Accelerating Future

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Robin Hanson has a very provocative post up, “Galaxy Calc Shows Aliens”:

What makes a planet a good host for life? That is, what does a planet need for life to originate there and then evolve to something at the human level? Astronomers today say a planet at least needs a star that 1) lasts long enough, 2) has enough heavy elements, and 3) is not too often hit by nearby supernovae or gamma ray bursts. Using such criteria, several astronomers (mentioned below) have tried to calculate “galactic habitable zones,” i.e., galactic distributions of good-for-life planets, in both space and time. Such calculations are far more important than I had realized – they can help say how common are aliens! Let me explain.

Like many of Robin’s arguments, this one can take a bit of time to understand. Don’t come to any conclusions until you’ve read the entire post and thought about it for a few minutes.

I can say that this argument has caused me to update substantially in the direction that there may actually be aliens in this galaxy. For over a decade I’ve thought this possibility was extremely unlikely. Now I’m not so sure.

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I am fascinated by the possibility of using fullerenes to build eternal structures. If not eternal, extremely long-lasting. Fullerenes already exist today. See?

Above are aggregated diamond nanorods (ADNRs). The name “hyperdiamond” recently appeared to describe this material.

ADNRs, a type of fullerene (any molecule made entirely out of carbon), is the hardest and least compressible known material. Its bulk modulus, meaning resistance to compression, is 491 gigapascals (GPa), beating diamond which is only about 445 GPa. For comparison, the bulk modulus of steel is 160 GPa, glass is 30 GPa, and bone is just 15 GPa.

What else? This black stuff:

Look how dark it is. Something made out of that would be hard to see at night. Also, its melting point would be several thousand degrees.

The image above shows one of the longest nanotube forests ever created. The nanotubes are about 8 mm long.

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Here it is. Congrats to Nikola for getting the interview. I was fortunate enough to have a one-on-one conversation with Stephen Wolfram at Singularity Summit 2009 and I found him extremely clever.

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This is a very interesting, accessible-to-laypeople talk about a new technology (injected ice slurry) for avoiding cell death after trauma.

Sean McCabe’s introduction is also very funny in this one. Sean, who was MC at SS09 and SS10, has been brought on board SIAI to help us organize and run our annual Summit. This is good for me because it means we get to share work.

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I posted this only a month ago, but here’s the link to the video again. People sometimes say there’s been no progress in AI, but the kind of results obtained by Tenenbaum are amazing and open up a whole approach to AI that uses fast and frugal heuristics for reasoning and requires very minimal inspiration from the human brain.

Abstract:

In everyday learning and reasoning, people routinely draw successful generalizations from very limited evidence. Even young children can infer the meanings of words, hidden properties of objects, or the existence of causal relations from just one or a few relevant observations — far outstripping the capabilities of conventional learning machines. How do they do it? And how can we bring machines closer to these human-like learning abilities? I will argue that people’s everyday inductive leaps can be understood as approximations to Bayesian computations operating over structured representations of the world, what cognitive scientists have called “intuitive theories” or “schemas”. For each of several everyday learning tasks, I will consider how appropriate knowledge representations are structured and used, and how these representations could themselves be learned via Bayesian methods. The key challenge is to balance the need for strongly constrained inductive biases — critical for generalization from very few examples — with the flexibility to learn about the structure of new domains, to learn new inductive biases suitable for environments which we could not have been pre-programmed to perform in. The models I discuss will connect to several directions in contemporary machine learning, such as semi-supervised learning, structure learning in graphical models, hierarchical Bayesian modeling, and nonparametric Bayes.

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Ramez Naam: The Digital Biome from Singularity Institute on Vimeo.

Abstract:

Exponential technologies offer the promise not only of changing the human condition, but of radically altering the face of the planet on which we dwell. Within the next 20 years we will have sequenced the genome of every known species on the earth and tremendously advanced our understanding of how to utilize those genes and reprogram those organisms to alter the biosphere. Biosphere engineering will play a major role in overcoming current environmental and resource challenges, including finite reserves of fossil fuels and looming changes to the earth’s climate. That is just the beginning. An understanding of the complete biome genome will bring tremendous agility in combating future infectious disease outbreaks, in creating new sensors and manufacturing capabilities, and in revolutionizing food. Biosphere engineering and its underlying technologies will allow us to dramatically raise the population carrying capacity of the planet to tens of billions of individuals at least. With effective technology to sculpt the planetary biome, the limits of the number of humans that can live on the planet, and the quality of life of each, at tremendously higher than they appear to be today. This talk will explore some of the lower bounds of what’s possible with control of the biome.

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Michael Vassar at Singularity Summit 2010 — The Darwinian Method from Singularity Institute on Vimeo.

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Here’s the link. Abstract:

In everyday learning and reasoning, people routinely draw successful generalizations from very limited evidence. Even young children can infer the meanings of words, hidden properties of objects, or the existence of causal relations from just one or a few relevant observations — far outstripping the capabilities of conventional learning machines. How do they do it? And how can we bring machines closer to these human-like learning abilities? I will argue that people’s everyday inductive leaps can be understood as approximations to Bayesian computations operating over structured representations of the world, what cognitive scientists have called “intuitive theories” or “schemas”. For each of several everyday learning tasks, I will consider how appropriate knowledge representations are structured and used, and how these representations could themselves be learned via Bayesian methods. The key challenge is to balance the need for strongly constrained inductive biases — critical for generalization from very few examples — with the flexibility to learn about the structure of new domains, to learn new inductive biases suitable for environments which we could not have been pre-programmed to perform in. The models I discuss will connect to several directions in contemporary machine learning, such as semi-supervised learning, structure learning in graphical models, hierarchical Bayesian modeling, and nonparametric Bayes.

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2008 report from US National Academies of Sciences’ Space Studies Board:

Severe Space Weather Events — Understanding Societal and Economic Impacts: A Workshop Report

NASA Science News, June 4, 2010, “As the Sun Awakens, NASA Keeps a Wary Eye on Space Weather”

Richard Fisher, head of NASA’s Heliophysics Division, explains what it’s all about:

“The sun is waking up from a deep slumber, and in the next few years we expect to see much higher levels of solar activity. At the same time, our technological society has developed an unprecedented sensitivity to solar storms. The intersection of these two issues is what we’re getting together to discuss.”

The National Academy of Sciences framed the problem two years ago in a landmark report entitled “Severe Space Weather Events—Societal and Economic Impacts.” It noted how people of the 21st-century rely on high-tech systems for the basics of daily life. Smart power grids, GPS navigation, air travel, financial services and emergency radio communications can all be knocked out by intense solar activity. A century-class solar storm, the Academy warned, could cause twenty times more economic damage than Hurricane Katrina.

(Hurricane Katrina caused $81 billion in damage, so 20 times that would be $1.6 trillion in damage.)

Media articles

It is difficult to come to any conclusion because the experts disagree.

Discovery: Is a Devastating Solar Flare Coming to a City Near You? — pessimistic analysis from an astrophysicist:

In the case of space weather, wouldn’t it be great if, as a civilization, we could look at the sun and get advanced notice of a solar eruption? All we’d need is a few hours lead-time and we could reduce the output of national power grids (to avoid overload) and switch our satellites into “safe mode.” Once the storm has passed, we’d continue our lives as normal. Disaster averted.

Unfortunately, it often takes a disaster to teach us to prepare better in the future. I just hope the next solar maximum doesn’t teach us a lesson we can’t recover from.

A lot of drama and ink spilled in this post, but ultimately this astrophysicist sounds just as uncertain and confused as your average dude.

Counterpoint to the above: Expert rubbishes solar storm claims:

One report quotes an Australian astronomer as saying “the storm is likely to come sooner rather than later”.

But Dr Phil Wilkinson, the assistant director of the Bureau of Meteorology’s Ionospheric Prediction Service, says claims that this coming solar maximum will be the most violent in 100 years are not factual.

“All this talk about gloom and doom has selling power, but I’m certain it’s overstated,” he said.

“[It's] going far beyond what’s realistic and could be worrying or concerning for people who don’t really understand the underlying science behind it all.

“The real message should be that the coming solar maximum period could be equally as hazardous as any other solar maximum.”

Unfortunately, there’s not a whole lot of explanation as to why this expert believes there isn’t a major risk, or what exactly he means by “regional”.

Space Weather Enterprise Forum has been meeting for four years to discuss the solar maximum risk.

The Register: NASA: Civilization will end in 2013 (possibly)

Searching for “solar maximum”, “power grid” on Google Scholar reveals 13 results. Either this means I’m using the wrong search terms, there’s only a minority of scientists qualified to write on this topic and barely any do, or something else disappointing given the scale of the risk. Here’s one article from Science:

Are We Ready for the Next Solar Maximum? No Way, Say Scientists
Richard A. Kerr

If the once-in-500-years “solar superstorm” that crippled telegraph systems for a day or two across the United States and Europe in 1859 but otherwise was mainly remembered for its dramatic light show were to happen today, the charged-particle radiation and electromagnetic fury would fry satellites, degrade GPS navigation, disrupt radio communications, and trigger continent-wide blackouts lasting weeks or longer. Even a storm of the century would wreak havoc. That’s why space physicists are so anxious to forecast space weather storms accurately. If predicting a hurricane a few days ahead can help people prepare for a terrestrial storm’s onslaught, they reason, predicting solar storms should help operators of susceptible systems prepare for an electromagnetic storm. And space weather forecasters’ next challenge is coming up soon. The next peak in the 11-year sunspot cycle of solar activity looms in 2012 or 2013. A space weather symposium last month asked, “Are we ready for Solar Max?” The unanimous answer from participants was “No.”

So far, the balance of scientific opinion seems to be on the side of very serious concern.

My response to the above abstract is mostly — in this context, who cares about fried satellites, degraded GPS navigation, and disrupted radio communications in comparison to week-long blackouts? Translated into risks affecting personal health, in my mind that line would read something like this: “the risk could cause a broken toenail, difficulty hearing, an itchy back, and cancer”.

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