The Long Now Foundation, established in 1996, is a private, non-profit organization based in San Francisco that seeks to become the seed of a very long-term cultural institution. It aims to provide a counterpoint to what it views as today’s “faster/cheaper” mindset and to promote “slower/better” thinking. The Long Now Foundation hopes to “creatively foster responsibility” in the framework of the next 10,000 years, and so uses 5-digit dates to address the Year 10,000 problem (e.g. by writing 02013 rather than 2013).
Civilization is revving itself into a pathologically short attention span. The trend might be coming from the acceleration of technology, the short-horizon perspective of market-driven economics, the next-election perspective of democracies, or the distractions of personal multi-tasking. All are on the increase. Some sort of balancing corrective to the short-sightedness is needed-some mechanism or myth which encourages the long view and the taking of long-term responsibility, where ‘long-term’ is measured at least in centuries. Long Now proposes both a mechanism and a myth.
Entoptic phenomena are visual effects whose source is within the eye itself.
Entoptic images have a physical basis in the image cast upon the retina. Hence, they are different from optical illusions, which are perceptual effects that arise from interpretations of the image by the brain. Because entoptic images are caused by phenomena within the observer’s own eye, they share one feature with optical illusions and hallucinations: the observer cannot share a direct and specific view of the phenomenon with others.
The vision of the brain as a computer, which I still champion, is changing so fast. The brain’s a computer, but it’s so different from any computer that you’re used to. It’s not like your desktop or your laptop at all, and it’s not like your iPhone except in some ways. It’s a much more interesting phenomenon. What Turing gave us for the first time (and without Turing you just couldn’t do any of this) is a way of thinking in a disciplined way about phenomena that have, as I like to say, trillions of moving parts. Until late 20th century, nobody knew how to take seriously a machine with a trillion moving parts. It’s just mind-boggling.
You couldn’t do it, but computer science gives us the ideas, the concepts of levels, virtual machines implemented in virtual machines implemented in virtual machines and so forth. We have these nice ideas of recursive reorganization of which your iPhone is just one example and a very structured and very rigid one at that.
We’re getting away from the rigidity of that model, which was worth trying for all it was worth. You go for the low-hanging fruit first. First, you try to make minds as simple as possible. You make them as much like digital computers, as much like von Neumann machines, as possible. It doesn’t work. Now, we know why it doesn’t work pretty well. So you’re going to have a parallel architecture because, after all, the brain is obviously massively parallel.
It’s going to be a connectionist network. Although we know many of the talents of connectionist networks, how do you knit them together into one big fabric that can do all the things minds do? Who’s in charge? What kind of control system? Control is the real key, and you begin to realize that control in brains is very different from control in computers. Control in your commercial computer is very much a carefully designed top-down thing.
You really don’t have to worry about one part of your laptop going rogue and trying out something on its own that the rest of the system doesn’t want to do. No, they’re all slaves. If they’re agents, they’re slaves. They are prisoners. They have very clear job descriptions. They get fed every day. They don’t have to worry about where the energy’s coming from, and they’re not ambitious. They just do what they’re asked to do and do it brilliantly with only the slightest tint of comprehension. You get all the power of computers out of these mindless little robotic slave prisoners, but that’s not the way your brain is organized.
Each neuron is imprisoned in your brain. I now think of these as cells within cells, as cells within prison cells. Realize that every neuron in your brain, every human cell in your body (leaving aside all the symbionts), is a direct descendent of eukaryotic cells that lived and fended for themselves for about a billion years as free-swimming, free-living little agents. They fended for themselves, and they survived.
A treatise on postmodern literary criticism by Chip Morninstar:
You get maximum style points for being French. Since most of us aren’t French, we don’t qualify for this one, but we can still score almost as much by writing in French or citing French sources. However, it is difficult for even the most intense and unprincipled American academician writing in French to match the zen obliqueness of a native French literary critic. Least credit is given for a clear, rational argument which makes its case directly, though of course that is what I will do with our example since, being gainfully employed, I don’t have to worry about graduation or tenure. And besides, I’m actually trying to communicate here.
John Bohannon on Zhao Bowen, a 21-year-old leading genetic researcher on what makes some humans — like him — geniuses:
Zhao’s goal is to use those machines to examine the genetic underpinnings of genius like his own. He wants nothing less than to crack the code for intelligence by studying the genomes of thousands of prodigies, not just from China but around the world. He and his collaborators, a transnational group of intelligence researchers, fully expect they will succeed in identifying a genetic basis for IQ. They also expect that within a decade their research will be used to screen embryos during in vitro fertilization, boosting the IQ of unborn children by up to 20 points. In theory, that’s the difference between a kid who struggles through high school and one who sails into college.
Getting awfully close to Gattaca.
If parents use IVF to conceive, then a genetic test—an extension of the screening tests for genetic diseases that are already routinely done on embryos—could let them pick the smartest genome from a batch of, say, 20 embryos. “It’s almost like there are 20 parallel universes,” Hsu says. “These are all really your kids.” You’re just choosing the ones with the greatest genetic potential for intelligence. But effectively, you could be giving an unborn child a boost in IQ above their parents. As Hsu sees it, this is no Faustian bargain. “Aren’t we doing them a great service?” Over the long term, he proclaims, this would “improve the average IQ of the species by quite a bit.” He hopes governments will even provide it for free; Singapore, he predicts, would be the first to sign up.
Did I say “awfully close”? Nevermind.
Edsger W. Dijkstra in 1972:
I observe a cultural tradition, which in all probability has its roots in the Renaissance, to ignore this influence, to regard the human mind as the supreme and autonomous master of its artefacts. But if I start to analyse the thinking habits of myself and of my fellow human beings, I come, whether I like it or not, to a completely different conclusion, viz. that the tools we are trying to use and the language or notation we are using to express or record our thoughts, are the major factors determining what we can think or express at all! The analysis of the influence that programming languages have on the thinking habits of its users, and the recognition that, by now, brainpower is by far our scarcest resource, they together give us a new collection of yardsticks for comparing the relative merits of various programming languages.
Original paper [pdf].
Peter Jonason’s other publications are generally related to the Dark Triad and/or mating:
"Playing hard-to-get: Manipulating one’s perceived availability as a mate."
"Avoiding entangling commitments: Tactics for implementing a short-term mating strategy."
"The “booty call”: A compromise between men and women’s ideal mating strategies."
"It’s not all about the Benjamins: Understanding preferences for mates with resources."
Now scientists at the Riken-M.I.T. Center for Neural Circuit Genetics at the Massachusetts Institute of Technology say they have created a false memory in a mouse, providing detailed clues to how such memories may form in human brains.
The plot of about a thousand shitty science fiction movies (and a few decent ones) just came true.
West of the Flower Washing Stream,
not far downstream from the bridge,
the master has chosen a quiet spot
here in the woods by the river.
Living apart from the city crowds,
the world loosens its grip;
murmuring of this clear water dissolves
the sadness that burdens a stranger.
Countless dragonflies play in the air,
dancing up and down;
a pair of wild ducks out in the stream
swim and dive together.
You could take a boat downstream,
thousands of miles to the east
or else forget the boat, and live
here by this stream forever.
When I taught remedial English in the East End, I had my students compose their own best- and worst-case scenarios for ten years later. The nightmares were fabulous: lush with fantastic fears, hilarious with misadventure. The pipedreams were all the same: a string of products and brand names. They read like mail-order catalogs. My students’ visions of the Good Life were so vapid and depressing that you could have got the two assignments confused
Thus, parents in good condition, based on health, size, dominance or other traits, would invest more in producing sons, whose inherited strength and bulk could help them better compete in the mating market and give them greater opportunities to produce more offspring. Conversely, mothers in poor condition would likely play it safe, producing more daughters, whose productivity is physiologically limited. Other hypotheses make similar predictions — that females who choose mates with particularly “good genes” (e.g. for attractiveness) should produce so called “sexy sons” as a result, Garner said.
A granfalloon, in the fictional religion of Bokononism (created by Kurt Vonnegut in his 1963 novel Cat’s Cradle), is defined as a “false karass.” That is, it is a group of people who outwardly choose or claim to have a shared identity or purpose, but whose mutual association is actually meaningless.
The most commonly purported granfalloons are associations and societies based on a shared but ultimately fabricated premise. As examples, Vonnegut cites: “the Communist Party, the Daughters of the American Revolution, the General Electric Company —and any nation, anytime, anywhere.” A more general and oft-cited quote defines a granfalloon as “a proud and meaningless association of human beings.” Another granfalloon example illustrated in the book were Hoosiers, of which the narrator (and Vonnegut himself) was a member.