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Can “Zebras” Fix What “Unicorns” Break?

Posted on Thursday, October 26th, 02017 by Ahmed Kabil
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Long Now Partners with Zebra Movement to Help Bring Long-Term Thinking to Startups and Venture Capital

The disruptive potential of Silicon Valley, epitomized in the mantra to “move fast and break things”, was once praised as its killer feature. These days, it is increasingly perceived as a bug.  Startups come and go, but the underlying structure of tech and venture capital persists. Entrepreneurs and investors have grown accustomed to the idea of limited runway, quick exits, and short-term gains, while accepting a 90% failure rate among startups as simply the cost of admission for playing the game. “Growth becomes the overriding motivation,” Noam Cohen wrote in a recent piece for The New York Times. “Something treasured for its own sake, not for anything it brings to the world.”

Entrepreneurs Jennifer Brandel, Mara Zepeda, Astrid Scholz, and Aniyia Williams are after a different sort of disruption—one that transforms tech and venture capital through long-term thinking and alternative business models that result in both profit and social impact. They call their project the Zebra Movement.

Founders of the Zebra Movement. From left: Jennifer Brandel, Co-Founder and CEO of Hearken; Mara Zepeda, Co-Founder and CEO of Switchboard; Astrid Scholz, Co-Founder and CEO of Sphaera; and Aniyia Williams, Co-Founder and CEO of Tinsel / Black & Brown Founders.

It started in 02016, when the Zebra founders wrote a provocative essay that deployed sex metaphors to critique the startup status quo of chasing “unicorns”:

Much is made about Silicon Valley’s culture of “innovation.” But the model for startup venture financing, and the system of rewards driving this supposed innovation, isn’t creative — it’s masturbatory. It wastes potential. It’s uninspired. It leaves founders like us staring at the ceiling.

Yes, we want to build businesses that succeed financially. But we also want so much more than that, and we aren’t alone. Most of the founders we know, many of whom happen to be women, are driven to build companies that generate money and meaning. And they’re in it for the long haul — not just to get their jollies, make their names, and exit.

The essay went viral, generating responses from hundreds of founders, investors, and advocates. The Zebra founders followed with a manifesto earlier this year to provide the beginnings of a solution to what they called the “broken” structure of technology and venture capital.

This is an urgent problem. For in this game, far more than money is at stake. When VC firms prize time on site over truth, a lucky few may profit, but civil society suffers. When shareholder return trumps collective well-being, democracy itself is threatened. The reality is that business models breed behavior, and at scale, that behavior can lead to far-reaching, sometimes destructive outcomes.

[…]

A company’s business model is the first domino in a long chain of consequences. In short: “The business model is the message.” From that business model flows company culture and beliefs, strategies for success, end-user experiences, and, ultimately, the very shape of society.

We believe that developing alternative business models to the startup status quo has become a central moral challenge of our time. These alternative models will balance profit and purpose, champion democracy, and put a premium on sharing power and resources. Companies that create a more just and responsible society will hear, help, and heal the customers and communities they serve.

The founders enlisted the Zebra as the symbol for their movement:

Why zebras?

  • To state the obvious: unlike unicorns, zebras are real.
  • Zebra companies are both black and white: they are profitable and improve society. They won’t sacrifice one for the other.
  • Zebras are also mutualistic: by banding together in groups, they protect and preserve one another. Their individual input results in stronger collective output
  • Zebra companies are built with peerless stamina and capital efficiency, as long as conditions allow them to survive.

Thousands responded after the Zebra founders proposed a conference to gather together and further define the goals and ethos of their movement. DazzleCon (a “dazzle” being a gathering of zebras) will be taking place from Wednesday, November 15 to Friday, November 17, 02017 in Portland, Oregon. Long Now has joined the Rockefeller Foundation, the MacArthur Foundation, and the Knight Foundation, among others, in supporting the Zebra founders by sharing resources, ideas and strategy for considering and applying long-term thinking to the growing conversation within the movement. We will be co-partnering with DazzleCon for the evening program of keynote talks on Wednesday, November 18th. (The evening program is open to the public; Long Now members can receive a $15 discount by entering the promo code LONGNOWDAZZLE on the Eventbrite page). 

We asked one of the founders, Mara Zepeda, to reflect on the role she believes long-term thinking should play in technology and Silicon Valley:

I grew up with many tattered copies of the Whole Earth Catalog. I would later connect with Howard Rheingold, who sits at the intersection of the Whole Earth Catalog ethos and technology, as a friend and teacher (we also both graduated from Reed College). I believe the deep, nuanced, systems thinking approach the Long Now Foundation promotes is so necessary in today’s culture. As the co-founder and CEO of a technology company, I’ve noticed its absence most acutely in technology, where a pervasive “winner takes all” culture of investor profits, billion dollar companies, and quick exits reigns supreme. Long-term thinking is what is so desperately needed in these times.

We need to return to the values of thinkers like Stewart Brand, Alan Kay, Howard Rheingold, Christopher Alexander, and Douglas Engelbart who believed that technology should augment humans, and create thriving ecosystems of collective intelligence.

In The Clock of the Long Now, Stewart Brand quotes institutional management advisor Rosabeth Moss Kanter. The gist is that people who take the long view will do so when they trust their leaders, the rules of the game are fair, they will share equitably in the returns, and feel a commitment to those who come after them. Zebra companies embody and promote these values of trust, shared prosperity, and a long-term investment in the earth, community, and each other.

Aligning around these principles creates better people, more ethical products, cooperative communities, and a kinder and more equitable world. We are thrilled to partner and share this wealth of knowledge across disciplines and generations.

If you’re interested in attending DazzleCon, or would like to know more about the Zebra Movement, head here. To attend the evening program at a discounted rate, enter LONGNOWDAZZLE on the Eventbrite page.

Galloping, GIFs and Genes: Geneticists Store Moving Image in Living Bacteria

Posted on Tuesday, August 22nd, 02017 by Ahmed Kabil
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In 01872, California Governor Leland Stanford hired the famed photographer Eadweard Muybridge to settle a question of popular debate—whether all four of a horse’s feet ever left the ground when it galloped. The resulting series of photographs, Sallie Gardner at a Gallop, showed without a doubt that horses do indeed go airborne at a full speed gait.

Sallie Gardner at a Gallop (1878)


As one of the earliest motion pictures ever made, Sallie Gardner at a Gallop became an icon of the scientific method in popular culture, demonstrating empirically what the human eye alone could not perceive. With the rise of animated GIFs as a form of visual communication in the 02010s, Sallie Gardner at a Gallop has found new life on the Internet.

It is perhaps fitting then, that Harvard researchers led by geneticist George Church chose Sallie Gardner at a Gallop to demonstrate one of the latest advances in genomics. As reported in July 02017 by Nature, the clip is the first motion picture to be encoded in the DNA of a living cell. Church, who is working with Revive and Restore to bring back the woolly mammoth from extinction, used CRISPR to enable the chronological recording of digital information, showcasing the genome’s potential as a storage device.

As the New York Times reported:

Dr. Church and Seth Shipman, a geneticist, and their colleagues began by assigning each pixel in the black-and-white film a DNA code based on its shade of gray. The vast chains of DNA in each cell are made of just four molecules — adenine, guanine, thymine and cytosine — arranged in enormously varied configurations.

The geneticists ended up with a sequence of DNA molecules that represented the entirety of the film. Then they used a powerful new gene editing technique, Crispr, to slip this sequence into the genome of a common gut bacteria, E. coli.

Despite the modification, the bacteria thrived and multiplied. The film stored in the genome was preserved intact with each new generation of progeny, the team found.

Geneticists hope to one day use the technology to record events in the cells of the human body, enabling doctors to playback the recording if someone gets sick—akin to the black boxes in airplanes that record data in crashes. For now, the advances demonstrate that Muybridge’s horse, which can now be retrieved and multiplied at will from the DNA of a living cell, can go viral in more ways than one.

Further Reading

 

The AI Cargo Cult: The Myth of a Superhuman Artificial Intelligence

Posted on Wednesday, July 5th, 02017 by Ahmed Kabil
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In a widely-shared essay first published in Backchannel, Kevin Kelly, a Long Now co-founder and Founding Editor of Wired Magazine, argues that the inevitable rise of superhuman artificial intelligence—long predicted by leaders in science and technology—is a myth based on misperceptions without evidence.

Kevin is now Editor at Large at Wired and has spoken in the Seminar and Interval speaking series several times, including on his most recent book, The Inevitable—sharing his ideas on the future of technology and how our culture responds to it. Kevin was part of the team that developed the idea of the Manual for Civilization, making a series of selections for it, and has also put forth a similar idea called the Library of Utility.

Read Kevin Kelly’s essay in full (LINK).

The Nuclear Bunker Preserving Movie History

Posted on Thursday, June 22nd, 02017 by Ahmed Kabil
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During the Cold War, this underground bunker in Culpeper, Virginia was where the government would have taken the president if a nuclear war broke out. Now, the Library of Congress is using it to preserve all manner of films, from Casablanca to Harry Potter. The oldest films were made on nitrate, a fragile and highly combustible film base that shares the same chemical compound as gunpowder. Great Big Story takes us inside the vault, and introduces us to archivist George Willeman, the man in charge of restoring and preserving the earliest (and most incendiary) motion pictures.

Göbekli Tepe and the Worst Day in History

Posted on Wednesday, May 24th, 02017 by Ahmed Kabil
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Technological advances are revolutionizing the field of archaeology, resulting in new discoveries that are upending our previous understanding of the birth of civilization. Many scholars believe that few will be as consequential as Göbekli Tepe.

The ruins of Göbekli Tepe. Photograph by Vincent J. Musi.


IN 01963, anthropologists from the University of Chicago and the University of Istanbul surveyed ruins atop of a hill in Southern Turkey that the locals called Göbekli Tepe (“potbelly hill” in Turkish). Examining the broken limestone slabs dotting the site, the anthropologists concluded that the mound was nothing more than a Byzantine cemetery—a dime a dozen in the ruin-rich Levant region.

Three decades later, German archaeologist Klaus Schmidt made a startling claim: Göbekli Tepe was the site of the world’s oldest temple. Geomagnetic surveys of the site revealed circles of  limestone megaliths dating back 11,600 years—seven millennia before the construction of Stonehenge and the Great Pyramids of Giza, six millennia before the invention of writing, and five centuries before the development of agriculture.

Photograph by Vincent J. Musi.


The implications of Schmidt’s discoveries were profound, and called into question previous archaeological and scientific understandings about the Neolithic Revolution, the key event in human development pointed to as the birth of human civilization. “We used to think agriculture gave rise to cities and later, to civilization,” journalist Charles Mann wrote in a 02011 National Geographic cover story on the site. “[Göbekli Tepe] suggests the urge to worship sparked civilization.” As Andrew Curry of The Smithsonian put it after a visit to Göbekli Tepe with Schmidt:

Scholars have long believed that only after people learned to farm and live in settled communities did they have the time, organization and resources to construct temples and support complicated social structures. But Schmidt argues it was the other way around: the extensive, coordinated effort to build the monoliths literally laid the groundwork for the development of complex societies.

Einkorn wheat was first domesticated near Göbekli Tepe—perhaps, posits Charles Mann, to feed those who came to worship. Photo by Vincent J. Musi.


Schmidt believed that humans made pilgrimages to Göbekli Tepe from as far away as 90 miles. But then there’s the question of what, exactly, these pilgrims were worshipping. As Curry mused after his visit to Göbekli Tepe:

What was so important to these early people that they gathered to build (and bury) the stone rings? The gulf that separates us from Gobekli Tepe’s builders is almost unimaginable. Indeed, though I stood among the looming megaliths eager to take in their meaning, they didn’t speak to me. They were utterly foreign, placed there by people who saw the world in a way I will never comprehend. There are no sources to explain what the symbols might mean

In a March 02017 article in the Journal of Mediterranean Archaeology and Archaeometry, Martin B. Sweatman and Dimitrios Tsikritsis proposed a bold theory: the pillars are telling the story of a comet hitting the earth and triggering an ice age some 13,000 years ago. The comet strike, known as the Younger Dryas Impact Event, is hypothesized to have set off a global cooling period that depleted hunter-gatherer resources and forced humans to settle into areas where they could cultivate crops.

On the left, an artistic rendering of the Younger Dryas Impact Event. On the right, the night sky around 10,950 BC when the impact hypothetically occurred. Image: Martin B. Sweatman and Dimitrios Tsikritsis


Combining the approaches of astronomy and archaeology, Sweatman and Tsikritsis claim that the animals carved on the pillars depict constellations, with the famous vulture stone indicating a time stamp of the night sky at the time of the catastrophe. Using computer software, Sweatman and Tsikritsis matched the animal carving to patterns of the stars, yielding three possibilities that synced up to their astronomical interpretations, plus or minus 250 years: 02000, 4350 BCE, 10,950 BCE, and 18,000 BCE.

The date of 10,950 BCE aligns with the latest hypotheses as to when the Younger Dryas Impact Event occurred, lending credence to Sweatman and Tsikritsis’ interpretation that the Vulture Stone depicts what Sweatman calls “probably the worst day in history since the end of the Ice Age.”

The famous vulture stone, which Sweatman and Tsikritsis claim depicts the constellations of the night sky. Photo by Vincent J. Musi.


But, as Becky Ferreira of Motherboard reports, there’s reason to regard Sweatman and Tsikritsis’ claims with skepticism. For one, many scholars do not accept the Younger Dryas Impact Hypothesis that a comet strike served as the catalyst for the Ice Age that followed. Some have also criticized Sweatman and Tsikritsis’ study for omitting crucial information to make their case. Archaeologist Jens Notroff, a researcher at the Göbekli Tepe site, takes Sweatman and Tsikritsis to task for failing to mention that the headless man on the vulture stone, which they claim symbolizes the devastating loss of human life after the comet, also possesses an erect phallus—hardly a robust indicator of loss of life.

“There’s more time between Gobekli Tepe and the Sumerian clay tablets [etched in 3300 B.C.] than from Sumer to today,” says Gary Rollefson, an archaeologist at Whitman College in Walla Walla, Washington. “Trying to pick out symbolism from prehistoric context is an exercise in futility.”

Perhaps. But if the recent archaeological discoveries are any indication, we are often mistaken in our assumptions about the complexity and historic trajectory of ancient civilizations. Time will tell. And technology will help.

FURTHER READING

As of this writing, Sweatman and Tsikritsis are working on a rebuttal to critiques of their paper.

Read Sweatman and Tsikritsis’ article in full.

Göbekli Tepe was added to the UNESCO World Heritage Tentative List five years ago and is expected to become a protected UNESCO Heritage site next year.

Read our February 02017 feature on how one historian is combining the approaches of comparative mythology of evolutionary biology with new computational modeling technologies to reconstruct some of humanity’s oldest myths.

Read Charles Mann’s National Geographic story in full. Mann also gave a Seminar for Long Now in April 02012.

The Other 10,000 Year Project: Long-Term Thinking and Nuclear Waste

Posted on Thursday, March 16th, 02017 by Ahmed Kabil
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With half-lives ranging from 30 to 24,000, or even 16 million years , the radioactive elements in nuclear waste defy our typical operating time frames. The questions around nuclear waste storage — how to keep it safe from those who might wish to weaponize it, where to store it, by what methods, for how long, and with what markings, if any, to warn humans who might stumble upon it thousands of years in the future—require long-term thinking.

The Yucca Mountain nuclear waste repository was set to open on March 21, 02017, but has been indefinitely delayed / via High Country News

I. “A Clear and Present Danger.”

“For anyone living in SOCAL, San Onofre nuclear waste is slated to be buried right underneath the sands,” tweeted @JoseTCastaneda3 in February 02017. “Can we say ‘Fukushima #2’ yet?”

The “San Onofre” the user was referring to is the San Onofre nuclear plant in San Diego County, California, which sits on scenic bluffs overlooking the Pacific Ocean and sands dotted with surfers and beach umbrellas. Once a provider of eighteen percent of Southern California’s energy demands, San Onofre is in the midst of a 20-year, $4.4 billion demolition project following the failure of replacement steam generators in 02013. At the time, Senator Barbara Boxer said San Ofore was “unsafe and posed a danger to the eight million people living within fifty miles of the plant,” and opened a criminal investigation.

A part of the demolition involved figuring out what to do with the plant’s millions of pounds of high-level waste (the “spent fuel” leftover after uranium is processed) that simmered on-site in nuclear pools.  It was decided that the nuclear waste would be transported a few hundred yards to the beach, where it would be buried underground in what local residents have taken to calling the “concrete monolith” – a state of the art dry cask storage container that will house 75 concrete-sealed tubes of San Onofre’s nuclear waste until 2049.

This has left a lot of San Diego County residents unhappy.

The San Onofre Nuclear Generating Station seen from San Onofre State Beach in San Clemente / via Jeff Gritchen, OC Register

“We held a sacred water ceremony today @ San Onofre where 3.6mm lbs of nuclear waste are being buried on the beach near the San Andreas faultline,” tweeted Gloria Garrett, hinting at a nuclear calamity to come.

Congressman Darrell Issa, who represents the district of the decommissioned plant and introduced a bill in February 02017 to relocate the waste from San Onofre, was concerned about the bottom line.

“It’s just located on the edge of an ocean and one of the busiest highways in America,” Issa said in an interview with the San Diego Tribune. “We’ll be paying for storage for decades and decades if we don’t find a solution. And that will be added to your electricity bill.”

“The issue of what to do with nuclear waste is a clear and present danger to every human life within 100 miles of San Onofre,” said Charles Langley of the activist group Public Watchdogs.

“Everyone is whistling past the graveyard, including our regulators,” Langley continued. “They are storing nuclear waste that is deadly to humans for 10,000 generations in containers that are only guaranteed to last 25 years.”

II. The Nuclear Waste Stalemate

Nobody wants a nuclear waste storage dump in their backyards.

That is, in essence, the story of America’s pursuit of nuclear energy as a source of electricity for the last sixty years.

In 01957, the first American commercial nuclear reactor opened in the United States.  That same year, the National Academy of Sciences (NAS) recommended that spent fuel should be transported from reactors and buried deep underground. Those recommendations went largely unheeded until the Three Mile Island meltdown of March 01979, when 40,000 gallons of radioactive wastewater from the reactor poured into Pennsylvania’s Susquehanna River.

The political challenge of convincing any jurisdiction to store nuclear waste for thousands of years has vexed lawmakers ever since. As Marcus Stroud put it in his in-depth 02012 investigative feature into the history of nuclear waste storage in the United States:

Though every presidential administration since Eisenhower’s has touted nuclear power as integral to energy policy (and decreased reliance on foreign oil), none has resolved the nuclear waste problem. The impasse has not only allowed tens of thousands of tons of radioactive waste to languish in blocks of concrete behind chain link fences near major cities. It has contributed to a declining nuclear industry, as California, Wisconsin, West Virginia, Oregon, and other states have imposed moratoriums against new power plants until a waste repository exists. Disasters at Fukushima, Chernobyl, and Three Mile Island have made it very difficult, expensive, and time-consuming to build a nuclear reactor because of insurance premiums and strict regulations, and the nuclear waste stalemate has added significantly to the difficulties and expenses. Only two new nuclear power plants have received licenses to operate in the last 30 years.

Yucca Mountain was designated as the site for a national repository of nuclear waste in the Nuclear Waste Act of 01987. It was to be a deep geological repository for permanently sealing off and storing all of the nation’s nuclear waste, one that would require feats of engineering and billions of dollars to build. Construction began in the 01990s.  The repository was scheduled to open and begin accepting waste on March 21, 02017.

But pushback from Nevadans, who worried about long-term radiation risks and felt that it was unfair to store nuclear waste in a state that has no nuclear reactors, left the project defunded and on indefinite hiatus since 02011.

Today, nuclear power provides twenty percent of America’s electricity, producing almost 70,000 tons of waste a year. Most of the 121 nuclear sites in the United States opt for the San Onofre route, storing waste on-site in dry casks made of steel and concrete as they wait for the Department of Energy to choose a new repository.

III. Opening Ourselves to Deep Time

“We must have the backbone to look these enormous spans of time in the eye. We must have the courage to accept our responsibility as our planet’s – and our descendants’ – caretakers, millennium in and millennium out, without cowering before the magnitude of our challenge.” —Vincent Ialenti

An aerial view of Posiva Oy’s prospective nuclear waste repository site in Olkiluoto, Finland / via Posiva Oy

Anthropologist Vincent Ialenti  recently spent two years doing field work with a Finnish team of experts who were in the process of researching the Onkalo long term geological repository in Western Finland that, like Yucca Mountain, would store all of the Finland’s nuclear waste. The Safety Case project, as it was called, required experts to think in deep time about the myriad of factors (geological, ecological, and climatological) that might affect the site as it stored waste for thousands of years.

Ialenti’s goal was to examine how these experts conceived of the future:

What sort of scientific ethos, I wondered, do Safety Case experts adopt in their daily dealings with seemingly unimaginable spans of time? Has their work affected how they understand the world and humanity’s place within it? If so, how? If not, why not?

In the process, Ialenti found that his engagement with problems of deep time (“At what pace will Finland’s shoreline continue expanding outward into the Baltic Sea? How will human and animal populations’ habits change? What happens if forest fires, soil erosion or floods occur? How and where will lakes, rivers and forests sprout up, shrink and grow? What role will climate change play in all this?”) changed the way he conceived of the world around him, the stillness and serenity of  the landscapes transforming into a “Finland in flux”:

I imagined the enormous Ice Age ice sheet that, 20,000 years ago, covered the land below. I imagined Finland decompressing when this enormous ice sheet later receded — its shorelines extending outward as Finland’s elevation rose ever higher above sea level. I imagined coastal areas of Finland emerging from the ice around 10,000 BC. I imagined lakes, rivers, forests and human settlements sprouting up, disappearing and changing shape and size over the millennia.

Ialenti’s field work convinced him of the necessity of long-term thinking in the Anthropocene, and that engaging with the problem of nuclear waste storage, unlikely though it may seem, is a useful way of inspiring it:

Many suggest we have entered the Anthropocene — a new geologic epoch ushered in by humanity’s own transformations of Earth’s climate, erosion patterns, extinctions, atmosphere and rock record. In such circumstances, we are challenged to adopt new ways of living, thinking and understanding our relationships with our planetary environment. To do so, anthropologist Richard Irvine has argued, we must first “be open to deep time.” We must, as Stewart Brand has urged, inhabit a longer “now.”

So, I wonder: Could it be that nuclear waste repository projects — long approached by environmentalists and critical intellectuals with skepticism — are developing among the best tools for re-thinking humanity’s place within the deeper history of our environment? Could opening ourselves to deep, geologic, planetary timescales inspire positive change in our ways of living on a damaged planet?

IV. How Long is Too Long?

Finland’s Onkalo repository for nuclear waste / via Remon

Finland’s Onkalo Repository  is designed to last for 100,000 years. In the 01990s, the U.S. Environmental Protection Agency decided that a 10,000 year-time span was how long a U.S. nuclear waste storage facility must remain sealed off, basing their decision in part on the predicted frequencies of ice ages.

But as Stroud reports, it was basically guesswork:

Later, [the 10,000-year EPA standard] was increased to a million years by the U.S. Court of Appeals in part due to the long half lives of certain radioactive isotopes and in part due to a significantly less conservative guess.

The increase in time from 10,000 years to 1 million years made the volcanic cones at Yucca look less stable and million-year-old salt deposits — like those found in New Mexico — more applicable to the nuclear waste problem.

[The Department of Energy] hired anthropologists to study the history of language—both at Yucca and at the WIPP site in New Mexico—to conceive of a way to communicate far into the future that waste buried underground was not to be disturbed.

But the Blue Ribbon Commission’s report [of 02012] calls these abstract time periods a little impractical.

“Many individuals have told [BRC] that it is unrealistic to have a very long (e.g., million-year) requirement,” it reads. “[BRC] agrees.”
It then points out that other countries “have opted for shorter timeframes (a few thousand to 100,000 years), some have developed different kinds of criteria for different timeframes, and some have avoided the use of a hard ‘cut-off’ altogether.” The conclusion? “In doing so, [these countries] acknowledge the fact that uncertainties in predicting geologic processes, and therefore the behavior of the waste in the repository, increase with time.”

Public Law 102-579, 106, Statute 4777 calls for nuclear waste to be stored for at least 10,000 years / via EPA

In a spirited 02006 Long Now debate between Global Business Network co-founder and Long Now board member Peter Schwartz and Ralph Cavanagh of the Nuclear Resources Defense Council, Cavanagh pressed Schwartz on the problem of nuclear waste storage.

Schwartz contended that we’ve defined the nuclear waste problem incorrectly, and that reframing the time scale associated with storage, coupled with new technologies, would ease concerns among those who take it on:

The problem of nuclear waste isn’t a problem of storage for a thousand years or a million years. The issue is storing it long enough so we can put it in a form where we can reprocess it and recycle it, and that form is probably surface storage in very strong caskets in relatively few sites, i.e., not at every reactor, and also not at one single national repository, but at several sites throughout the world with it in mind that you are not putting waste in the ground forever where it could migrate and leak and raise all the concerns that people rightly have about nuclear waste storage. By redesigning the way in which you manage the waste, you’d change the nature of the challenge fundamentally.

Schwartz and other advocates of recycling spent fuel have discussed new pyrometallurgical technologies for reprocessing that could make nuclear power “truly sustainable and essentially inexhaustible.” These emerging pyro-processes, coupled with faster nuclear reactors, can capture upwards of 100 times more of the energy and produce little to no plutonium, thereby easing concerns that the waste could be weaponized.  Recycling spent fuel would  vastly reduce the amount of high-level waste, as well as the length of time that the waste must be isolated. (The Argonne National Laboratory believes its pyrochemical processing methods can drop the time needed to isolate waste from 300,000 years to 300 years).

There’s just one problem: the U.S. currently does not reprocess or recycle its spent fuel. President Jimmy Carter banned the commercial reprocessing of nuclear waste in 01977 over concerns that the plutonium in spent fuel could be extracted to produce nuclear weapons. Though President Reagan lifted the ban in 01981, the federal government has for the most part declined to provide subsidies for commercial reprocessing, and subsequent administrations have spoken out against it. Today, the “ban” effectively remains in place.

Inside Onkalo / via Posiva Oy

When the ban was first issued, the U.S. expected other nuclear nations like Great Britain and France to follow suit. They did not. Today, France generates eighty percent of its electricity from nuclear power, with much of that energy coming from reprocessing and recycling spent fuel. Japan and the U.K reprocess their fuel, and China and India are modeling their reactors on France’s reprocessing program. The United States, on the other hand, uses less than five percent of its nuclear fuel, storing the rest as waste.

In a 02015 op-ed for Forbes, William F. Shughart, research director for the Independent Institute in Oakland, California, argued that we must lift the nuclear recycling “ban” and take full advantage our nuclear capacity if we wish to adequately address the threats posed by climate change:

Disposing of “used” fuel in a deep-geologic repository as if it were worthless waste – and not a valuable resource for clean-energy production – is folly.

Twelve states have banned the construction of nuclear plants until the waste problem is resolved. But there is no enthusiasm for building the proposed waste depository. In fact, the Obama administration pulled the plug on the one high-level waste depository that was under construction at Nevada’s Yucca Mountain.

The outlook might be different if Congress were to lift the ban on nuclear-fuel recycling, which would cut the amount of waste requiring disposal by more than half. Instead of requiring a political consensus on multiple repository sites to store nuclear plant waste, one facility would be sufficient, reducing disposal costs by billions of dollars.

By lifting the ban on spent fuel recycling we could make use of a valuable resource, provide an answer to the nuclear waste problem, open the way for a new generation of nuclear plants to meet America’s growing electricity needs, and put the United States in a leadership position on climate-change action.

According to Stroud, critics of nuclear processing cite its cost (a Japanese government report from 02004 found reprocessing to be four times as costly as non-reprocessed nuclear power); the current abundance of uranium (Stroud says most experts agree that “if the world’s needs quadrupled today, uranium wouldn’t run out for another eighty years”); the fact that while reprocessing produces less waste, it still wouldn’t eliminate the need for a site to store it; and finally, the risk of spent fuel being used to make nuclear weapons.

Shughart, along with Schwartz and many others in the nuclear industry, feels the fears of nuclear proliferation from reprocessing are overblown:

The reality is that no nuclear materials ever have been obtained from the spent fuel of a nuclear power plant, owing both to the substantial cost and technical difficulty of doing so and because of effective oversight by the national governments and the International Atomic Energy Agency.

V. Curiosity Kills the Ray Cat

Whether we ultimately decide to store spent fuel for 10,000 years in a sealed off repository deep underground or for 300 years in above-ground casks, there’s still the question of how to effectively mark nuclear waste to warn future generations who might stumble upon it. The languages we speak now might not be spoken in the future, so the written word must be cast aside in favor of “nuclear semiotics” whose symbols stand the test of time.

After the U.S. Department of Energy assembled a task force of anthropologists and linguists to tackle the problem in 01981, French author Françoise Bastide and Italian semiologist Paolo Fabbri proposed an intriguing solution: ray cats.

Artist rendering of ray cats / via Aeon

Imagine a cat bred to turn green when near radioactive material. That is, in essence, the ray cat solution.

“[Their] role as a detector of radiation should be anchored in cultural tradition by introducing a suitable name (eg, ‘ray cat’)” Bastide and Fabbri wrote at the time.

The idea has recently been revived. The Ray Cat Movement was established in 02015 to “insert ray cats into the cultural vocabulary.”

Alexander Rose, Executive Director at Long Now who has visited several of the proposed nuclear waste sites, suggests however that solutions like the ray cats only address part of the problem.

“Ray cats are cute, but the solution doesn’t promote a myth that can be passed down for generations,” he said. “The problem isn’t detection technology. The problem is how you create a myth.”

Rose said the best solution might be to not mark the waste sites at all.

“Imagine the seals on King Tut’s tomb,” Rose said. “Every single thing that was marked on the tomb are the same warnings we’re talking about with nuclear waste storage: markings that say you will get sick and that there will be a curse upon your family for generations. Those warnings virtually guaranteed that the tomb would be opened if found.”

The unbroken seal on King Tutankhamun’s tomb

“What if you didn’t mark the waste, and instead put it in a well engineered, hard to get to place that no one would go to unless they thought there was something there. The only reason they’d know something was there was if the storage was marked.”

Considering the relatively low number of casualties that could come from encountering nuclear waste in the far future, Rose suggests that likely the best way to reduce risk is avoid attention.

VI. A Perceived Abundance of Energy

San Onofre’s nuclear waste will sit in a newly-developed Umax dry-cask storage container system made of the most corrosion-resistant grade of stainless steel. It is, according to regulators, earthquake-ready.

At San Onofre, wood squares mark the spots where containers of spent fuel will be encased in concrete / via Jeff Gritchen, OC Register

Environmentalists are nonetheless concerned that the storage containers could crack, given the salty and moist environment of the beach. Others fear that an earthquake coupled with a tsunami cause a Fukushima-like meltdown on the West Coast.

“Dry cask storage is a proven technology that has been used for more than three decades in the United States, subject to review and licensing by the U.S. Nuclear Regulatory Commission,” said a spokeswoman for Edison, the company that runs San Onofre, in an interview with the San Diego Union Tribune.

A lawsuit is pending in the San Diego Supreme Court that challenges the California Coastal Commission’s 02015 permit for the site. A hearing is scheduled for March 02017. If the lawsuit is successful, the nuclear waste in San Onofre might have to move elsewhere sooner than anybody thought.

Meanwhile, the U.S. Department of Energy in January 02017 started efforts to move nuclear waste to temporary storage sites in New Mexico and West Texas that could store the waste until a more long-term solution is devised. Donald Trump’s new Secretary of Energy, former Texas governor Rick Perry, is keen to see waste move to West Texas. Residents of the town of Andrews are split. Some see it as a boon for jobs. Others, as a surefire way to die on the job.

Regardless of how Andrews’ residents feel, San Onofre’s waste could soon be on the way.

Tom Palmisano, Chief Nuclear Officer for Edison, the company that runs San Onofre, expressed doubts and frustration in an interview with the Orange County Register:

There could be a plan, and a place, for this waste within the next 10 years, Palmisano said – but that would require congressional action, which in turn would likely require much prodding from the public.

“We are frustrated and, frankly, outraged by the federal government’s failure to perform,” he said. “I have fuel I can ship today, and throughout the next 15 years. Give me a ZIP code and I’ll get it there.”

A prodding public might be in short supply. According to the latest Gallup poll, support for nuclear power in the United States has dipped to a fifteen-year low.  For the first time since Gallup began asking the question in 01994, a majority of Americans (54%) oppose nuclear as an alternative energy source.

Support for nuclear energy in the United States / via Gallup

Gallup suggests the decline in support is prompted less by fears about safety after incidents like the 02011 Fukushima nuclear plant meltdown, and more by  “energy prices and the perceived abundance of energy sources.” Gallup found that Americans historically only perceive a looming energy shortage when gas prices are high. Lower gas prices at the pump over the last few years have Americans feeling less worried about the nation’s energy situation than ever before.

Taking a longer view, the oil reserves fueling low gas prices will continue to dwindle. With the risks of climate change imminent, many in the nuclear industry argue that nuclear power would radically reduce CO2 levels and provide a cleaner, more efficient form of energy.

But if a widespread embrace of nuclear technology comes to pass, it will require more than a change in sentiment in the U.S. public about its energy future. It will require people embracing the long-term nature of dealing with nuclear waste, and ultimately, to trust future generations to continue to solve these issues.

 

A Brief Economic History of Time

Posted on Thursday, March 16th, 02017 by Ahmed Kabil
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“The age of exploration and the industrial revolution completely changed the way people measure time, understand time, and feel and talk about time,” writes Derek Thompson of The Atlantic. “This made people more productive, but did it make them any happier?”

In a wide-ranging essay touching upon the advent of the wristwatch, railroads, and Daylight Saving Time, Thompson reveals how the short-term time frames in our day-to-day experience that are so familiar to us — concepts like the work day, happy hour, the weekend, and retirement—were inventions of the last 150 years of economic change:

Three forces contributed to the modern invention of time. First, the conquest of foreign territories across the ocean required precise navigation with accurate timepieces. Second, the invention of the railroad required the standardization of time across countries, replacing the local system of keeping time using shadows and sundials. Third, the industrial economy necessitated new labor laws, which changed the way people think about work.

“So much of what we now call time,” concludes Thompson, “is a collective myth.” This collective myth helped power the industrial revolution and make our modern world. But, as Stewart Brand wrote at the founding of the Long Now Foundation, it has also contributed to civilization “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.

You can read Thompson’s essay in its entirety here.

Richard Feynman and The Connection Machine

Posted on Wednesday, February 8th, 02017 by Ahmed Kabil
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One of the most popular pieces of writing on our site is Long Now co-founder Danny Hillis’ remembrance of building an experimental computer with theoretical physicist Richard Feynman. It’s easy to see why: Hillis’ reminisces about Feynman’s final years as they worked together on the Connection Machine are at once illuminating and poignant, and paint a picture of a man who was beloved as much for his eccentricity as his genius.

Photo by Faustin Bray

Photo by Faustin Bray

Richard Feynman and The Connection Machine

by W. Daniel Hillis for Physics Today

Reprinted with permission from Phys. Today 42(2), 78 (01989). Copyright 01989, American Institute of Physics.

One day when I was having lunch with Richard Feynman, I mentioned to him that I was planning to start a company to build a parallel computer with a million processors. His reaction was unequivocal, “That is positively the dopiest idea I ever heard.” For Richard a crazy idea was an opportunity to either prove it wrong or prove it right. Either way, he was interested. By the end of lunch he had agreed to spend the summer working at the company.

Richard’s interest in computing went back to his days at Los Alamos, where he supervised the “computers,” that is, the people who operated the mechanical calculators. There he was instrumental in setting up some of the first plug-programmable tabulating machines for physical simulation. His interest in the field was heightened in the late 1970’s when his son, Carl, began studying computers at MIT.

I got to know Richard through his son. I was a graduate student at the MIT Artificial Intelligence Lab and Carl was one of the undergraduates helping me with my thesis project. I was trying to design a computer fast enough to solve common sense reasoning problems. The machine, as we envisioned it, would contain a million tiny computers, all connected by a communications network. We called it a “Connection Machine.” Richard, always interested in his son’s activities, followed the project closely. He was skeptical about the idea, but whenever we met at a conference or I visited CalTech, we would stay up until the early hours of the morning discussing details of the planned machine. The first time he ever seemed to believe that we were really going to try to build it was the lunchtime meeting.

Richard arrived in Boston the day after the company was incorporated. We had been busy raising the money, finding a place to rent, issuing stock, etc. We set up in an old mansion just outside of the city, and when Richard showed up we were still recovering from the shock of having the first few million dollars in the bank. No one had thought about anything technical for several months. We were arguing about what the name of the company should be when Richard walked in, saluted, and said, “Richard Feynman reporting for duty. OK, boss, what’s my assignment?” The assembled group of not-quite-graduated MIT students was astounded.

After a hurried private discussion (“I don’t know, you hired him…”), we informed Richard that his assignment would be to advise on the application of parallel processing to scientific problems.

“That sounds like a bunch of baloney,” he said. “Give me something real to do.”

So we sent him out to buy some office supplies. While he was gone, we decided that the part of the machine that we were most worried about was the router that delivered messages from one processor to another. We were not sure that our design was going to work. When Richard returned from buying pencils, we gave him the assignment of analyzing the router.

The Machine

The router of the Connection Machine was the part of the hardware that allowed the processors to communicate. It was a complicated device; by comparison, the processors themselves were simple. Connecting a separate communication wire between each pair of processors was impractical since a million processors would require $10^{12]$ wires. Instead, we planned to connect the processors in a 20-dimensional hypercube so that each processor would only need to talk to 20 others directly. Because many processors had to communicate simultaneously, many messages would contend for the same wires. The router’s job was to find a free path through this 20-dimensional traffic jam or, if it couldn’t, to hold onto the message in a buffer until a path became free. Our question to Richard Feynman was whether we had allowed enough buffers for the router to operate efficiently.

During those first few months, Richard began studying the router circuit diagrams as if they were objects of nature. He was willing to listen to explanations of how and why things worked, but fundamentally he preferred to figure out everything himself by simulating the action of each of the circuits with pencil and paper.

In the meantime, the rest of us, happy to have found something to keep Richard occupied, went about the business of ordering the furniture and computers, hiring the first engineers, and arranging for the Defense Advanced Research Projects Agency (DARPA) to pay for the development of the first prototype. Richard did a remarkable job of focusing on his “assignment,” stopping only occasionally to help wire the computer room, set up the machine shop, shake hands with the investors, install the telephones, and cheerfully remind us of how crazy we all were. When we finally picked the name of the company, Thinking Machines Corporation, Richard was delighted. “That’s good. Now I don’t have to explain to people that I work with a bunch of loonies. I can just tell them the name of the company.”

The technical side of the project was definitely stretching our capacities. We had decided to simplify things by starting with only 64,000 processors, but even then the amount of work to do was overwhelming. We had to design our own silicon integrated circuits, with processors and a router. We also had to invent packaging and cooling mechanisms, write compilers and assemblers, devise ways of testing processors simultaneously, and so on. Even simple problems like wiring the boards together took on a whole new meaning when working with tens of thousands of processors. In retrospect, if we had had any understanding of how complicated the project was going to be, we never would have started.

‘Get These Guys Organized’

I had never managed a large group before and I was clearly in over my head. Richard volunteered to help out. “We’ve got to get these guys organized,” he told me. “Let me tell you how we did it at Los Alamos.”

Every great man that I have known has had a certain time and place in their life that they use as a reference point; a time when things worked as they were supposed to and great things were accomplished. For Richard, that time was at Los Alamos during the Manhattan Project. Whenever things got “cockeyed,” Richard would look back and try to understand how now was different than then. Using this approach, Richard decided we should pick an expert in each area of importance in the machine, such as software or packaging or electronics, to become the “group leader” in this area, analogous to the group leaders at Los Alamos.

Part Two of Feynman’s “Let’s Get Organized” campaign was that we should begin a regular seminar series of invited speakers who might have interesting things to do with our machine. Richard’s idea was that we should concentrate on people with new applications, because they would be less conservative about what kind of computer they would use. For our first seminar he invited John Hopfield, a friend of his from CalTech, to give us a talk on his scheme for building neural networks. In 1983, studying neural networks was about as fashionable as studying ESP, so some people considered John Hopfield a little bit crazy. Richard was certain he would fit right in at Thinking Machines Corporation.

What Hopfield had invented was a way of constructing an [associative memory], a device for remembering patterns. To use an associative memory, one trains it on a series of patterns, such as pictures of the letters of the alphabet. Later, when the memory is shown a new pattern it is able to recall a similar pattern that it has seen in the past. A new picture of the letter “A” will “remind” the memory of another “A” that it has seen previously. Hopfield had figured out how such a memory could be built from devices that were similar to biological neurons.

Not only did Hopfield’s method seem to work, but it seemed to work well on the Connection Machine. Feynman figured out the details of how to use one processor to simulate each of Hopfield’s neurons, with the strength of the connections represented as numbers in the processors’ memory. Because of the parallel nature of Hopfield’s algorithm, all of the processors could be used concurrently with 100\% efficiency, so the Connection Machine would be hundreds of times faster than any conventional computer.

An Algorithm For Logarithms

Feynman worked out the program for computing Hopfield’s network on the Connection Machine in some detail. The part that he was proudest of was the subroutine for computing logarithms. I mention it here not only because it is a clever algorithm, but also because it is a specific contribution Richard made to the mainstream of computer science. He invented it at Los Alamos.

Consider the problem of finding the logarithm of a fractional number between 1.0 and 2.0 (the algorithm can be generalized without too much difficulty). Feynman observed that any such number can be uniquely represented as a product of numbers of the form $1 + 2^{-k]$, where $k$ is an integer. Testing each of these factors in a binary number representation is simply a matter of a shift and a subtraction. Once the factors are determined, the logarithm can be computed by adding together the precomputed logarithms of the factors. The algorithm fit especially well on the Connection Machine, since the small table of the logarithms of $1 + 2^{-k]$ could be shared by all the processors. The entire computation took less time than division.

Concentrating on the algorithm for a basic arithmetic operation was typical of Richard’s approach. He loved the details. In studying the router, he paid attention to the action of each individual gate and in writing a program he insisted on understanding the implementation of every instruction. He distrusted abstractions that could not be directly related to the facts. When several years later I wrote a general interest article on the Connection Machine for [Scientific American], he was disappointed that it left out too many details. He asked, “How is anyone supposed to know that this isn’t just a bunch of crap?”

Feynman’s insistence on looking at the details helped us discover the potential of the machine for numerical computing and physical simulation. We had convinced ourselves at the time that the Connection Machine would not be efficient at “number-crunching,” because the first prototype had no special hardware for vectors or floating point arithmetic. Both of these were “known” to be requirements for number-crunching. Feynman decided to test this assumption on a problem that he was familiar with in detail: quantum chromodynamics.

Quantum chromodynamics is a theory of the internal workings of atomic particles such as protons. Using this theory it is possible, in principle, to compute the values of measurable physical quantities, such as a proton’s mass. In practice, such a computation requires so much arithmetic that it could keep the fastest computers in the world busy for years. One way to do this calculation is to use a discrete four-dimensional lattice to model a section of space-time. Finding the solution involves adding up the contributions of all of the possible configurations of certain matrices on the links of the lattice, or at least some large representative sample. (This is essentially a Feynman path integral.) The thing that makes this so difficult is that calculating the contribution of even a single configuration involves multiplying the matrices around every little loop in the lattice, and the number of loops grows as the fourth power of the lattice size. Since all of these multiplications can take place concurrently, there is plenty of opportunity to keep all 64,000 processors busy.

To find out how well this would work in practice, Feynman had to write a computer program for QCD. Since the only computer language Richard was really familiar with was Basic, he made up a parallel version of Basic in which he wrote the program and then simulated it by hand to estimate how fast it would run on the Connection Machine.

He was excited by the results. “Hey Danny, you’re not going to believe this, but that machine of yours can actually do something [useful]!” According to Feynman’s calculations, the Connection Machine, even without any special hardware for floating point arithmetic, would outperform a machine that CalTech was building for doing QCD calculations. From that point on, Richard pushed us more and more toward looking at numerical applications of the machine.

By the end of that summer of 1983, Richard had completed his analysis of the behavior of the router, and much to our surprise and amusement, he presented his answer in the form of a set of partial differential equations. To a physicist this may seem natural, but to a computer designer, treating a set of boolean circuits as a continuous, differentiable system is a bit strange. Feynman’s router equations were in terms of variables representing continuous quantities such as “the average number of 1 bits in a message address.” I was much more accustomed to seeing analysis in terms of inductive proof and case analysis than taking the derivative of “the number of 1’s” with respect to time. Our discrete analysis said we needed seven buffers per chip; Feynman’s equations suggested that we only needed five. We decided to play it safe and ignore Feynman.

The decision to ignore Feynman’s analysis was made in September, but by next spring we were up against a wall. The chips that we had designed were slightly too big to manufacture and the only way to solve the problem was to cut the number of buffers per chip back to five. Since Feynman’s equations claimed we could do this safely, his unconventional methods of analysis started looking better and better to us. We decided to go ahead and make the chips with the smaller number of buffers.

Fortunately, he was right. When we put together the chips the machine worked. The first program run on the machine in April of 1985 was Conway’s game of Life.

Cellular Automata

The game of Life is an example of a class of computations that interested Feynman called [cellular automata]. Like many physicists who had spent their lives going to successively lower and lower levels of atomic detail, Feynman often wondered what was at the bottom. One possible answer was a cellular automaton. The notion is that the “continuum” might, at its lowest levels, be discrete in both space and time, and that the laws of physics might simply be a macro-consequence of the average behavior of tiny cells. Each cell could be a simple automaton that obeys a small set of rules and communicates only with its nearest neighbors, like the lattice calculation for QCD. If the universe in fact worked this way, then it presumably would have testable consequences, such as an upper limit on the density of information per cubic meter of space.

The notion of cellular automata goes back to von Neumann and Ulam, whom Feynman had known at Los Alamos. Richard’s recent interest in the subject was motivated by his friends Ed Fredkin and Stephen Wolfram, both of whom were fascinated by cellular automata models of physics. Feynman was always quick to point out to them that he considered their specific models “kooky,” but like the Connection Machine, he considered the subject sufficiently crazy to put some energy into.

There are many potential problems with cellular automata as a model of physical space and time; for example, finding a set of rules that obeys special relativity. One of the simplest problems is just making the physics so that things look the same in every direction. The most obvious pattern of cellular automata, such as a fixed three-dimensional grid, have preferred directions along the axes of the grid. Is it possible to implement even Newtonian physics on a fixed lattice of automata?

Feynman had a proposed solution to the anisotropy problem which he attempted (without success) to work out in detail. His notion was that the underlying automata, rather than being connected in a regular lattice like a grid or a pattern of hexagons, might be randomly connected. Waves propagating through this medium would, on the average, propagate at the same rate in every direction.

Cellular automata started getting attention at Thinking Machines when Stephen Wolfram, who was also spending time at the company, suggested that we should use such automata not as a model of physics, but as a practical method of simulating physical systems. Specifically, we could use one processor to simulate each cell and rules that were chosen to model something useful, like fluid dynamics. For two-dimensional problems there was a neat solution to the anisotropy problem since [Frisch, Hasslacher, Pomeau] had shown that a hexagonal lattice with a simple set of rules produced isotropic behavior at the macro scale. Wolfram used this method on the Connection Machine to produce a beautiful movie of a turbulent fluid flow in two dimensions. Watching the movie got all of us, especially Feynman, excited about physical simulation. We all started planning additions to the hardware, such as support of floating point arithmetic that would make it possible for us to perform and display a variety of simulations in real time.

Feynman the Explainer

In the meantime, we were having a lot of trouble explaining to people what we were doing with cellular automata. Eyes tended to glaze over when we started talking about state transition diagrams and finite state machines. Finally Feynman told us to explain it like this,

“We have noticed in nature that the behavior of a fluid depends very little on the nature of the individual particles in that fluid. For example, the flow of sand is very similar to the flow of water or the flow of a pile of ball bearings. We have therefore taken advantage of this fact to invent a type of imaginary particle that is especially simple for us to simulate. This particle is a perfect ball bearing that can move at a single speed in one of six directions. The flow of these particles on a large enough scale is very similar to the flow of natural fluids.”

This was a typical Richard Feynman explanation. On the one hand, it infuriated the experts who had worked on the problem because it neglected to even mention all of the clever problems that they had solved. On the other hand, it delighted the listeners since they could walk away from it with a real understanding of the phenomenon and how it was connected to physical reality.

We tried to take advantage of Richard’s talent for clarity by getting him to critique the technical presentations that we made in our product introductions. Before the commercial announcement of the Connection Machine CM-1 and all of our future products, Richard would give a sentence-by-sentence critique of the planned presentation. “Don’t say `reflected acoustic wave.’ Say [echo].” Or, “Forget all that `local minima’ stuff. Just say there’s a bubble caught in the crystal and you have to shake it out.” Nothing made him angrier than making something simple sound complicated.

Getting Richard to give advice like that was sometimes tricky. He pretended not to like working on any problem that was outside his claimed area of expertise. Often, at Thinking Machines when he was asked for advice he would gruffly refuse with “That’s not my department.” I could never figure out just what his department was, but it did not matter anyway, since he spent most of his time working on those “not-my-department” problems. Sometimes he really would give up, but more often than not he would come back a few days after his refusal and remark, “I’ve been thinking about what you asked the other day and it seems to me…” This worked best if you were careful not to expect it.

I do not mean to imply that Richard was hesitant to do the “dirty work.” In fact, he was always volunteering for it. Many a visitor at Thinking Machines was shocked to see that we had a Nobel Laureate soldering circuit boards or painting walls. But what Richard hated, or at least pretended to hate, was being asked to give advice. So why were people always asking him for it? Because even when Richard didn’t understand, he always seemed to understand better than the rest of us. And whatever he understood, he could make others understand as well. Richard made people feel like a child does, when a grown-up first treats him as an adult. He was never afraid of telling the truth, and however foolish your question was, he never made you feel like a fool.

The charming side of Richard helped people forgive him for his uncharming characteristics. For example, in many ways Richard was a sexist. Whenever it came time for his daily bowl of soup he would look around for the nearest “girl” and ask if she would fetch it to him. It did not matter if she was the cook, an engineer, or the president of the company. I once asked a female engineer who had just been a victim of this if it bothered her. “Yes, it really annoys me,” she said. “On the other hand, he is the only one who ever explained quantum mechanics to me as if I could understand it.” That was the essence of Richard’s charm.

A Kind Of Game

Richard worked at the company on and off for the next five years. Floating point hardware was eventually added to the machine, and as the machine and its successors went into commercial production, they were being used more and more for the kind of numerical simulation problems that Richard had pioneered with his QCD program. Richard’s interest shifted from the construction of the machine to its applications. As it turned out, building a big computer is a good excuse to talk to people who are working on some of the most exciting problems in science. We started working with physicists, astronomers, geologists, biologists, chemists — everyone of them trying to solve some problem that it had never been possible to solve before. Figuring out how to do these calculations on a parallel machine requires understanding of the details of the application, which was exactly the kind of thing that Richard loved to do.

For Richard, figuring out these problems was a kind of a game. He always started by asking very basic questions like, “What is the simplest example?” or “How can you tell if the answer is right?” He asked questions until he reduced the problem to some essential puzzle that he thought he would be able to solve. Then he would set to work, scribbling on a pad of paper and staring at the results. While he was in the middle of this kind of puzzle solving he was impossible to interrupt. “Don’t bug me. I’m busy,” he would say without even looking up. Eventually he would either decide the problem was too hard (in which case he lost interest), or he would find a solution (in which case he spent the next day or two explaining it to anyone who listened). In this way he worked on problems in database searches, geophysical modeling, protein folding, analyzing images, and reading insurance forms.

The last project that I worked on with Richard was in simulated evolution. I had written a program that simulated the evolution of populations of sexually reproducing creatures over hundreds of thousands of generations. The results were surprising in that the fitness of the population made progress in sudden leaps rather than by the expected steady improvement. The fossil record shows some evidence that real biological evolution might also exhibit such “punctuated equilibrium,” so Richard and I decided to look more closely at why it happened. He was feeling ill by that time, so I went out and spent the week with him in Pasadena, and we worked out a model of evolution of finite populations based on the Fokker Planck equations. When I got back to Boston I went to the library and discovered a book by Kimura on the subject, and much to my disappointment, all of our “discoveries” were covered in the first few pages. When I called back and told Richard what I had found, he was elated. “Hey, we got it right!” he said. “Not bad for amateurs.”

In retrospect I realize that in almost everything that we worked on together, we were both amateurs. In digital physics, neural networks, even parallel computing, we never really knew what we were doing. But the things that we studied were so new that no one else knew exactly what they were doing either. It was amateurs who made the progress.

Telling The Good Stuff You Know

Actually, I doubt that it was “progress” that most interested Richard. He was always searching for patterns, for connections, for a new way of looking at something, but I suspect his motivation was not so much to understand the world as it was to find new ideas to explain. The act of discovery was not complete for him until he had taught it to someone else.

I remember a conversation we had a year or so before his death, walking in the hills above Pasadena. We were exploring an unfamiliar trail and Richard, recovering from a major operation for the cancer, was walking more slowly than usual. He was telling a long and funny story about how he had been reading up on his disease and surprising his doctors by predicting their diagnosis and his chances of survival. I was hearing for the first time how far his cancer had progressed, so the jokes did not seem so funny. He must have noticed my mood, because he suddenly stopped the story and asked, “Hey, what’s the matter?”

I hesitated. “I’m sad because you’re going to die.”

“Yeah,” he sighed, “that bugs me sometimes too. But not so much as you think.” And after a few more steps, “When you get as old as I am, you start to realize that you’ve told most of the good stuff you know to other people anyway.”

We walked along in silence for a few minutes. Then we came to a place where another trail crossed and Richard stopped to look around at the surroundings. Suddenly a grin lit up his face. “Hey,” he said, all trace of sadness forgotten, “I bet I can show you a better way home.”

And so he did.

Edge Question 02017

Posted on Friday, January 20th, 02017 by Ahmed Kabil
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Spiders 2013 by Katinka Matson

It’s been an annual tradition since 01998: with a new year comes a new Edge question.

Every January, John Brockman presents the members of his online salon with a question that elicits discussion about some of the biggest intellectual and scientific issues of our time. Previous iterations have included prompts such as “What should we be worried about?” or  “What do you think about machines that think?” The essay responses – in excess of a hundred each year – offer a wealth of insight into the direction of today’s cultural forces, scientific innovations, and global trends.

This year, Brockman asks:

What scientific term or concept ought to be more widely known?

The extensive collection of answers includes contributions by several Long Now Board members, fellows, and past (and future!) SALT speakers:

George Dyson, who spoke at Long Now in 02013, says the Reynolds Number from fluid dynamics can be applied to non-traditional domains to understand why things might go smoothly for a while, and then all of a sudden don’t.

Long Now Board Member Stewart Brand says genetic rescue can help threatened wildlife populations by restoring genetic diversity.

Priyamvada Natarajan, who spoke at Long Now in 02016, describes how the bending of light, or gravitational lensing, is a consequence of Einstein’s re-conceptualization of gravity in his theory of relativity.

Samuel Arbesman, who spoke at the Interval in 02016, says “magical” self-replicating computer programs known as quines underscore the limits of mathematics and computer science while demonstrating that reproduction isn’t limited to the domain of the biological.

Michael Shermer, who spoke at Long Now in 02015, says the very human tendency to be “preternaturally pessimistic” has an evolutionary basis. Negativity bias, which can be observed across all domains of life, is a holdover from an evolutionary past where existence was more dangerous, so over-reacting to threats offered more of a pay-off than under-reacting.

Long Now Board Member Brian Eno sets his sights on confirmation bias after a particularly divisive election season playing out on social media revealed that more information does not necessarily equal better decisions.

George Church of Long Now’s Revive and Restore says that while DNA may be one of the most widely known scientific terms, far too few people understand the DNA in their own bodies. With DNA tests as low as $499, Church says there’s no reason not to get your DNA tested, especially when it could allow for preventative measures when it comes to genetic diseases.

Brian Christian, who spoke at Long Now in 02016, argues that human culture progresses via the retention of youthful traits into adulthood, a process known as neoteny.

Long Now Board Member Kevin Kelly argues that the best way to steer clear of failure is by letting go of success once it is achieved, thereby avoiding premature optimization.

Seth Lloyd, who spoke at Long Now in 02016, explains the accelerating spread of digital information using a centuries-old scientific concept from classical mechanics called the virial theorem.

Long Now Board Member Danny Hillis unpacks impedance matching, or adding elements to a system so that it accepts energy more efficiently. He predicts a future where impedance matching could help cool the earth by adding tiny particles of dust to our stratosphere that would reflect away the sun’s infrared waves.

Steven Pinker, who spoke at Long Now in 02012, argues that the meaning of life and human purpose lies in the second law of thermodynamics. Pinker believes our deeply-engrained habit of under-appreciating the universe’s tendency towards disorder is “a major source of human folly.”

Long Now Board Member Paul Saffo says that at the heart of today’s biggest challenges, from sustaining mega-cities to overpopulation to information overload, are hidden laws of scale described by Haldane’s Rule of the Right Size.

Martin Rees, who spoke at Long Now in 02010, says we may be living in a multiverse.

These are just a few of this year’s thought-provoking answers; you can read the full collection here.

50% Long Now Member Discount for REAL2016 Conference Event at Fort Mason Center

Posted on Tuesday, March 1st, 02016 by Andrew Warner
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Bay-Lights-REAL2016

On March 8th & 9th at Fort Mason Center, Autodesk will be hosting their annual conference event REAL2016, which focuses on new 3D technologies, including 3D modeling, 3D printing, laser scanning, augmented reality, and fabrication. Autodesk has generously offered Long Now Members a 50% discount for the event, please check your email for instructions on how to redeem this discount.

The programming over 2 days features talks, panels, demonstrations and a startup competition – all centered around capture, compute and create technologies and their increasing convergence.

Alexander Rose, Long Now’s Executive Director, will also be speaking on the Futures Panel with designer Syd Mead and others on Wednesday March 9 starting at 11:20am.

Do stop by and visit The Interval while you are at the event, we’ll be open from 10am to midnight offering thoughtful coffee and cocktails. Private events and ticketed lectures are noted on The Interval website and our Twitter.

We hope that many of you will be able to attend!