have to have some kind of a drive, some kind of a desire to find out the answer, a desire to find out what makes things tick. If you don’t have that, you may have all the training and intelligence in the world, you don’t have questions and you won’t just find answers.

This is a hard thing to put your finger on. It is a matter of temperament probably; that is, a matter of probably early training, early childhood experiences, whether you will motivate in the direction of scientific research. I think that at a superficial level, it is blended use of several things. This is not any attempt at a deep analysis at all, but my feeling is that a good scientist has a great deal of what we can call curiosity. I won’t go any deeper into it than that.

He wants to know the answers. He’s just curious how things tick and he wants to know the answers to questions; and if he sees thinks, he wants to raise questions and he wants to know the answers to those.

What Evolution Teaches Us About Creativity

Source: Kirkus Reviews, Jun 2019

Most readers associate evolution with Darwinian natural selection, but Wagner points out its limited creative capacity.

In natural selection, a better adapted organism produces more offspring. This preserves good traits and discards bad ones until it reaches a peak of fitness. This process works perfectly in an “adaptive landscape” with a single peak, but it fails when there are many—and higher—peaks.

Conquering the highest—true creativity—requires descending into a valley and trying again. Natural selection never chooses the worse over the better, so it can’t descend.

Wagner devotes most of his book to the 20th-century discovery of the sources of true biological creativity: genetic drift, recombination, and other processes that inject diversity into the evolutionary process.

His final section on human creativity contains less hard science but plenty of imagination. The human parallel with natural selection is laissez faire competition, which is efficient but equally intolerant of trial and error.

Far more productive are systems that don’t penalize failure but encourage play, experimentation, dreaming, and diverse points of view.

In this vein, American schools fare poorly, but Asian schools are worse.

Related Resources:

https://www.santafe.edu/news-center/news/book-review-life-finds-way-andreas-wagner

“Exploratory play,” remarks Wagner, “is about creating a diversity of experiences or ideas, only some of which will eventually lead somewhere and be successful.”

Failure is key to success, Wagner insists, and it should be embraced as a necessary part of the creative process. “If we are honest with ourselves, we understand that we are failing more often than we are succeeding, and that is a very Darwinian concept,” he says. “Even very successful scientists have a lot of failures.”

https://inquisitivebiologist.wordpress.com/2019/07/17/book-review-life-finds-a-way-what-evolution-teaches-us-about-creativity/

as Life Finds a Way shows, not all solutions are equally good. To evolve from a suboptimal solution to a superior one usually involves several steps through intermediary solutions that are even worse, something that natural selection acts against. So how does evolution overcome such obstacles?

What if a population ends up on a suboptimal peak? From the image you can see that, unless you can do it in a single step, you cannot just descend one peak, move through a valley, and up the other peak. Natural selection will eliminate those individuals who “try”

how does nature get off suboptimal peaks? Biological traits are ultimately coded for by DNA and as biologists know, life has other options to change DNA than single mutations such as genetic drift and recombination.

The former is the chance disappearance of certain genes when all individuals carrying it die, something that is statistically much more likely in small populations.

The latter is the wholesale exchange of chromosome regions during meiosis, the cell divisions that creates sperm and egg cells. Drift is dangerous and can push whole populations away from fitness peaks and into extinction (this is why conservation biologists are so concerned about habitat fragmentation).

Wagner likens recombination to nothing less than teleportation; it allows offspring to take large leaps to a completely different part of an adaptive landscape.

Most combinations will be nonsensical, but many will not. Interestingly, Wagner’s computational work suggests that the number of viable genes or proteins encoded by these possibilities is vast. There are many possible solutions to a problem. So many, in fact, that they form networks. Wagner called it a hidden architecture that accelerates life’s ability to innovate.

Here too, finding better solutions sometimes requires big leaps, which can be brought about by play, daydreaming, or other means.

Elastic Thinking

Source: FS, Nov 2019

some suggestions for how to develop elastic thinking:

  • Cultivate a “beginner’s mind” by questioning situations as if you have no experience in them.
  • Introduce discord by pursuing relationships and ideas that challenge your beliefs.
  • Recognize the value of diversity.
  • Generate lots of ideas and don’t be bothered that most of them will be bad.
  • Develop a positive mood.
  • Relax when you see yourself becoming overly analytical.