[[posterous-content:pid___0]]It has only just occurred to me that in almost every single conflict the military seeks the blessing of the clergy. It is almost as if they are so unsure of their position that they need to check in with the boss to make sure that it’s ok to blow the enemy to bits.

I’m hoping tha the young Buddhist monks in the picture above said no.

But that’s not why i’m writing to you today because I just published a very short post on my blog “Transforming Communication” that discusses how much truth is there really in that old myth that we’re genetically predisposed towards being warlike.

I have my opinions and I’m really curious to know what your views are…Do you have any views about war or are your views manipulated by the media ?

Only one way you’ll ever find out

Go here——> http://www.transformingcommunication.com/blog/2012/03/20/why-war-may-not-be-inevitable/

What do you want when you communicate with somebody ?

The reality is that being perceived as an expert communicator should  NOT be your number 1 priority.

Realise that what you are looking for is  to have control of the response. Your response…

Your first priority when communicating is to be sure that what you are  saying has been understood. Until that happens everything else is completely irrelevant, simply  because you are not communicating.

The message is not getting through.

You also have a responsibility to understand what is being said to you. Without both of these  components you are still not communicating.

You are talking AT each other.

You are probably thinking well yes this is all very well but doesn’t the other person also have the same responsibilities to understand me. I mean hey, my view is important here too.

The answer is yes…and no

There are two parties to any communication and because you are here and reading this I assume that you want to improve the type of communication you’re having with other people. I assume that you want to improve the quality of your communication which may mean that you get better responses to your questions or deeper levels of truth or emotions.

Either way, whatever you want out of your communication It is your responsibility to ensure that you get the responses that you need.

If you want more truthfulness…

If you want to be respected more …

If you want to have more influence or more friends..

or

Any other type of response you can think of.

Remember…Only you are in charge of your brain.

And if you don’t think that you’re in charge of it, then who is and who decided you would let them control your thinking ? Think about that…Because if you can consider who is actually in charge of your thinking it means that you really are the one who is in charge of your thoughts.

Right !

That means that you  not only have the power to take control of what you think. You also get to decide what you say  and how you say it.

Your brain receives a massive amount of information from your ears and eyes and then it decides what that information means. Your mind decides what the messages that you get from the outside world mean and then it tells you about that message. It tells you by encoding that information as a belief. Another aspect that makes up your beliefs are your values.

Values are  powerful beliefs that you use to measure yourself against in terms of your results and also your actions. Another word for your values is your conscience. What you believe to be right and good.

So let’s imagine that you have had a message from your boss or your partner. The message says that they are not very happy about something you have done.

That message could be interpreted that you are a victim of circumstance and powerless to change your life for the better… That your boss dominates your life and change is beyond your control…Your partner is the one that makes the decisions for you and so they must be right.

The same information could also be interpreted that while your life is not exactly what you want, at the moment,  you have got lots of really big incentives to change it and “By golly you’re not going to let anything or anyone stop you from getting it…”

The thing you can understand here is that YOU are the one who decides what the information you receive means. And you are the one who decides what you will do with that meaning.

Here’s a little test for your beliefs and what they mean to you… 

I am assuming that you have a goal that you will get as a result of having better communication skills. Yes ?

Do your current beliefs and the meaning you have attached to them, get you closer to your goals or do they move you further away from them ? And if they are not supporting you in getting your goals is there something else you could believe that would be more useful ?

You have the power to make a choice. You can stick with what has not worked so far…You can keep on doing those things that frustrate you and upset you…

Or you can decide right now that as you realise you are reading this and as you become aware that you are understanding these words… you can change what you believe about anything  you want to.

Your whole life is just made up of thoughts. thoughts that come into and flow through your mind. And you get to decide whether you believe them or not and what you want to do about that.

And even when the thoughts  say you have no control…You can still ask them this question…

Says who, specifically ?

and just be aware of the answers that come to you.

I came across this today on the Casey Daily Dispatch. It confirms what you may have already suspected. that you are truly amazing. You can sign up for their free newsletter here. I get nothing from this as there is no commision payable here. it’s just good solid information.

If you ever felt inadequate when faced with the latest technology well, you can relax because your brain is still at least ten times faster than the worlds best super computer…and will remain so for the foreseeable future.

Round One of The Fight of the Millennium

Wetware is a term applied to biologically based information processors. There aren’t any commercial devices of this sort on the market – you can’t go and pick one up at Best Buy – yet the world has a couple trillion of them running around. We’re talking about brains, the amazing computers that power every animal on the planet.  

And, of course, as evidenced by the fact that this article is both written and being read, we know there is no more advanced piece of wetware walking the earth than the human brain. But even calling the brain by such a term implies that it is some kind of supercomputer whose components can be analyzed as you would your Mac… and that an understanding of the interplay of hard- and software on our desktops allows us to model that most mysterious of organs.

But is what’s inside our heads really comparable to product offerings from Apple, Intel, and Microsoft?

Well, actually, in some ways it is.

After all, both are electrical at their core, and both are based on binary logic. But when it comes to relative computing power, there is simply no contest.

The building block of electronic computers is the logic gate, through which all information processing flows. It takes two or more input impulses and translates them into an output impulse according to the simple on/off, zeroes and ones, true/false binary structure with which most everyone is at least vaguely familiar.

Two simple ones are AND gates and OR gates, which schematically look like this:

(If you’d prefer to see a logic gate in action, here’s an entertaining video that uses dominoes to demonstrate the principle.)

Traditionally, the logic gate employs transistors. Sure, there are other options, such as optical and molecular. And out on the fringe, researchers are tinkering with crazy ideas like spintronics and quantum gates.

But for now we mostly have transistors, with the binary nature of their output determined by whether the current passing through them is “strong” or “weak.” The number of them that can be embedded in a computer chip has grown exponentially for the past half-century, more or less in accordance with “Moore’s Law.” This most famous law of information technology states that the number of transistors on a chip will double about every two years, for the same unit cost. Thus, in 1971, we could fit only 2,300 transistors on a chip. In 2011, we can squeeze in something like 2.3 billion.

That’s a lot of decision-making logic gates, and it puts an enormous amount of computing power at our fingertips.

By contrast, our brains must seem puny. Right? 

In fact, that is far from the case. We may not be able to solve advanced math problems in our heads in microseconds, but that doesn’t mean we don’t each own our personal advanced supercomputer. We’re just tuned for very different tasks than your average computer, which doesn’t have to find food or watch out for predators.

The human brain is truly unique. To begin understanding its complexity, you have to look at it on the cellular level.

Although this certainly isn’t the whole story, the brain can be broken down very roughly into two different kinds of cells, neurons and glial cells. Neurons do the heavy lifting, i.e., they conduct electrical impulses. Glial cells do not; they’re the sidekicks to the big guys, irreplaceable yet usually uncredited. They surround neurons and provide support for them and insulation between them (i.e., prevent crossed wires). Bidirectional communication exists between glial cells and neurons, and between glial cells and vascular cells. Until recently, it was believed that the number of glial cells outnumbered neurons by 5-10 times, but the latest research indicates that their numbers are actually approximately equal.

The staggering thing is how many of these cells there are. Exactly how many, no one knows. There are just too many, and they are just too small, to actually count. There are only really rough ballpark guesses. If you search the data, you will find estimates ranging from 50 billion to a trillion, with 100 billion a nice round number that a lot of people tend to agree on.

A 2009 article in the Journal of Comparative Neurology attempts to pin it down more precisely and comes up with a similar figure: “… despite the widespread quotes that the human brain contains 100 billion neurons and ten times more glial cells, the absolute number of neurons and glial cells in the human brain remains unknown. Here we determine these numbers by using the isotropic fractionator and compare them with the expected values for a human-sized primate. We find that the adult male human brain contains on average 86.1 ± 8.1 billion NeuN-positive cells (‘neurons’) and 84.6 ± 9.8 billion NeuN-negative (‘nonneuronal’ or glial) cells.” (An isotropic fractionator is a technique for breaking down highly complex brain structures into just their nuclei, making them easier to count in a lab.)

Of the neurons, there seems to be a fairly general agreement that about 22 billion of them reside in the cerebral cortex alone, the 2- to 4-millimeter-thick layer on the outer region of the mammalian brain often dubbed “gray matter” after its appearance once preserved. The rest of the mass of the brain appears to be mostly made up of wiring in the form of axons to connect the brain’s specifically programmed regions to each other and the rest of the nervous system.

Whatever the case, it might be tempting to see a neuron as the functional equivalent of the computer’s transistor. That, however, would be an error. It’s way more complicated than that.

This, highly simplified, is what a garden-variety neuron looks like:

Every neuron has an axon (usually only one). The axon is an “output” fiber that sends impulses to other neurons. Each neuron also has a proliferation of dendrites – short, hair-like “input” fibers that receive impulses from adjacent neurons. When a dendrite is stimulated in a particular way, the neuron to which it is attached suddenly changes its electrical polarity and may fire, sending a signal out along its single axon where it may be picked up by the dendrites of other neurons.

The connections are made via synapses - conductive links between abutting neurons. The links are formed at narrow spaces between the sending and receiving neurons, known as gap junctions. One gap junction channel is composed of two connexons (or hemichannels), each of which is made up of six connexins that can move together to open and close the connexon, as pictured below. It’s much like a camera’s iris. The two connexons bond across the intercellular space, allowing electrical or chemical signals to pass from one cell to another.

The brain features both chemical and electrical synapses, with the latter most often used to trigger actions that require a quick response time, as in the “fight or flight” reflex. Electrical synapses, like the one above, are characterized by a microscopic gap junction, 2-4 nanometers, as you can see. Chemical synapses’ gaps are still tiny, but about 10 times larger.

These things are fast. Signals are transmitted across a chemical synapse in about 2 milliseconds (ms), and an electrical synapse in about 0.2 ms.

But the real eye-opener is how many there are. Babies are born with about 2,500 synapses in an average neuron. By the time the adult human brain is fully formed, that number has ballooned to 10-15,000.

Synapses are the true closest analogue to transistors. They are similarly binary, open or closed, letting a signal pass through or blocking it. So our biocomputer has – taking a median estimate of 12,500 synapses/neuron, and taking the consensus estimate of 22 billion cortical neurons – something on the order of 275 trillion transistors. In other words, our cerebral cortex alone contains the implied equivalent of about 120,000 of our most advanced chips.

As to processor speed, let’s assume a very conservative average firing rate for a neuron of 200 times per second. If the signal is passed to 12,500 synapses, then 22 billion neurons are capable of performing 55 petaflops (a petaflop = one quadrillion calculations) per second.

The world’s fastest supercomputer, a monster from Japan unveiled by Fujitsu at a conference this past June, has a configuration of 864 racks, comprising a total of 88,128 interconnected CPUs. It tested out at 8 petaflops (which only five months later was upped to 10.51 petaflops). Our brains are nearly five times faster.

But that’s not even half the story. Unlike transistors locked into place on their silicon wafers, synaptic connections can and do move over time, creating an ever-shifting environment where the possible hookups are, for all practical purposes, limitless. Furthermore, there are another 78 billion neurons, give or take, outside of the cortex, hard at work on other complex functions.

The wiring complexity of our brains alone means that in the crude terms we understand computers today, our brains are much more complex than anything we’ve built, and still faster than even the most expensive supercomputer ever built.   

On top of that, we are only beginning to understand the complexity of that wiring. Instead of one-to-one connections, some theorists postulate that there are potentially thousands of different types of inter-neuronal connections, upping the ante. Moreover, recent evidence points to the idea that there is actually subcellular computing going on within neurons, moving our brains from the paradigm of a single computer to something more like a self-contained Internet, with billions of simpler nodes all working together in a massive parallel network. All of this may mean that the types of computing we are capable of are only just being dreamt of by computer scientists. 

Will our electronic creations ever exceed our innate capabilities? Almost certainly. Futurist Ray Kurzweil predicts that there will be cheap computers with the same capabilities as the brain by 2023. To us, that seems incredibly unlikely. But on a slightly longer time frame, given the exponential advances of the field, it is quite possible that there are humans alive today who will live to see the day. 

The main stumbling block right now is that, as ever more powerful computers are built, there is a concurrent expansion of power, management, and structural issues. But the Defense Advanced Research Projects Agency (DARPA) is putting its money on the line, betting that the problems can be overcome. And soon.

In late 2010, DARPA awarded the first grants to firms it wants to build so-called exascale computers, i.e., machines capable of performing a quintillion computations per second. DARPA expects the first prototypes to be working by 2018.

At that point, they’ll be faster than us, but the software will still be far behind. But even there things march forward rapidly, with advances in artificial intelligence. 

For the moment, at least, wetware reigns supreme.

Yet, instead of being built from exotic materials, involving hundreds of engineers, and plugging into a worldwide electrical grid, our brain both builds and powers itself with cheeseburgers and blueberries. And then uses what’s left over to help us dream up machines that may one day be as smart as we are.

I came across this today on the Casey Daily Dispatch. It confirms what you may have already suspected. that you are truly amazing. You can sign up for their free newsletter here. I get nothing from this as there is no commision payable here. it’s just good solid information.

If you ever felt inadequate when faced with the latest technology well, you can relax because your brain is still at least ten times faster than the worlds best super computer…and will remain so for the foreseeable future.

Round One of The Fight of the Millennium

Wetware is a term applied to biologically based information processors. There aren’t any commercial devices of this sort on the market – you can’t go and pick one up at Best Buy – yet the world has a couple trillion of them running around. We’re talking about brains, the amazing computers that power every animal on the planet.  

And, of course, as evidenced by the fact that this article is both written and being read, we know there is no more advanced piece of wetware walking the earth than the human brain. But even calling the brain by such a term implies that it is some kind of supercomputer whose components can be analyzed as you would your Mac… and that an understanding of the interplay of hard- and software on our desktops allows us to model that most mysterious of organs.

But is what’s inside our heads really comparable to product offerings from Apple, Intel, and Microsoft?

Well, actually, in some ways it is.

After all, both are electrical at their core, and both are based on binary logic. But when it comes to relative computing power, there is simply no contest.

The building block of electronic computers is the logic gate, through which all information processing flows. It takes two or more input impulses and translates them into an output impulse according to the simple on/off, zeroes and ones, true/false binary structure with which most everyone is at least vaguely familiar.

Two simple ones are AND gates and OR gates, which schematically look like this:

(If you’d prefer to see a logic gate in action, here’s an entertaining video that uses dominoes to demonstrate the principle.)

Traditionally, the logic gate employs transistors. Sure, there are other options, such as optical and molecular. And out on the fringe, researchers are tinkering with crazy ideas like spintronics and quantum gates.

But for now we mostly have transistors, with the binary nature of their output determined by whether the current passing through them is “strong” or “weak.” The number of them that can be embedded in a computer chip has grown exponentially for the past half-century, more or less in accordance with “Moore’s Law.” This most famous law of information technology states that the number of transistors on a chip will double about every two years, for the same unit cost. Thus, in 1971, we could fit only 2,300 transistors on a chip. In 2011, we can squeeze in something like 2.3 billion.

That’s a lot of decision-making logic gates, and it puts an enormous amount of computing power at our fingertips.

By contrast, our brains must seem puny. Right? 

In fact, that is far from the case. We may not be able to solve advanced math problems in our heads in microseconds, but that doesn’t mean we don’t each own our personal advanced supercomputer. We’re just tuned for very different tasks than your average computer, which doesn’t have to find food or watch out for predators.

The human brain is truly unique. To begin understanding its complexity, you have to look at it on the cellular level.

Although this certainly isn’t the whole story, the brain can be broken down very roughly into two different kinds of cells, neurons and glial cells. Neurons do the heavy lifting, i.e., they conduct electrical impulses. Glial cells do not; they’re the sidekicks to the big guys, irreplaceable yet usually uncredited. They surround neurons and provide support for them and insulation between them (i.e., prevent crossed wires). Bidirectional communication exists between glial cells and neurons, and between glial cells and vascular cells. Until recently, it was believed that the number of glial cells outnumbered neurons by 5-10 times, but the latest research indicates that their numbers are actually approximately equal.

The staggering thing is how many of these cells there are. Exactly how many, no one knows. There are just too many, and they are just too small, to actually count. There are only really rough ballpark guesses. If you search the data, you will find estimates ranging from 50 billion to a trillion, with 100 billion a nice round number that a lot of people tend to agree on.

A 2009 article in the Journal of Comparative Neurology attempts to pin it down more precisely and comes up with a similar figure: “… despite the widespread quotes that the human brain contains 100 billion neurons and ten times more glial cells, the absolute number of neurons and glial cells in the human brain remains unknown. Here we determine these numbers by using the isotropic fractionator and compare them with the expected values for a human-sized primate. We find that the adult male human brain contains on average 86.1 ± 8.1 billion NeuN-positive cells (‘neurons’) and 84.6 ± 9.8 billion NeuN-negative (‘nonneuronal’ or glial) cells.” (An isotropic fractionator is a technique for breaking down highly complex brain structures into just their nuclei, making them easier to count in a lab.)

Of the neurons, there seems to be a fairly general agreement that about 22 billion of them reside in the cerebral cortex alone, the 2- to 4-millimeter-thick layer on the outer region of the mammalian brain often dubbed “gray matter” after its appearance once preserved. The rest of the mass of the brain appears to be mostly made up of wiring in the form of axons to connect the brain’s specifically programmed regions to each other and the rest of the nervous system.

Whatever the case, it might be tempting to see a neuron as the functional equivalent of the computer’s transistor. That, however, would be an error. It’s way more complicated than that.

This, highly simplified, is what a garden-variety neuron looks like:

Every neuron has an axon (usually only one). The axon is an “output” fiber that sends impulses to other neurons. Each neuron also has a proliferation of dendrites – short, hair-like “input” fibers that receive impulses from adjacent neurons. When a dendrite is stimulated in a particular way, the neuron to which it is attached suddenly changes its electrical polarity and may fire, sending a signal out along its single axon where it may be picked up by the dendrites of other neurons.

The connections are made via synapses - conductive links between abutting neurons. The links are formed at narrow spaces between the sending and receiving neurons, known as gap junctions. One gap junction channel is composed of two connexons (or hemichannels), each of which is made up of six connexins that can move together to open and close the connexon, as pictured below. It’s much like a camera’s iris. The two connexons bond across the intercellular space, allowing electrical or chemical signals to pass from one cell to another.

The brain features both chemical and electrical synapses, with the latter most often used to trigger actions that require a quick response time, as in the “fight or flight” reflex. Electrical synapses, like the one above, are characterized by a microscopic gap junction, 2-4 nanometers, as you can see. Chemical synapses’ gaps are still tiny, but about 10 times larger.

These things are fast. Signals are transmitted across a chemical synapse in about 2 milliseconds (ms), and an electrical synapse in about 0.2 ms.

But the real eye-opener is how many there are. Babies are born with about 2,500 synapses in an average neuron. By the time the adult human brain is fully formed, that number has ballooned to 10-15,000.

Synapses are the true closest analogue to transistors. They are similarly binary, open or closed, letting a signal pass through or blocking it. So our biocomputer has – taking a median estimate of 12,500 synapses/neuron, and taking the consensus estimate of 22 billion cortical neurons – something on the order of 275 trillion transistors. In other words, our cerebral cortex alone contains the implied equivalent of about 120,000 of our most advanced chips.

As to processor speed, let’s assume a very conservative average firing rate for a neuron of 200 times per second. If the signal is passed to 12,500 synapses, then 22 billion neurons are capable of performing 55 petaflops (a petaflop = one quadrillion calculations) per second.

The world’s fastest supercomputer, a monster from Japan unveiled by Fujitsu at a conference this past June, has a configuration of 864 racks, comprising a total of 88,128 interconnected CPUs. It tested out at 8 petaflops (which only five months later was upped to 10.51 petaflops). Our brains are nearly five times faster.

But that’s not even half the story. Unlike transistors locked into place on their silicon wafers, synaptic connections can and do move over time, creating an ever-shifting environment where the possible hookups are, for all practical purposes, limitless. Furthermore, there are another 78 billion neurons, give or take, outside of the cortex, hard at work on other complex functions.

The wiring complexity of our brains alone means that in the crude terms we understand computers today, our brains are much more complex than anything we’ve built, and still faster than even the most expensive supercomputer ever built.   

On top of that, we are only beginning to understand the complexity of that wiring. Instead of one-to-one connections, some theorists postulate that there are potentially thousands of different types of inter-neuronal connections, upping the ante. Moreover, recent evidence points to the idea that there is actually subcellular computing going on within neurons, moving our brains from the paradigm of a single computer to something more like a self-contained Internet, with billions of simpler nodes all working together in a massive parallel network. All of this may mean that the types of computing we are capable of are only just being dreamt of by computer scientists. 

Will our electronic creations ever exceed our innate capabilities? Almost certainly. Futurist Ray Kurzweil predicts that there will be cheap computers with the same capabilities as the brain by 2023. To us, that seems incredibly unlikely. But on a slightly longer time frame, given the exponential advances of the field, it is quite possible that there are humans alive today who will live to see the day. 

The main stumbling block right now is that, as ever more powerful computers are built, there is a concurrent expansion of power, management, and structural issues. But the Defense Advanced Research Projects Agency (DARPA) is putting its money on the line, betting that the problems can be overcome. And soon.

In late 2010, DARPA awarded the first grants to firms it wants to build so-called exascale computers, i.e., machines capable of performing a quintillion computations per second. DARPA expects the first prototypes to be working by 2018.

At that point, they’ll be faster than us, but the software will still be far behind. But even there things march forward rapidly, with advances in artificial intelligence. 

For the moment, at least, wetware reigns supreme.

Yet, instead of being built from exotic materials, involving hundreds of engineers, and plugging into a worldwide electrical grid, our brain both builds and powers itself with cheeseburgers and blueberries. And then uses what’s left over to help us dream up machines that may one day be as smart as we are.

 http://www.washingtonpost.com/national/health-science/the-aging-brain/2011/12/05/gIQAskhDWO_graphic.html?hpid=z2

Enjoy
Read more… preventing aging ? From the washington Post

“Whether you believe you can or you believe you can’t, you’re right”.

Did you know, Henry Ford was trying to raise money for his idea of producing cars on an assembly line, where each little bit was added at a certain place. The bank manager that he initially applied to, told him that the automobile was just a fad, and it would never catch on. He told him there was no point in lending him any money for that kind of frivolity.

So, whether you think you will, or whether you think you won’t, you’re right.

Beliefs structure our reality, they color our perception of what happens. They affect our values and attitudes. And how we experience the world.

Wouldn’t it make sense to adopt useful beliefs and assumptions about the world, and by doing so increase our effectiveness in what we do? Wouldn’t it be better to hold empowering beliefs instead of holding beliefs that don’t provide us with a useful system to get results?

You’ve probably noticed that the way some people think of things, is very often the way things happen. I’ve got friends who expect that things are not going to be successful and they get that belief fulfilled.

NLP, or neurolinguistic programming, has a set of assumptions and beliefs that are very useful in people’s lives. Because NLP is the study of how people succeed, what they do and what they believe in order to excel in their lives.

Now, NLP doesn’t claim these beliefs are necessarily true. But when you act as if they are true you can achieve much more easily what it is you want to achieve. They may not be true but they are definitely useful.

Henry Ford watched the 15 millionth Model T Ford roll off the assembly line in 1927. His ‘universal car’ was the industrial success story of its age. He was an American icon and one of the nation’s richest men.

By having useful beliefs about what is possible and not being deterred by other people’s unhelpful beliefs, he transformed the automobile itself from a luxury to a necessity.

What do YOU believe?

In future posts I’ll go into the different beliefs, or presuppositions, of NLP.
Read more… What Do You Believe?