Post-Interesting

Is Google Pursuing AGI?

2006-01-14T14:16:00.000-08:00

See...

http://www.economist.com/business/displaystory.cfm?story_id=5382048

where it says

"But some people think they detect an even more grandiose design. Google is already working on a massive and global computing grid. Eventually, says Mr Saffo, .they're trying to build the machine that will pass the Turing test..in other words, an artificial intelligence that can pass as a human in written conversations. Wisely or not, Google wants to be a new sort of deus ex machina."

Peter Norvig (one of Google's AI leaders) shed some light onto this at his talk at the ACC05 conference last September.

What he alluded to there was a goal, in 5+ years from now, of having a system that can answer any natural language query whose answer exists somewhere on the Internet.

E.g. if asked "Who was the first President of the US" it would answer "George Washington" because somewhere there is a web page with a sentence such as "George Washington, the first President of the United States, blah blah."

This would be Step 1. He didn't talk about it, but it's obvious Step 2 would be something that could answer questions whose answers are not contained on any single Web page.

To see how far off we are from this Step 2 now, peruse the results of the Pascal Challenge on "Recognizing Textual Entailment", from last year:

http://www.pascal-network.org/Challenges/RTE/

Anyway, I suspect what Norvig described reflects Google's intentions; and IMO is not exactly a direct approach at AGI in the sense that it has no focus on self-understanding, creativity, and so forth. However, I can see how proceeding in this direction could in time create a system that could (with appropriate expenditure of additional effort) be turned into an AGI.

-- Ben Goertzel

How Infant Language Processing Builds on Physical Inference

2005-12-26T04:18:00.000-08:00

It's a rare occurence, but I have just read an AI research paper which is of nontrivial interest...

N. L. Cassimatis (2004). Grammatical Processing Using the Mechanisms of Physical Inferences. In Proceedings of the Twentieth-Sixth Annual Conference of the Cognitive Science Society.

available at

http://www.cassimatis.com/polyscheme.html

As the author describes it,

"
A model of syntactic parsing model based almost entirely on the mechanisms in the physical reasoning model, making the case for the cognitive substrate principle.
"

The author Nick Cassimatis, who is specifically oriented toward creating human-level intelligence, has

articulated an explanation of infant-level physical learning in terms of his logic-based AI framework, PolyScheme (in which multiple reasoning algorithms interact using a common predicate-logic language)
then shown how the same mechanisms and representations used for infant physical learning can be used for language learning

I first became aware of Nick's PolyScheme approach to AGI when we both presented at the AAAI workshop on Achieving Human-Level Intelligence Through Integrated Systems and Research, in late 2004.

I think PolyScheme is a sensible approach at heart, though as currently articulated it seems to me a long way from constituting a fully-developed architecture for AGI.

-- Ben

Genetics of Aging in Humans and Flies

2005-12-24T04:14:00.000-08:00

In spite of the lack of focus placed on the subject by the "research funding powers that be", insights into the genetics of aging keep rolling out, month by month and year by year.

Some recent research discusses specific alleles that seem correlated with survival to age 90:

http://www.abc.net.au/news/newsitems/200512/s1537519.htm

http://www.eurekalert.org/pub_releases/2005-12/g-nre121205.php

In a similar vein I just read biologist Michael Rose's very excellent book The Long Tomorrow

http://www.us.oup.com/us/catalog/general/subject/LifeSciences/EvolutionaryBiology/?view=usa&ci=0195179390

which recounts his work studying aging in flies. One of his more striking results is that after a certain age is reached, the mortality rate in flies stops increasing and stays constant. (The book is easy to read by anyone who understands high school biology, yet presents and describes important research without significant dumbing-down. It also does a pretty good job of getting across the flavor of modern experimental biology research ... and of emphasizing the point that a lot more progress toward curing aging could be made if society chose to devote resources toward this goal. Many very good scientists, such as Rose himself and Aubrey de Grey and many others, have promising ideas regarding how to better understand and potentially alleviate the aging process, but our society is more interested in spending money blowing people up and inventing new forms of fabric softener. Bummer, huh.)

Also, in reviewing the work of some other researchers, Rose notes that there seem to be 300-400 genes that behave differentially in old versus young flies. He disputes the ideas of some other researchers who claim that there may just be 1 or 2 genes serving as master control genes for the aging process. I tend to agree with him, yet, I wonder if a careful analysis of gene expression data from old and young flies might indicate that a few dozen of these 300-400 genes are more "central" and in a sense drive the behavior of the other differentially-behaving genes. This is something I'd be interested to work on myself if I could find some good data freely available. To oversimplify slightly, it's something that could be addressed by simply plugging some relevant microarray data into our Biomind software.

The data used in this paper

http://www.pubmedcentral.gov/articlerender.fcgi?artid=419663

would seem to be adequate for this kind of study, but, I have not found the raw data available online. I'm going to see if this research group is interested in collaboration.

On the theme of foolish allocation of resources, my contacts at the Center for Disease Control suggest to me that the budget cuts hinted at in

http://www.usmedicine.com/article.cfm?articleID=1046&issueID=72

are likely actually going to happen. Bush seems to be cutting the CDC's budget by 7% or so (to fund his war in Iraq and his differential tax cuts for the wealthy, I suppose). Of course, this doesn't directly affect aging research because in its immense foolishness the government does not consider aging a disease. But it affects aging research indirectly because there are commonalities between aging and other diseases. Fortunately, real scientific progress continues in spite of this sort of idiocy.

Robot Recognizes Its Own Mirror Image

2005-12-22T07:19:00.000-08:00

Though substantially overhyped in this article

"
Robot Demonstrates Self Awareness
By Tracy Staedter, Discovery News
"

http://dsc.discovery.com/news/briefs/20051219/awarerobot_tec.html?source=rss

this robot that recognizes its own mirror image and in this sense can distinguish "self from other" is still an interesting achievement, since it was done via adaptive hierarchical neural nets rather than any kind of total "cheating" methodology.

Still, my bet is that the way this little bot achieves self-recognition bears fairly little resemblance to how humans, apes or dolphins do it (these are the only species that seem to be able to consistently carry out this cognitive feat:

http://www.sciam.com/article.cfm?articleID=0002433B-A643-1C5E-B882809EC588ED9F

)

Perhaps this line of research will lead to a branch of cognitive robotics focused on "distributed cognition"

(cf.
http://www-sv.cict.fr/cotcos/pjs/TheoreticalApproaches/DistributedCog/DistributedCogIntro.htm
)

This is the sort of thing my colleagues and I will experiment with using our Novamente AI system in the AGISIM simulation world, as the NM/AGISIM connection matures. (But AGISIM doesn't support mirrors yet!)

-- Ben Goertzel

Metaptation

2005-12-15T17:45:00.000-08:00

I recently read a well-thought-out and elegantly written (though rather dense) article, Metaptation: The Product of Selection at the Second Tier, by David King. The concept is not a particularly new one; King riffs on the evolution of evolvability, learning how to learn, and Hofstadter's metaphor of knob-twiddling vs. knob-creation. The article is worth reading for King's eloquence and careful reasoning even if you're already familiar with all of the material (I'd estimate about 2/3rds familiarity myself).

Briefly, metaptations are adaptations which are selected for in an evolutionary system not because of their direct effects on fitness, but because they tend to lead to the appearance of meaningful adaptations. An example would be a reorganization of an organism's genome that had no effect on it's phenotype, but made deleterious mutations less common and/or "helpful" mutations more common (e.g., varying the size of an entire organism is more likely to succeed than varying the size of an individual organ). This kind of second-tier organization is particular dear to me because it forms the intellectual grounding for my current research efforts, designing evolutionary-probabilistic learning algorithms that incorporate explicit metaptive mechanisms for on-the-fly creation of meaningful varaibles (i.e., Hofstadterian knobs).

Note that this is a kind of group-level selection effect (which I am generally leery of), but carefully reasoned and circumscribed. The selfish gene paradigm is not negated but extended to recognize a hierarchy of selective levels. I could go on, but if you're still interested at this point, just go read the article :).

Cancer Genome Atlas project launched

2005-12-15T08:14:00.000-08:00

Biology, one of the best-funded branches of science these days, marches rapidly ahead....

According to the Washington Post,

http://www.washingtonpost.com/wp-dyn/content/article/2005/12/13/AR2005121301667.html

"
Federal health officials yesterday launched the biggest genetic research endeavor since the landmark human genome project: an ambitious effort to categorize all of the hundreds of molecular glitches that turn normal healthy cells into cancers.The Cancer Genome Atlas, whose total cost could reach $1 billion or more, will for the first time direct the full force of today's sophisticated genetic technologies to the thorough understanding of a single disease -- one that will eventually strike nearly half of all Americans alive.
"

Semi-relatedly, I had a meeting at the National Cancer Institute recently where I discussed with some researchers the need to use advanced pattern-recognition technology to find combinations of genes and proteins that contribute to cancer (rather than just studying the effects of individual genes in isolation, which is the default paradigm now). They understood the need, but I got the impression that their progress toward actually adopting a "radical" approach like this will be fairly slow.

However, if the NCI is going to put big bucks into trying to obtain a "complete" understanding of cancer, then they are going to run up against this problem pretty quickly.

At some point in the not too distant future of biology, genomics is going to meet systems biology -- i.e., enabled by sophisticated informatics, it will supply sufficient data to make simulation models of the interactions inside cells and organisms. At this point we will see really fast progress toward a fuller understanding of biological systems. Perhaps the study of cancer (since it's so popular with funding sources) will be the domain in which this transition occurs....

At dinner with a group of biologists in Melbourne earlier this year, I asked how long they thought it would be till human biology was basically finished (in the sense that we pretty much fully understand the human organism in its original unaugmented condition). No one wanted to venture a guess, but when I speculated "50 years", a couple folks were brave enough to agree with me... (I didn't get into the Singularity; it wasn't that kind of crowd ;-)

-- Ben Goertzel

The management of uncertainty in the human brain: new experimental insights

2005-12-13T19:11:00.000-08:00

When someone talks to me about using neuroscience to inspire AI theory, I always complain that we simply don't understand the brain well enough for this to be feasible yet.

I definitely stand by this statement -- but, I'm always excited when some neuroscience results come out that seem to have some connection with ideas I've encountered in my AI work.

Along these lines: Some recent neuroscience results, pointed out to me by Pei Wang, appear to qualitatively validate the approach taken in my Novamente AI system and Pei's NARS AI system (and some other AI approaches such as Walley's imprecise probability theory), in which numbers measuring frequency are augmented by additional numbers measuring the uncertainty in these frequency measures.

In other words, some of us maverick AI theorists have been saying for a while that using just ONE number (typically probability) to measure uncertainty is not enough. Two numbers -- e.g. a probability and another number measuring the "weight of evidence" in favor of this probability (or to put it differently, the "confidence" one has in the probability) -- are needed to make a cognitively meaningful algebra of uncertainty.

Well, this paper suggests that the brain also reckons in terms of uncertainties-of-probabilities as well as probabilities themselves:

Neural Systems Responding to Degrees of Uncertainty in Human Decision-Making
Ming Hsu, Meghana Bhatt, Ralph Adolphs, Daniel Tranel, and Colin F. Camerer, Science 9 December 2005: 1680-1683

Much is known about how people make decisions under varying levels of probability (risk). Less is known about the neural basis of decision-making when probabilities are uncertain because of missing information (ambiguity). In decision theory, ambiguity about probabilities should not affect choices. Using functional brain imaging, we show that the level of ambiguity in choices correlates positively with activation in the amygdala and orbitofrontal cortex, and negatively with a striatal system. Moreover, striatal activity correlates positively with expected reward. Neurological subjects with orbitofrontal lesions were insensitive to the level of ambiguity and risk in behavioral choices. These data suggest a general neural circuit responding to degrees of uncertainty, contrary to decision theory.

Of course, these results contradict aspects of traditional statistical decision theory, but they don't contradict mathematical probability theory in general -- just some particular, conventional ways of using it to study decisions. The way probability theory is used in Novamente, and the way it's used by imprecise-probabilities-theorists like Peter Walley, is actually somewhat validated by these findings.

The article can be obtained (for money) at

http://www.sciencemag.org/cgi/content/abstract/310/5754/1680

and some related journalistic discussion is at

http://groups.yahoo.com/group/envecolnews/message/2651

-- Ben Goertzel

Transvision 2006: Helsinki, Finland ... August

2005-12-13T08:40:00.000-08:00

Another interesting conference coming up: Transvision 2006, the conference of the World Transhumanist Association, will be held in Helsinki Finland this August.

This looks to be a really interesting one!

http://transhumanismi.org/tv06/

The conference organizer, Ari Heljakka, is a collaborator on the Novamente AGI project and the leader of the Finnish Transhumanist Association, and I know he is making a big effort to get a wide variety of interesting speakers with deep knowledge of, and a high level of current activity in, their subject areas.

If you're a researcher in a Singularity-relevant area of science or technology, please consider coming to Helsinki to give a presentation on your work. The call for papers is here:

http://transhumanismi.org/tv06/call

Conference Session on Human-Level AI, Vancouver, July 2006

2005-12-13T08:30:00.000-08:00

It is interesting to see that the academic AI community is finally, slowly, waking up to the notion that artificial general intelligence is valuable and viable and worth thinking seriously about.

For instance, in Vancouver in 2006, at this conference

http://www.wcci2006.org/

there will be a panel session called “A Roadmap to Human-Level Intelligence” at which I among other AGI-oriented AI researchers will be presenting.

To quote the conference website:

Panelists

James Anderson (Brown University)
Nick Cassimatis (Human Level Intelligence Laboratory)
Andrew Coward (Australian National University)
Richard Duro (Universidade da Coruna)
David Fogel (Natural Selection Inc.)
Walter Freeman (University of California)
Ben Goertzel (Artificial General Intelligence Research Institute)
Robert Hecht-Nielsen (University of California)
Soo Young Lee (Korea Advanced Institute of Science and Technology)
John Pollock (University of Arizona)
John Taylor (King's College London)

Summary

Building intelligent systems with the human level of competence is the ultimate grand challenge for science and technology in general, and the computational intelligence community in particular. How are we going to achieve it? Several exciting projects aimed at reaching human-level intelligence have been formulated recently. Some of these projects start from low-level neuromorphic brain simulations, some focus on mesoscopic brain simulators, some are based on hybrid architectures and some try to develop higher-level cognitive functions at purely symbolic level. What are the merits, what are the limitations, and what can we expect at the end of each road? Potential applications span across areas of basic brain research and medicine to cognitive robotics and space research.

At the WCCI 2006 congress we plan to have a special session and a panel discussion aimed at defining a roadmap to building systems with human-level intelligence. It is a multi disciplinary subject demanding concentrated effort of experts from various fields. The emphasis will be on the scalability of the proposed models, defining the series of challenges that should be solved by these models, evolutionary and bootstrap approaches that may bring us there faster. Before the panel we shall have a special session where position papers will be presented. An edited book containing expanded versions of these papers will be published after the conference. Such organization should allow us to concentrate more on intensive discussion during the panel.

A "Little Man" Trashes Aubrey de Grey -- Pfffehhh!!

2005-12-02T17:10:00.000-08:00

The following letter – a piece of biased, absurd and asinine “science journalism” -- was just in the Chronicle of Higher Education. It pertains to the intriguing and pathbreaking ideas of Aubrey de Grey, one of my favorite anti-aging researchers. (Check out Aubrey's website for yourself; read his papers and make up your own mind.)

A 'Fantasy' of Immortality
The Chronicle of Higher Education, 5.12.2

To the Editor:

It is very sad to see The Chronicle featuring a story on Aubrey de Grey, and compounding this mistake with an online chat with him ([3]"The Man Who Would Murder Death," October 28). The Chronicle might note that it is only one in a long list of publications that has written about Mr. de Grey; unfortunately, the story is typically uncritical of his ideas. For example, he is described as "a serious, thoughtful, sincere, prolific, even brilliant researcher." How do you know? ... Whose expertise was used to decide?

In fact, much of what Aubrey de Grey has written is unscientific speculation and outright fantasy; it should be obvious that this is incompatible with the role of any legitimate researcher, much less a serious or brilliant one. A few researchers, like Anthony Atala and Graham Pawelec, appear to support de Grey's enthusiasm and his unusual style, and possibly even his ideas. But style is not substance, and it would be surprising if those few supporters in science had actually read de Grey's writings. ... Those who have read and understood them have passively allowed de Grey to peddle nonsense because, generally, scientists do not respond to fanciful speculation. ...

However, the situation with de Grey is reaching a turning point, and in the next few months many scientists will be publicly expressing their thoughts on him and his Strategies for Engineered Negligible Senescence. The gist of these thoughts is that SENS is not science, or legitimate scholarship of any kind. One letter along those lines, signed by over 20 eminent scientists, has already appeared in EMBO reports. ...

Why are scientists taking this step with de Grey and not with most cranks? Because of stories like the one in The Chronicle, which have given him loads of publicity and a degree of respect that his pseudoscientific prognostications cannot earn him. ...

De Grey made a bet that all 13 mitochondrial proteins would have been successfully moved to the nucleus by October 2005. It is now November 2005, and this achievement has not been reported; in fact, virtually no progress on this problem has been reported.

What can de Grey do about this? What blame should he share, since he does not do any actual research, and progress on this problem is in the hands of actual scientists? He is just a cheerleader who doesn't understand and cannot do the science, so we cannot blame him that real scientists did not fulfill his expectations, right?

But that is the primary problem with de Grey's speculations: Since he neither understands how real scientific research is done nor does it himself, he places the burden of scientific research and development in the hands of people who are able to do these things, while he simultaneously calls them ignorant and rejects their scientifically sound belief that SENS is not legitimate science. ...

The long-term interests of The Chronicle would be well served if you interviewed some actual researchers in gerontological research or related fields, who represent real science and its prospects. Sorry, we can't promise imminent biological immortality -- or vacation trips to Pluto or back into time. We're scientists, not gods or wizards.

Preston (Pete) Estep III
President and Chief Executive Officer
Longenity Inc.
Waltham, Mass.

Funny as heck! But it’s (sort of) fair enough for the Chronicle to publish this crap, I suppose, since it did publish a positive article on Aubrey’s work (which is what occasioned Pete Estep’s attack).

I have studied many of Aubrey's papers and have found them to include a lot of rigorous biological science. Of course, it's true that he's also made a lot of speculative conjectures that could be classified as "fanciful speculation" if one wanted to adopt a negative emotional tone. But the truth is that "fanciful speculation" of this sort is a necessary precondition to any kind of big scientific advance. Recall, for instance, Riemann's fanciful speculations that it might make sense to think about physical space as having more than three dimensions. Fanciful indeed, yet a while later Einstein built on those ideas to create General Relativity Theory, which is real science and predicts experimental results accurately. If Einstein had been unwilling to pay attention to "fanciful speculations" like Riemann's he would not have been able to come up with his new science.

Aubrey has proposed a plausible research program (SENS = Strategies for Engineering Negligible Senescence) that is aimed at rigorously validating or falsifying his hypotheses (i.e. "speculations") about the conquest of aging. He is trying to raise a large amount of funds to carry out this program -- and this may be part of the reason why some folks in the mainstream of biology don't like him! They're afraid that he might succeed in raising money for his research, while will take money away from their (less risky, less adventurous, less exciting) research.

In my own work on AGI (Artificial General Intelligence) I have found it necessary to mix up speculation with rigorous science pretty freely. It's true that this is different than the more down-to-earch scientific work one typically sees. But if one is trying to make a big leap ahead of the current state of knowledge, there's really no other way to do it. This kind of work is higher-risk and higher-reward than conventional scientific research, and it's only natural for the "little men" of conventional science to put it down. To hell with them.

Aubrey de Grey may be wrong --- I think he's wrong on some things and right on others (for whatever my opinion on biology is worth). But he's no crank, and he's definitely not worthy of this kind of haughty dismissiveness from a massively lesser mind like Pete Estep. Pfffeeehhhh!!!

Mining He-3 from the Moon

2005-12-01T14:55:00.000-08:00

From an email discussion list that I'm on:

"
I've heard a really interesting rumor....it goes like this: There's abundant H3 (Hydrogen3) on the moon. H3 is big-badda-BOOM in terms of kinetic energy, a small amount makes a large explosion. Big Oil misusing it's current position of power within the government to use NASA to explore the moon, certainly cheaper than creating a seperate infrastructure for space exploration. Thus the explanation of ending funding for the Hubble and transferring the funding to seemingly frivolous Lunar Exploration. There are plans to extract the H3 and find a safe way to ship it planetside, so after they've milked all the oil, they can create dependence on yet another difficult-to-extract resource, namely H3.

Mind you, I live surrounded by extremist hippies who have even less idea than I do how possible it is to produce H3 earthside. It seems difficult at best to ship containers of H3 through the atmosphere and land them safely,after all they are basically very large bombs (Hindenburg anyone? and thatwas simple hydrogen).

Still, it's amusing and making the rounds of theBirkenstock-clad drones. Debunk the myth for me!
"

Interesting...

Actually, I believe they mean "Helium 3" or He-3, not Hydrogen 3, see:

http://www.space.com/scienceastronomy/helium3_000630.html

All this was discussed a while ago in Mining the Sky, a reasonably decent tract of space exploration evangelism.

I hope we do go to the moon and bring back loads of He-3 and use it to power fusion reactions... (but I hope even more that we can create Friendly AI's and let them transform the universe for the better within the next couple decades, so that the AI's can rapidly handle all the boring helium-digging for us!!)

-- Ben G

Google and Genetics Research

2005-11-29T13:02:00.000-08:00

A recent article ( http://www.timesonline.co.uk/article/0,,2095-1892323,00.html ) highlights Google's possible entry into the field of genetics data mining.

The article points out correctly that in terms of genetics and biology, there is a very real "islands of information" problem that makes just accessing data painful. Google apparently wants to bring to bear their search technology to allow people to search on some biological term(s) and get useful results back from these various sources. While this is a decent first step, I see the problem as being much more complicated than this simplistic approach.

Biological data comes in many forms. There is the Gene Ontology, which is hierarchical. There is the KEGG pathway database which is more akin to nodes and links; there is the sequence database which lends itself to custom chromosome viewer graphics, and the list goes on and on. Much of this data lends itself to specific visual/graphical views that may be distinct to the data type. But these various data sources do represent atoms of information that are not independent...they are related to eachother. Sequence information denotes the underpinnings of genes, genes produce proteins/enzymes that are in pathways, and genes are also characterized by function in Gene Ontology. The point I am making is that for this information to be manageable and digestable to the researcher, a seamless graphical interface has to be layered on top of the data. This interface must allow users to easily move between these disparate sources, allowing the user to piece the puzzle together of what a SNP/Gene/Protein is doing. I don't see Google solving this problem soon...the graphics are challenging as is the data integration problem. There are well over 100 significant biological databases that could be utilized in such a manner as described above.

The problem gets harder when you realize that almost all of the real data out there that is useful to researchers is stored in research papers. I can tell you that this is not a task for your mother's NLP system to address. No truly competent language processor has yet to be able to comb through thousands of research papers and determine what the contents of the paper are. Until this information is successfully mined, researchers will continue to be constrained by this bottleneck. I am rather dismayed that some standards body has not stepped forward to mandate an XML type standard that would accompany every new paper and allow for easy mining of papers' content. Perhaps I should undertake to do this :)

Lastly, but not leastly, what really is needed is to take all this aggregated information and apply some real AI to it. We don't need superhuman, or even human level, AI here...we just need a very good and accurate inference system. The depth and breadth of data that resides out "there" tells me that there are discoveries to be made by looking collectively at these many sources and inferring relations that weren't previously known. A human could do the same, but the sheer volume of data, in many different places and in many different forms, makes it laborious at best, and intractable at worst. This is a perfect application for a competent AI inference system.

I have sketched out a design to do all of the above, and even more. The problem is resources and time and money....I hope someday to be able to have the time and money to implement this system... I firmly believe that it would have a major impact on research in the biological field.

Cheers,
Kevin Cramer

Review of the Librie "Electronic Book" Reader

2005-11-29T08:14:00.000-08:00

Matt Bamberger has posted an interesting review of the Librie electronic book reader here:

http://www.mattbamberger.com/Main/updates/TheSonyLibrie

This is definitely a technology whose time WILL come, and Matt makes a decent argument that its time of arrival is near in terms of technology -- though there is not yet enough content published in Librie format to make it worthwhile for most people to buy one.

-- Ben Goertzel

Review of "The Mind and the Brain" by Jeffrey Schwartz

2005-11-27T10:11:00.000-08:00

I just read a fairly interesting book called

The Mind and the Brain: Neuroplasticity and the Power of Mental Force

by Jeffrey Schwartz and Sharon Begley.

The interesting part of the book is the wealth of biological examples, which illustrate the powerful ways in which the human brain can modify its own structure during adult life. When I first studied neuroscience in the 1980's we were taught that the brain can't grow new neurons or synapses after childhood. I was always skeptical of this and now it turns out that the old wisdom was false: brains can and do grow new neurons and synapses during adulthood, and this is a significant aspect of the way humans learn over their lifetimes.

The lead author is an expert on the treatment of obsessive-compulsive disorder and gives interesting examples of how appropriate therapies allow patients to overcome OCD via neural restructuring (which can be observed via brain scanning).

The frustrating part of the book is the end where the author draws on Stapp's ideas to argue that neural restructuring is a consequence of quantum dynamics in the brain -- that this restructuring is caused by some quantum-enabled "force of will". None of the biological material presented seems to demand this kind of recourse to quantum magic, and it weakens the book considerably (although from the author's perspective it's one of the main points of the book!).

(A concise version of my own current view on the relation between quantum theory and consciousness is here:
http://www.goertzel.org/blog/2005/10/quantum-theory-and-consciousness.html)

IBM's new Cell processor and its potential uses for AI

2005-11-27T05:52:00.000-08:00

The following link

http://www.ibm.com/developerworks/power/library/pa-fpfunleashing/?ca=dgr-lnxw01CellUnleash

contains some interesting information on IBM's new Cell processors (used inside the PlayStation 3).

I am left wondering whether the Cell Broadband Engine could potentially be effective for Genetic Programming learning. (In Novamente we use an evolutionary learning algorithm different from GP, but it's similar enough that if the CBE can do GP, then it can do our algorithm as well.)

I am curious for the opinion of others who are more knowledgeable about such things. (I'm not really a hardware guy.)

Looking over the article referenced, it seems to me that the PPE (the main processing unit, a PowerPC variant) could be used to run the main GP algorithm, and then fitness evaluations could be carried out on the 8 SPE's ("synergistic processing units") in parallel.

For Novamente-relevant cases (as opposed to mathematical optimization problems) this would require what the above article calls a "Large single-SPE programming model", meaning that the SPE would need to access main memory to do its fitness evaluation. (Because for Novamente learning, fitness evaluation of evolved programs has to do with comparison of programs against fairly large databases of experientially and inferentially acquired knowledge.)

A downside is that the Cell has only 256MB of RAM. This doesn't seem to be a fundamental obstacle to GP applications but it means care would have to be taken in coding/design.... In the application I envision, most of the RAM would be taken up by the set of data against which the candidate programs are compared during the fitness evaluation process.

Of course, the basic idea is that if this worked it would be much cheaper to buy PS3's than 8-processor PC's, so a much larger evolutionary learning farm could be constructed at a relatively modest budget.

Hmmmm...

-- Ben Goertzel

Chimps may lack altruism

2005-11-03T07:33:00.000-08:00

This article

http://www.thestate.com/mld/thestate/news/nation/13007022.htm

reports research showing that chimpanzees, at least in a laboratory setting, lack the altruistic impulse that characterizes some humans.

To quote:

"
The experiment gave the animals the opportunity to pull a lever and provide treats for chimps in adjacent cages — without receiving anything in return and at no cost to themselves.

No cost. No benefit. Sorry, Bonzo, no banana.
"

If this holds up it has interesting implications regarding the evolution of human altruism.

I was reminded however of some experiments I read about in the book "The Curse of the Self" this morning (it's a decent though not awesome book, with a lot of interesting research-psychology tidbits assembled in favor of its Buddhistic theme on the dangers associated with the psychological construct called "self"). In these experiments, a set of people was divided into two groups by a series of coin tosses, and then informed about who was in their group and who was not. Then, people were asked questions about the individuals in their group and in the other group -- and systematically people rated individuals in their (randomly selected!) group higher on various scales than people in the other group. This sort of finding has been replicated repeatedly and seems pretty robust.

Maybe if you divided the chimps into randomly selected groups and let them know who was on their team, then the chimps in each group would be willing to pull the levers to give each other bananas! Hmmm....

It is nice to know that we are more ethically advanced than chimps, but unfortunately I don't think we've advanced all that far, given the society I see around me....

But at least we do have the notion of balancing selfishness with altruism -- i.e. of balancing the good of our own individual system with the good of the larger systems in which we're embedded. We have a hard time figuring out how to carry out this balancing act, but even choosing to carry out such a balancing act at all is progress beyond our chimp forebears, it would seem.

And I do call this "progress" intentionally -- I think that it's progress not only in the narrow sense of agreeing better with human value systems, but also in the broader sense that it leads to more complex and interesting structures than the chimp way. Altruism, kept within appropriate bounds, promotes the emergence of complex inter-organismic social structures, which support things like mathematics, literature, books, articles, experiments and blogs. Some libertarians have argued that pure selfishness would lead to more complex and productive emergent inter-human structures, but I tend not to believe it. My guess is that, if the emergence of interesting social and cultural systems is the goal, there is some optimal level of altruism which is between zero and maximal.