Monday, December 6, 2010

Synthetic biology and evolution : The New Yorker

A Life of Its Own
Where will synthetic biology lead us?
by Michael Specter September 28, 2009

Read more

Kevin Kelly on what technology wants | TEDxAmsterdam

God Is the Machine


By Kevin Kelly


50 Posts About Cyborgs

September 2010 was the 50th Anniversary of the coining of the term 'cyborg'. Over the course of the month, this site was updated 50 times with links to material — most of it new — celebrating 50 years of one of the 20th Century's more enduring concepts.

Sunday, October 17, 2010

If this is the current technology to make a robot resemble a human, I won't be terribly worried for a decade or so.

Robot dancing

Friday, September 24, 2010

Top 5 TED talks on transhumanism

TED (Technology, Entertainment, Design) brings together some of the world’s top thinkers at conferences around the world to deliver short presentations on “ideas worth spreading.” Not surprisingly, several speakers have delivered talks on topics of interest to transhumanists, such as life extension, artificial intelligence, nanotechnology, and more.

Find them here!

Suicide Note and Singularity

1,900 page suicide note talks an awful lot about the singularity.

Thursday, September 9, 2010

What Is Information? : 13.7: Cosmos And Culture : NPR

"We live in the midst of the “Information Age,” surrounded by computers, the web, Facebook, Twitter, electronic medical records, Skype. You would think we knew what information “is.”

The answer is surprisingly unclear.

What I want to do in this blog is present three views of information."


Wednesday, September 8, 2010

U of U Researchers Decode Words from Brain Signals

U. scientists decode words from brain signals
September 8th, 2010 @ 10:02pm
By Jed Boal

SALT LAKE CITY -- University of Utah researchers recently discovered a way to decode words from brain signals. In other words, the brain speaks.

This breakthrough study, published in this month's Journal of Neural Engineering, is an early step to enable severely paralyzed people to speak with their thoughts.

As we speak, our brains signal our mouths to make words. Bradley Greger, an assistant professor of bioengineering at the University of Utah, set out with his research team to decode spoken words using only brain signals.
A micro-electrocorticographic imaging device translated brain signals into words. It used two grids of microelectrodes implanted beneath the skull, without penetrating the brain.

"That's what we really need to know: what are the patterns of neurosignals that correlate with the spoken words?" Greger said.

A special micro-electrocorticographic (microECoG) imaging device translated brain signals into words. It used two grids of microelectrodes implanted beneath the skull, without penetrating the brain.

"Since it's such a small grid, we can place it precisely over the area of the brain that controls speech," Greger explained.

Words originate as patterns of electrical activity in the brain before they are ever spoken. The researchers tapped into that on a volunteer patient and discovered information processed on a microscale.

"There really is information at that scale, the microscale, from the surface of the brain," Greger said.

The scientists recorded brain signals as the patient repeatedly read 10 simple words, like "yes" and "no," "cold" and "hungry."

Examining the brain signals, the team picked the correct word 28 percent to 48 percent of the time.

That's better than chance, but not good enough for a device to translate a paralyzed person's thoughts into words spoken by a computer.

Essentially, what they validated is that there is information at that level, and speech can be extracted from it. So now they're moving on to the next generation and hope to come up with a device that the patient can use to communicate with words.

"What we need to do now is scale this device up a bit, not in terms of the size of the electrodes but the number of electrodes so we can cover a larger area of the brain and get more information out," Greger said.

If patients speak the words the same way each time, Greger says, they'll also get more accurate results.

Soon, the researchers hope to do a feasibility study on translating brain signals into computer-spoken words.

"That will give us, we hope and we think, the tool to really enable people to have restored communication," Greger said.

If accuracy improves, a communication device could quickly follow.


Friday, August 27, 2010

Ray Kurzweil -The Singularity Summit at Stanford

Three Major Singularity Schools

(Originally appeared on the Singularity Institute blog, September 2007.)

Singularity discussions seem to be splitting up into three major schools of thought: Accelerating Change, the Event Horizon, and the Intelligence Explosion.

  • Accelerating Change:
    • Core claim: Our intuitions about change are linear; we expect roughly as much change as has occurred in the past over our own lifetimes. But technological change feeds on itself, and therefore accelerates. Change today is faster than it was 500 years ago, which in turn is faster than it was 5000 years ago. Our recent past is not a reliable guide to how much change we should expect in the future.
    • Strong claim: Technological change follows smooth curves, typically exponential. Therefore we can predict with fair precision when new technologies will arrive, and when they will cross key thresholds, like the creation of Artificial Intelligence.
    • Advocates: Ray Kurzweil, Alvin Toffler(?), John Smart

  • Event Horizon:
    • Core claim: For the last hundred thousand years, humans have been the smartest intelligences on the planet. All our social and technological progress was produced by human brains. Shortly, technology will advance to the point of improving on human intelligence (brain-computer interfaces, Artificial Intelligence). This will create a future that is weirder by far than most science fiction, a difference-in-kind that goes beyond amazing shiny gadgets.
    • Strong claim: To know what a superhuman intelligence would do, you would have to be at least that smart yourself. To know where Deep Blue would play in a chess game, you must play at Deep Blue’s level. Thus the future after the creation of smarter-than-human intelligence is absolutely unpredictable.
    • Advocates: Vernor Vinge

  • Intelligence Explosion:
    • Core claim: Intelligence has always been the source of technology. If technology can significantly improve on human intelligence – create minds smarter than the smartest existing humans – then this closes the loop and creates a positive feedback cycle. What would humans with brain-computer interfaces do with their augmented intelligence? One good bet is that they’d design the next generation of brain-computer interfaces. Intelligence enhancement is a classic tipping point; the smarter you get, the more intelligence you can apply to making yourself even smarter.
    • Strong claim: This positive feedback cycle goes FOOM, like a chain of nuclear fissions gone critical – each intelligence improvement triggering an average of>1.000 further improvements of similar magnitude – though not necessarily on a smooth exponential pathway. Technological progress drops into the characteristic timescale of transistors (or super-transistors) rather than human neurons. The ascent rapidly surges upward and creates superintelligence (minds orders of magnitude more powerful than human) before it hits physical limits.
    • Advocates: I. J. Good, Eliezer Yudkowsky

The thing about these three logically distinct schools of Singularity thought is that, while all three core claims support each other, all three strong claims tend to contradict each other.

If you extrapolate our existing version of Moore’s Law past the point of smarter-than-human AI to make predictions about 2099, then you are contradicting both the strong version of the Event Horizon (which says you can’t make predictions because you’re trying to outguess a transhuman mind) and the strong version of the Intelligence Explosion (because progress will run faster once smarter-than-human minds and nanotechnology drop it into the speed phase of transistors).

I find it very annoying, therefore, when these three schools of thought are mashed up into Singularity paste. Clear thinking requires making distinctions.

But what is still more annoying is when someone reads a blog post about a newspaper article about the Singularity, comes away with none of the three interesting theses, and spontaneously reinvents the dreaded fourth meaning of the Singularity:

  • Apocalyptism: Hey, man, have you heard? There’s this bunch of, like, crazy nerds out there, who think that some kind of unspecified huge nerd thing is going to happen. What a bunch of wackos! It’s geek religion, man.

I’ve heard (many) other definitions of the Singularity attempted, but I usually find them to lack separate premises and conclusions. For example, the old Extropian FAQ used to define the “Singularity” as the Inflection Point, “the time when technological development will be at its fastest” and just before it starts slowing down. But what makes this an interesting point in history apart from its definition? What are the consequences of this assumption? To qualify as a school of thought or even a thesis, one needs an internal structure of argument, not just a definition.

If you’re wondering which of these is the original meaning of the term “Singularity”, it is the Event Horizon thesis of Vernor Vinge, who coined the word.

Thursday, August 26, 2010

Susan Blackmore in last Sunday's NYT: The Third Replicator

The Third Replicator

All around us information seems to be multiplying at an ever increasing pace. New books are published, new designs for toasters and i-gadgets appear, new music is composed or synthesized and, perhaps above all, new content is uploaded into cyberspace. This is rather strange. We know that matter and energy cannot increase but apparently information can.

It is perhaps rather obvious to attribute this to the evolutionary algorithm or Darwinian process, as I will do, but I wish to emphasize one part of this process — copying. The reason information can increase like this is that, if the necessary raw materials are available, copying creates more information. Of course it is not new information, but if the copies vary (which they will if only by virtue of copying errors), and if not all variants survive to be copied again (which is inevitable given limited resources), then we have the complete three-step process of natural selection (Dennett, 1995). From here novel designs and truly new information emerge. None of this can happen without copying.

I want to make three arguments here.

Imitation is not just some new minor ability. It changes everything. It enables a new kind of evolution.

The first is that humans are unique because they are so good at imitation. When our ancestors began to imitate they let loose a new evolutionary process based not on genes but on a second replicator, memes. Genes and memes then coevolved, transforming us into better and better meme machines.

The second is that one kind of copying can piggy-back on another: that is, one replicator (the information that is copied) can build on the products (vehicles or interactors) of another. This multilayered evolution has produced the amazing complexity of design we see all around us.

The third is that now, in the early 21st century, we are seeing the emergence of a third replicator. I call these temes (short for technological memes, though I have considered other names). They are digital information stored, copied, varied and selected by machines. We humans like to think we are the designers, creators and controllers of this newly emerging world but really we are stepping stones from one replicator to the next.

As I try to explain this I shall make some assertions and assumptions that some readers may find outrageous, but I am deliberately putting my case in its strongest form so that we can debate the issues people find most interesting or most troublesome.

Some may entirely reject the notion of replicators, and will therefore dismiss the whole enterprise. Others will accept that genes are replicators but reject the idea of memes. For example, Eva Jablonka and Marion J. Lamb ( 2005) refer to “the dreaded memes” while Peter J. Richerson and Robert Boyd (2005), who have contributed so much to the study of cultural evolution, assert that “cultural variants are not replicators.” They use the phrase “selfish memes” but still firmly reject memetics (Blackmore 2006). Similarly, in a previous “On The Human” post, William Benzon explains why he does not like the term “meme,” yet he needs some term to refer to the things that evolve and so he still uses it. As John S. Wilkins points out in response, there are several more classic objections: memes are not discrete (I would say some are not discrete), they do not form lineages (some do), memetic evolution appears to be Lamarckian (but only appears so), memes are not replicated but re-created or reproduced, or are not copied with sufficient fidelity (see discussions in Aunger 2000, Sterelny 2006, Wimsatt 2010). I have tackled all these, and more, elsewhere and concluded that the notion is still valid (Blackmore 1999, 2010a).

So I will press on, using the concept of memes as originally defined by Dawkins who invented the term; that is, memes are “that which is imitated” or whatever it is that is copied when people imitate each other. Memes include songs, stories, habits, skills, technologies, scientific theories, bogus medical treatments, financial systems, organizations — everything that makes up human culture. I can now, briefly, tell the story of how I think we arrived where we are today.

Both memes and genes are vast competing sets of information, all selfishly getting copied whenever and however they can.

First there were genes. Perhaps we should not call genes the first replicator because there may have been precursors worthy of that name and possibly RNA-like replicators before the evolution of DNA (Maynard Smith and Szathmary 1995). However, Dawkins (1976), who coined the term “replicator,” refers to genes this way and I shall do the same.

We should note here an important distinction for living things based on DNA, that the genes are the replicators while the animals and plants themselves are vehicles, interactors, or phenotypes: ephemeral creatures constructed with the aid of genetic information coded in tiny strands of DNA packaged safely inside them. Whether single-celled bacteria, great oak trees, or dogs and cats, in the gene-centered view of evolution they are all gene machines or Dawkins’s “lumbering robots.” The important point here is that the genetic information is faithfully copied down the generations, while the vehicles or interactors live and die without actually being copied. Put another way, this system copies the instructions for making a product rather than the product itself, a process that has many advantages (Blackmore 1999, 2001). This interesting distinction becomes important when we move on to higher replicators.

So what happened next? Earth might have remained a one-replicator planet but it did not. One of these gene machines, a social and bipedal ape, began to imitate. We do not know why, although shifting climate may have favored stealing skills from others rather than learning them anew (Richerson and Boyd 2005). Whatever the reason, our ancestors began to copy sounds, skills and habits from one to another. They passed on lighting fires, making stone tools, wearing clothes, decorating their bodies and all sorts of skills to do with living together as hunters and gatherers. The critical point here is, of course, that they copied these sounds, skills and habits, and this, I suggest, is what makes humans unique. No other species (as far as we know) can do this. Song birds can copy some sounds, some of the other great apes can imitate some actions, and most notably whales and dolphins can imitate, but none is capable of the widespread, generalized imitation that comes so easily to us. Imitation is not just some new minor ability. It changes everything. It enables a new kind of evolution.

This is why I have called humans “Earth’s Pandoran species.” They let loose this second replicator and began the process of memetic evolution in which memes competed to be selected by humans to be copied again. The successful memes then influenced human genes by gene-meme co-evolution (Blackmore 1999, 2001). Note that I see this process as somewhat different from gene-culture co-evolution, partly because most theorists treat culture as an adaptation (e.g. Richerson and Boyd 2005), and agree with Wilson that genes “keep culture on a leash.” (Lumsden and Wilson 1981 p 13).

Benzon, in responding to Peter Railton’s post here at The Stone, points out the limits of this metaphor and proposes the “chess board and game” instead. I prefer a simple host-parasite analogy. Once our ancestors could imitate they created lots of memes that competed to use their brains for their own propagation. This drove these hominids to become better meme machines and to carry the (potentially huge and even dangerous) burden of larger brain size and energy use, eventually becoming symbiotic. Neither memes nor genes are a dog or a dog-owner. Neither is on a leash. They are both vast competing sets of information, all selfishly getting copied whenever and however they can.

To help understand the next step we can think of this process as follows: one replicator (genes) built vehicles (plants and animals) for its own propagation. One of these then discovered a new way of copying and diverted much of its resources to doing this instead, creating a new replicator (memes) which then led to new replicating machinery (big-brained humans). Now we can ask whether the same thing could happen again and — aha — we can see that it can, and is.

As “temes” proliferate, using ever more energy and resources, our own role becomes ever less significant.

A sticking point concerns the equivalent of the meme-phenotype or vehicle. This has plagued memetics ever since its beginning: some arguing that memes must be inside human heads while words, technologies and all the rest are their phenotypes, or “phemotypes”; others arguing the opposite. I disagree with both (Blackmore 1999, 2001). By definition, whatever is copied is the meme and I suggest that, until very recently, there was no meme-phemotype distinction because memes were so new and so poorly replicated that they had not yet constructed stable vehicles. Now they have.

Think about songs, recipes, ways of building houses or clothes fashions. These can be copied and stored by voice, by gesture, in brains, or on paper with no clear replicator/vehicle distinction. But now consider a car factory or a printing press. Thousands of near-identical copies of cars, books, or newspapers are churned out. Those actual cars or books are not copied again but they compete for our attention and if they prove popular then more copies are made from the same template. This is much more like a replicator-vehicle system. It is “copy the instructions” not “copy the product.”

Of course cars and books are passive lumps of metal, paper and ink. They cannot copy, let alone vary and select information themselves. So could any of our modern meme products take the step our hominid ancestors did long ago and begin a new kind of copying? Yes. They could and they are. Our computers, all linked up through the Internet, are beginning to carry out all three of the critical processes required for a new evolutionary process to take off.

Computers handle vast quantities of information with extraordinarily high-fidelity copying and storage. Most variation and selection is still done by human beings, with their biologically evolved desires for stimulation, amusement, communication, sex and food. But this is changing. Already there are examples of computer programs recombining old texts to create new essays or poems, translating texts to create new versions, and selecting between vast quantities of text, images and data. Above all there are search engines. Each request to Google, Alta Vista or Yahoo! elicits a new set of pages — a new combination of items selected by that search engine according to its own clever algorithms and depending on myriad previous searches and link structures.

This is a radically new kind of copying, varying and selecting, and means that a new evolutionary process is starting up. This copying is quite different from the way cells copy strands of DNA or humans copy memes. The information itself is also different, consisting of highly stable digital information stored and processed by machines rather than living cells. This, I submit, signals the emergence of temes and teme machines, the third replicator.
More From The Stone

Read previous contributions to this series.

* Go to All Posts »

What should we expect of this dramatic step? It might make as much difference as the advent of human imitation did. Just as human meme machines spread over the planet, using up its resources and altering its ecosystems to suit their own needs, so the new teme machines will do the same, only faster. Indeed we might see our current ecological troubles not as primarily our fault, but as the inevitable consequence of earth’s transition to being a three-replicator planet. We willingly provide ever more energy to power the Internet, and there is enormous scope for teme machines to grow, evolve and create ever more extraordinary digital worlds, some aided by humans and others independent of them. We are still needed, not least to run the power stations, but as the temes proliferate, using ever more energy and resources, our own role becomes ever less significant, even though we set the whole new evolutionary process in motion in the first place.

Whether you consider this a tragedy for the planet or a marvelous, beautiful story of creation, is up to you.

(Susan Blackmore’s essay is the subject of this week’s forum discussion among the humanists and scientists at On the Human, a project of the National Humanities Center.)
Susan Blackmore

Susan Blackmore is a psychologist and writer researching consciousness, memes, and anomalous experiences, and a Visiting Professor at the University of Plymouth. She is the author of several books, including “The Meme Machine” (1999), “Conversations on Consciousness” (2005) and Ten Zen Questions (2009).


Aunger, R.A. (Ed) (2000) “Darwinizing Culture: The Status of Memetics as a Science,” Oxford University Press

Benzon, W.L. (2010) “Cultural Evolution: A Vehicle for Cooperative Interaction Between the Sciences and the Humanities.” Post for On the Human.

Blackmore, S. 1999 “The Meme Machine,” Oxford and New York, Oxford University Press

Blackmore,S. 2001 “Evolution and memes: The human brain as a selective imitation device.” Cybernetics and Systems, 32, 225-255

Blackmore, S. (2006) “Memetics by another name?” Review of “Not by Genes Alone” by P.J. Richerson and R. Boyd. Bioscience, 56, 74-5

Blackmore, S. (2010a) Memetics does provide a useful way of understanding cultural evolution. In “Contemporary Debates in Philosophy of Biology”, Ed. Francisco Ayala and Robert Arp, Chichester, Wiley-Blackwell, 255-72.

Blackmore (2010b) “Dangerous Memes; or what the Pandorans let loose.” In “Cosmos and Culture: Cultural Evolution in a Cosmic Context,” Ed. Steven Dick and Mark Lupisella, NASA 297-318

Dawkins,R. (1976) “The Selfish Gene,” Oxford, Oxford University Press (new edition with additional material, 1989)

Dennett, D. (1995) “Darwin’s Dangerous Idea,” London, Penguin

Jablonka, E. and Lamb, M.J. (2005) “Evolution in Four Dimensions: Genetic, Epigenetic, Behavioral and Symbolic Variation in the History of Life.” Bradford Books

Lumsden,C.J. and Wilson,E.O. (1981) “Genes, Mind and Culture.” Cambridge, Mass., Harvard University Press.

Maynard-Smith,J. and Szathm√°ry,E (1995) “The Major Transitions in Evolution.” Oxford, Freeman

Richerson, P.J. and Boyd, R. (2005) “Not by Genes Alone: How Culture Transformed Human Evolution,” Chicago, University of Chicago Press

Sterelny, K. (2006). “Memes Revisited.” British Journal for the Philosophy of Science 57 (1)

Wimsatt, W. (2010) Memetics does not provide a useful way of understanding cultural evolution: A developmental perspective. In “Contemporary Debates in Philosophy of Biology” Ed. Francisco Ayala and Robert Arp, Chichester, Wiley-Blackwell, 255-72.


Wednesday, August 25, 2010

Two TED talks by Ray Kurzweil

On How Technology Will Transform Us

Singularity University

This Blog

This blog will function as a conduit between students in Dr. Hanewicz's Singularity course at UVU (hence the name, SINGU[VU]LARITY). This blog, for now, will be public - and will remain as such for as long as posts and comments continue to be insightful - with a few of the students in the class posting thoughts, images, videos, theories, summaries of readings/class/discussions/etc... and anybody can comment on such posts.

As part of the learning experience, I hope to also organize a weekly coffee night for the Singularity course, and also a set of paper presentation/workshop sessions later in the semester. If you are interested in attending and participating in any of these three things (blog, coffee/discussion sessions, paper presentation/workshop sessions) please let me know.

Please post and comment as much as you like, there's never a shortage of information out there.