“Timing devices” in the new paper are like RISC (Reduced Instruction Set Computers) in comparison to Quad Nets that are like CISC (Complex Instruction Set Computers). “Quad Nets” is based on “critical point thermodynamics” and I am confident that they are new. However, “timing devices” may have been explored by others and I will especially welcome any pointers to existing literature.

Comments and suggestions are always welcome, I am found at:
rlk “at” sonic.net
Bob Kovsky

Eric Thomson wrote several posts that included the following:

It would really help if you dissected an individual ‘tial’ mathematically. That is, what rules do they follow? What are the rules for how they interact with one another? Is there an example of a computation that they can perform? E.g., xor.
…
Bob: without an equation to describe how an individual element works, it’s impossible for me to say anything more. Even if you need six to get a cycle, it would be very helpful to know what is cycling, what the rules governing the individual elements of the cycle. It is usually pedagogically most useful to start simple, with equations that govern how an individual element (whether it be neuron, capacitor, etc) works, and then build up slowly to more interesting behavior.
…
Eric noted comparisons to:
…cellular automata, but the rules governing the behavior of individual cells is quite explicable. My main point is, that as a sociological fact, few people will read or understand your theory unless you take what you call the ‘atomic-molecular’ approach.
…
also it would be good to fill out in more detail the input-output transform being implemented by an individual element: a drawing that specifies the inputs, outputs, and the transform between the two.

…This should all be quantifiable. The controls (with parameters), the inputs, and the output (even if it is just a periodic real function). If it is open-ended, give a case with a specific set of inputs.

Mike S. wrote:
Here’s my advice, from 20 years in the industry.
1. Define what each unit does.
2. Describe how the units interact.
3. Show that the interaction causes the units to generate a representation.

http://www.technologyreview.com/TR35/

Kevin Lafferty, a parasitologist, has put forth the idea that a fairly ubiquitous parasite (infecting O(10%) of Americans, and up to 2/3 of people in places like Brazil) is responsible for some of the diversity of human culures (1). The parasite uses common housecats to increase its transmission to the next host in the life cycle, and has a subtle effect on human personality, with some studies claiming that it even causes neuroticism, and even schizophrenia. (One clinical report (2) claims that “subjects with latent toxoplasmosis had higher intelligence [and] lower guilt proneness.” Hmm!)

Anyway, Lafferty noted that toxoplasmosis varies in prevalence from world region to world region, and then tries to draw correlates between these prevalences and local cultures:

“Drivers of the geographical variation in the prevalence of this parasite include the effects of climate on the persistence of infectious stages in soil, the cultural practices of food preparation and cats as pets. Some variation in culture, therefore, may ultimately be related to how climate affects the distribution of T. gondii, though the results only explain a fraction of the variation in two of the four cultural dimensions, suggesting that if T. gondii does influence human culture, it is only one among many factors.”

I wonder how one could test this hypothesis? Look for recent immigrants from one culture to another, who have lower Toxoplasmosis incidence? (Preferably finding populations that go in opposite directions, as a control.) Track culture change vs. migration vs. climate change?

Unlikely, perhaps. But nice that people are still thinking big

– Ed

(1) Lafferty, K
Can the common brain parasite, Toxoplasma gondii, influence human culture?
Proceedings of the Royal Society B: Biological Sciences
doi:10.1098/rspb.2006.3641

Picked up by the popular press here

(2) Flegr J, Havlicek J.
Changes in the personality profile of young women with latent toxoplasmosis.
Folia Parasitol (Praha). 1999;46(1):22-8.

[This sounds interesting... although it is fine to promote your personal projects here, we'd at least like to know a little bit about how your project is achieving its goal or how your specific algorithms make this different from similar AI endeavors. And please, please always put your name at the bottom of the post! -Neville]

Bacteria secrete signals to other bacteria of the same species through vesicle packets.

Mashburn and Whiteley describe the unexpected convergence of two seemingly unrelated areas of microbiological research: how bacteria talk to their friends, and how they attack their enemies. The authors studied the bacterial pathogen Pseudomonas aeruginosa, which releases a hydrophobic molecule called the ‘pseudomonas quinolone signal’ (PQS) to send messages to other bacteria of the same species. The surprise is that, rather than being secreted as single molecules, PQS is released in bubble-like ‘vesicles’ that also contain antibacterial agents and probably toxins aimed at host tissue cells as well.

I wonder if this is evolutionarily connected to synaptic vesicles or if this is a case of something like convergent evolution…

Click more for some interesting excerpts.

In 1967, Francis H. C. Crick, the co-discoverer of DNA, and the Nobel Prize-winning biologist Sydney Brenner had called for “the complete solution of E. coli.”

But the call went unheeded for over 30 years. After all, E. coli contains an estimated 60 million biological molecules. Simulating all of them at once was an absurdly difficult task.

But by the late 1990′s, it began to look plausible, although not necessarily easy. Despite decades of research, many of E. coli’s genes still remain a mystery – “probably around 1,000 genes,” Dr. Thomas said. “There’s a lot more we need to know about E. coli before we can build a really solid model.”

Crazy, isn’t it? And as many have claimed with the brain…

“Assuming the speed of computing keeps increasing, I don’t see why it’s not possible,” said Dr. Emonet, who is not involved in Project Gemini.

But, like some other scientists, he has some reservations about its usefulness. “Even if we could make a simulation of everything inside E. coli today, that does not mean we would understand it,” he said “The trick is to build the thing in steps and check that you understand the phenomena one at a time.”

Ofria had wanted to see what would happen if he killed off any organism with a beneficial mutation. So he ran a program which tested each organism for beneficial-ness. However, the organisms evolved to recognize regularities in the test environment, and to “play dead” when they were being tested, thereby avoiding being weeded out.

BBSRC article

Roland Piquepaille’s weblog