Quote of the week: 

“Most of us have jobs that are too small for our spirits.” ― Studs Terkel

On Leonardo Da Vinci’s obsessions and curiosities

There’s a great little anecdote in this recent Ben Wilson podcast about what historians found in Leonardo Da Vinci’s notebook: Ideas for a helicopter on one page, sketches of scuba gear on the next, an analysis of a dragonfly’s wings, and so on. As Wilson—creator of the How to Take Over the World podcast—argues, there is no doubt that Da Vinci was a genius, but it was his profound sense of curiosity that makes him such a fascinating character to study and learn from. “I think Da Vinci is a one of one,” Wilson says. “I’ve never seen or read about a mind like his ever, anywhere. You’re probably not wired like Da Vinci. And that’s okay. I’m not. I don’t know anyone that is. But I think anyone can learn how to be more curious by learning from his example. And curiosity, it turns out, is a superpower.” Wilson continues: 

“Da Vinci is widely regarded as one of the greatest artists of all time, if not the greatest artist of all time. He was a shockingly insightful amateur scientist… He made observations about physics, biology, engineering, and material sciences that would take centuries to replicate. He was also a tinkerer, an amateur inventor who came up with a number of useful inventions, and laid the groundwork for even more. Steve Jobs said of Da Vinci, he saw beauty in both art and engineering. And his ability to combine them was what made him a genius.”


How to come up with good ideas

In 2014, researchers queried more than 200 people from three distinct industries—roofing, inline skating, and carpentry—about how to make each industry safer. You might think that carpenters would have no novel ideas about how to make inline skating safer, but, in fact, the opposite turned out to be true. “The team found that those from ‘analogous markets’ were significantly better at generating original ideas,” writes Mario Gabriele in his recent essay, “Where Do Great Ideas Come From?” “Roofers had more original concepts for carpenters and inline skaters than for themselves, for example. Interestingly, the greater the distance the participant had from the target problem, the more novel their ideas.” Gabriele’s essay offers provocative insights for investors, operators, and founders who are looking to augment their creative capacity in the search for new (and good) ideas.

“The decrement of ideas makes their study all the more important. Rather than diminishing them, we should seek to understand better how, where, and by who they are created. What incentives encourage originality? Who should you hire to boost an organization’s innovation? And how do you harness the abilities of a collective?… Academia is always in conversation with itself; arguments, conflicts, and gradations should be expected. We approach these findings with curiosity, humility, and the hope that they spark new ideas and open fresh perspectives for us all.”


Beware of highly correlated opinions (and other thoughts from Kevin Kelly)

“If your views on other things can be predicted from your views on one thing, you need to be very careful that you’re not in the grip of an ideologue,” says Kevin Kelly in a recent conversation with The Knowledge Project’s Shane Parrish. Kelly is one of my favorite essayists, technologists, and modern-day philosophers—you may recall his excellent 103 Bits of Advice in Issue #58 of The Nightcrawler. True to form, Kelly’s conversation with Parrish is full of insights about a wide range of subjects, from long-termism to AI. I find his comments on the importance of thinking independently to be especially resonant today as AI encroaches into many elements of our lives. “The idea is to not be so predictable,” Kelly says. “If your views on the environment can be deduced from your views on religion or something, that means that you are not really that much of an independent thinker.”

“So there’s a lot of concern [from] artists and even writers about training an AI to produce work, to generate work, creative work. And there the concern is ‘Well, my material that I’ve worked really hard [to create] has been used to train this AI and people can use it to imitate me.’ And sometimes those imitations are quite amazing. Really, what you want to be able to do is to have a style, so to speak, to have something that’s unpredictable, [un-imitable], that you can’t be imitated. And this again goes back to my other piece of advice about ‘Don’t aim to be the best; aim to be the only.’ So if you are in this category [in which] it’s hard to imitate you, that’s a really good place to be in the human world. And also a really good place to be in the AI world because AIs will have difficulty in imitating.”

A few more links I enjoyed:

“Experts consume a wealth of case studies, stories and history, but not only to create hard-and-fast rules. They also do it to build a massive database for their intuition. Each new situation is an opportunity to update the model, rather than something to be overfitted to a stale one. One way to think of it is that reality is so variable and complex that you don’t always know which part of which story will be useful in advance. Perhaps most importantly for these chaotic times, deep expert intuition is able to respond to increasingly novel circumstances far more effectively.”
“Keeping our technology secret was always a tenuous proposition. Google researchers are leaving for other companies on a regular cadence, so we can assume they know everything we know, and will continue to for as long as that pipeline is open. But holding on to a competitive advantage in technology becomes even harder now that cutting edge research in LLMs is affordable. Research institutions all over the world are building on each other’s work, exploring the solution space in a breadth-first way that far outstrips our own capacity. We can try to hold tightly to our secrets while outside innovation dilutes their value, or we can try to learn from each other.”

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