Neural Network Quotes

Relationships may become wrecked by a quirky syndrome: the “Ain't broke, don't fix”-syndrome. When there is no interaction in the neural network and no breakthrough into the mind but only a shallow skin experience, living together might be very torturous. If a heartfelt bond has not been molded, nothing can be broken and thus nothing needs to be fixed. (“I wonder what went wrong.”)

The butterfly's wing beat of love can engender a mystical attraction in the neural meanders of our mind and generate emotional torments with a single stroke. ("I seek you")

When we get business networks to function similarly to neural networks and mycelium networks, we'll have a better world.

As advances in AI, machine learning, and neural networks evolve, incomprehensibility will reach even higher levels - exposing these complex systems to both human and machine errors.

For more than 2 million years, human neural networks kept growing and growing, but apart from some flint knives and pointed sticks, humans had precious little to show for it. What then drove forward the evolution of the massive human brain during those 2 million years? Frankly, we don’t know.

Posthuman. It was a word that came up in the media every five or six years, and it meant different things every time. Neural regrowth hormone? Posthuman. Sex robots with inbuilt pseudo intelligence? Posthuman. Self-optimizing network routing? Posthuman. It was a word from advertising copy, breathless and empty, and all he’d ever thought it really meant was that the people using it had a limited imagination about what exactly humans were capable of.

All the experiences in your life- from single conversations to your broader culture- shape the microscopic details of your brain. Neurally speaking, who you are depends on where you've been. Your brain is a relentless shape-shifter, constantly rewriting its own circuitry- and because your experiences are unique, so are the vast detailed patterns in your neural networks. Because they continue to change your whole life, your identity is a moving target; it never reaches an endpoint.

Unrelenting criticism, especially when it is ground in with parental rage and scorn, is so injurious that it changes the structure of the child’s brain. Repeated messages of disdain are internalized and adopted by the child, who eventually repeats them over and over to himself. Incessant repetitions result in the construction of thick neural pathways of self-hate and self-disgust. Over time a self-hate response attaches to more and more of the child’s thoughts, feelings and behaviors. Eventually, any inclination toward authentic or vulnerable self-expression activates internal neural networks of self-loathing. The child is forced to exist in a crippling state of self-attack, which eventually becomes the equivalent of full-fledged self-abandonment. The ability to support himself or take his own side in any way is decimated. With ongoing parental reinforcement, these neural pathways expand into a large complex network that becomes an Inner Critic that dominates mental activity. The inner critic’s negative perspective creates many programs of self-rejecting perfectionism. At the same time, it obsesses about danger and catastrophizes incessantly.

We get smarter and more creative as we age, research shows. Our brain's anatomy, neural networks, and cognitive abilities can actually improve with age and increased life experiences. Contrary to the mythology of Silicon Valley, older employees may be even more productive, innovative, and collaborative than younger ones... Most people, in fact, have multiple cognitive peaks throughout their lives.

Optimal sculpting of key neural networks through healthy early relationships allows us to think well of ourselves, trust others, regulate our emotions, maintain positive expectations, and utilize our intellectual and emotional intelligence in moment-to-moment

Describing good relatedness to someone, no matter how precisely or how often, does not inscribe it into the neural networks that inspire love. Self-help books are like car repair manuals: you can read them all day, but doing so doesn't fix a thing. Working on a car means rolling up your sleeves and getting under the hood, and you have to be willing to get dirt on your hands and grease beneath your fingernails. Overhauling emotional knowledge is no spectator sport; it demands the messy experience of yanking and tinkering that comes from a limbic bond. If someone's relationship today bear a troubled imprint, they do so because an influential relationship left its mark on a child's mind. When a limbic connection has established a neural pattern, it takes a limbic connection to revise it.

Genocide is only possible when dehumanization happens on a massive scale, and the perfect tool for this job is propaganda: it keys right into the neural networks that understand other people, and dials down the degree to which we empathize with them.

The current technological and scientific revolution implies not that authentic individuals and authentic realities can be manipulated by algorithms and TV cameras, but rather that authenticity is a myth. People are afraid of being trapped inside a box, but they don’t realise that they are already trapped inside a box – their brain – which is locked within a bigger box – human society with its myriad fictions. When you escape the matrix the only thing you discover is a bigger matrix. When the peasants and workers revolted against the tsar in 1917, they ended up with Stalin; and when you begin to explore the manifold ways the world manipulates you, in the end you realise that your core identity is a complex illusion created by neural networks.

Intelligence is not limited to neural networks, Merrill. Indeed, half of human intelligence resides in our bodies outside our skulls…The genius of the irrational…This is the body’s intelligence, not the mind’s. Every living cell possess it…[the] indomitable will to survive.

Is a mind a complicated kind of abstract pattern that develops in an underlying physical substrate, such as a vast network of nerve cells? If so, could something else be substituted for the nerve cells – something such as ants, giving rise to an ant colony that thinks as a whole and has an identity – that is to say, a self? Or could something else be substituted for the tiny nerve cells, such as millions of small computational units made of arrays of transistors, giving rise to an artificial neural network with a conscious mind? Or could software simulating such richly interconnected computational units be substituted, giving rise to a conventional computer (necessarily a far faster and more capacious one than we have ever seen) endowed with a mind and a soul and free will?

The beauty of neuroplasticity is that when you make changes to what you remember and how you remember it, what you do and how you do it, your brain overrides the old neural networks with new ones.

The intense effort to develop artificial intelligence has increased our understanding of neural networks because at its core, AI is but an attempt to improve artificially what the brain already does effortlessly.

Scientists are cautiously beginning to question the view that the brain is the sole and absolute ruler over the body. The gut not only possesses an unimaginable number of nerves, those nerves are also unimaginably different from those of the rest of the body. The gut commands an entire fleet of signaling substances, nerve-insulation materials, and ways of connecting. There is only one other organ in the body that can compete with the gut for diversity—the brain. The gut’s network of nerves is called the “gut brain” because it is just as large and chemically complex as the gray matter in our heads. Were the gut solely responsible for transporting food and producing the occasional burp, such a sophisticated nervous system would be an odd waste of energy. Nobody would create such a neural network just to enable us to break wind. There must be more to it than that.

Let me use a second metaphor. Imagine that you found a tangle of seaweed on the edge of the shore and lifted it. The heaviest parts rest on the sand in a mesh, but some skeins extend vertically. This neural network is shaped like that: it looks like a tangled skein of a hundred thousand golden threads that has been drawn upward. The mass of it gathers in the pelvis, but strands from the same network extend upward to the spinal cord and brain.

The human brain is incredible in its capacity to heal and rewire itself. The human brain can be shaped and trained to be more resilient, calm, compassionate and alert—we can condition ourselves to be successful. Through mindfulness meditation, we can literally re-wire our brains through new experiences, which modify our neural network and our neural chemistry. Mindfulness also enhances gamma synchrony and improves the function of the human brain.

We do not have time to develop a complicated neural network. This is a strictly procedural algorithm. Very complex, but not AI at all. We have to be able to test it in thousands of ways and know exactly how it responds and why. We can’t do that with a neural network.

Despite the feeling that we’re directly experiencing the world out there, our reality is ultimately built in the dark, in a foreign language of electrochemical signals. The activity churning across vast neural networks gets turned into your story of this, your private experience of the world: the feeling of this book in your hands, the light in the room, the smell of roses, the sound of others speaking.

The vulva, clitoris, and vagina are actually best understood as the surface of an ocean that is shot through with vibrant networks of underwater lightning—intricate and fragile, individually varied neural pathways.

We have more computing power in the drop ships’ tactical integrated neural network computers than existed on the entire planet fifty years ago, and somehow mission planning goes better when you’re outside in the fresh air and drawing diagrams and maps into the dirt with a pointy stick. “Two

The brain that we think of as a necessity for intelligence is only one possible form a neural network can take and that is determined by ecological function and species shape; it is not essential to intelligence. As neurologist Antonio Damasio puts it, “the mind is embodied, not just embrained.

There must be a trick to the train of thought, a recursive formula. A group of neurons starts working automatically, sometimes without external impulse. It is a kind of iterative process with a growing pattern. It wanders about in the brain, and the way it happens must depend on the memory of similar patterns.

In our everyday lives, if we intentionally set out to learn new things or do familiar things in new ways (such as commuting to work via a new route or taking the bus instead of a car), we effectively rewire our brains and improve them. A physical workout builds muscle; a mental workout creates new synapses to strengthen the neural network.

In this way, each of us has unique neural networks, which are formed, reinforced, and constantly updated by the eclectic circumstances of our lives. Once circuits are formed, that increases the chances the same circuits will fire in the future. The neural networks embody our experiences and in turn guide future action. They contain the unique way each of us carries himself in the world, the way we walk, talk, and react. They are the grooves down which our behavior flows. A brain is the record of a life. The networks of neural connections are the physical manifestation of your habits, personality, and predilections. You are the spiritual entity that emerges out of the material networks in your head.

I thought of my own self fifteen years ago, and how much I’ve changed in the same period. The me who exists today and the me who existed then, if put side by side, would look more than vaguely similar. But we are a completely different collection of molecules, with different hairlines and waistlines, and, it sometimes seems, little in common besides our names. What binds that me to this me, and allows me to maintain the illusion that there is continuity from moment to moment and year to year, is some relatively stable but gradually evolving thing at the nucleus of my being. Call it a soul, or a self, or an emergent by-product of a neural network, but whatever you want to call it, that element of continuity is entirely dependent on memory.

In a 2004 study, Angelo Maravita and Atsushi Iriki discovered that when monkeys and humans consistently use a tool to extend their reach, such as using a rake to reach an object, certain neural networks in the brain change their “map” of the body to include the new tool. This fascinating finding reinforces the idea that external tools can and often do become a natural extension of our minds.

The “losers” in memory competitions, this research suggests, stumble not because they remember too little. They have studied tens, perhaps hundreds of thousands of words, and often they are familiar with the word they ultimately misspell. In many cases, they stumble because they remember too much. If recollecting is just that—a re-collection of perceptions, facts, and ideas scattered in intertwining neural networks in the dark storm of the brain—then forgetting acts to block the background noise, the static, so that the right signals stand out. The sharpness of the one depends on the strength of the other.

Mind is just a word we use to describe neural activity in the brain. No brain, no mind. We know this because if a part of the brain is destroyed through stroke or cancer or injury or surgery, whatever that part of the brain was doing is now gone. If the damage occurs in early childhood when the brain is especially plastic, or in adulthood in certain parts of the brain that are conducive to rewiring, then that brain function—that “mind” part of the brain—may be rewired into another neural network in the brain. But this process just further reinforces the fact that without neural connections in the brain there is no mind.

For their neural networks to function, plants use virtually the same neurotransmitters we do, including the two most important: glutamate and GABA (gamma aminobutyric acid). They also utilize, as do we, acetylcholine, dopamine, serotonin, melatonin, epinephrine, norepinephrine, levodopa, indole-3-acetic acid, 5-hydroxyindole acetic acid, testosterone (and other androgens), estradiol (and other estrogens), nicotine, and a number of other neuroactive compounds. They also make use of their plant-specific neurotransmitter, auxin, which, like serotonin, for example, is synthesized from tryptophan. These transmitters are used, as they are in us, for communication within the organism and to enhance brain function.

... [O]ne of the most influential approaches to thinking about memory in recent years, known as connectionism, has abandoned the idea that a memory is an activated picture of a past event. Connectionist or neural network models are based on the principle that the brain stores engrams by increasing the strength of connections between different neurons that participate in encoding an experience. When we encode an experience, connections between active neurons become stronger, and this specific pattern of brain activity constitutes the engram. Later, as we try to remember the experience, a retrieval cue will induce another pattern of activity in the brain. If this pattern is similar enough to a previously encoded pattern, remembering will occur. The "memory" in a neural network model is not simply an activated engram, however. It is a unique pattern that emerges from the pooled contributions of the cue and the engram. A neural network combines information in the present environment with patterns that have been stored in the past, and the resulting mixture of the two is what the network remembers... When we remember, we complete a pattern with the best match available in memory; we do not shine a spotlight on a stored picture.

One of the reasons for learning about type is to recognize that we are constantly motivated, simply by the way we’ve established our neural networks, to shape reality along particular functional lines. Another is to recognize the possibilities for growth and change that exist within—and apart from—the framework we have created for ourselves. Even small changes in our usual way of doing things can make big differences in the way our brain is operating. We develop the ability to think in new ways, and this stimulates creative change in all areas of our lives.

Growth of the Body and the Brain. The physical growth of the human body increases in a roughly linear manner from birth through adolescence. In contrast, the brain’s physical growth follows a different pattern. The most rapid rate of growth takes place in utero, and from birth to age four the brain grows explosively. The brain of the four-year-old is 90 percent adult size! A majority of the physical growth of the brain’s key neural networks takes place during this time. It is a time of great malleability and vulnerability as experiences are actively shaping the organizing brain. This is a time of great opportunity for the developing child: safe, predictable, nurturing and repetitive experiences can help express a full range of genetic potentials. Unfortunately, however, it is also when the organizing brain is most vulnerable to the destructive impact of threat, neglect and trauma.

Finally, some scientists concede that consciousness is real and may actually have great moral and political value, but that it fulfils no biological function whatsoever. Consciousness is the biologically useless by-product of certain brain processes. Jet engines roar loudly, but the noise doesn’t propel the aeroplane forward. Humans don’t need carbon dioxide, but each and every breath fills the air with more of the stuff. Similarly, consciousness may be a kind of mental pollution produced by the firing of complex neural networks. It doesn’t do anything. It is just there. If this is true, it implies that all the pain and pleasure experienced by billions of creatures for millions of years is just mental pollution. This is certainly a thought worth thinking, even if it isn’t true. But it is quite amazing to realise that as of 2016, this is the best theory of consciousness that contemporary science has to offer us. Maybe

The third SADE, Rayland, who had inhabited Libre as an Independent, was unknown to most Librans. He had been network isolated and studied by Méridien neural scientists ever since he’d been diagnosed as a psychopath after he had stranded his ship and suffocated the entire crew, asking them what it felt like to die.

Despite the feeling that we’re directly experiencing the world out there, our reality is ultimately built in the dark, in a foreign language of electrochemical signals. The activity churning across vast neural networks gets turned into your story of this, your private experience of the world: the feeling of this book in your hands, the light in the room, the smell of roses, the sound of others speaking. Even more strangely, it’s likely that every brain tells a slightly different narrative. For every situation with multiple witnesses, different brains are having different private subjective experiences. With seven billion human brains wandering the planet (and trillions of animal brains), there’s no single version of reality. Each brain carries its own truth. So what is reality? It’s like a television show that only you can see, and you can’t turn it off. The good news is that it happens to be broadcasting the most interesting show you could ask for: edited, personalized, and presented just for you.

Both scientists and laypeople can find themselves seduced into the easy trap of wanting to assign each function of the brain to a specific location. Perhaps because of pressure for simple sound bites, a steady stream of reports in the media (and even in the scientific literature) has created the false impression that the brain area for such-and-such has just been discovered. Such reports feed popular expectation and hope for easy labeling, but the true situation is much more interesting: the continuous networks of neural circuitry accomplish their functions using multiple, independently discovered strategies. The brain lends itself well to the complexity of the world, but poorly to clear-cut cartography.

To cover all the bases, I also signed up for a class on psycholinguistics, which had a prerequisite in neural networking. In addition to not having taken it, I also didn’t know what neural networking was. For some reason, this didn’t really bother me, or seem like a problem. The handsome Italian professor wore the most elegant suits I had ever seen, in the most subtle colors—gray with a hint of smoky blue so elusive that you had to keep looking to be sure you hadn’t imagined it. The class met on the tenth floor of the psychology building, most of which was devoted to an institute for bat study and smelled accordingly. It was total sensory discord to see the handsome professor in his elegant suits stepping out of the elevator into the hall of stinky bats.

In addition to localized neural networks, hallucinogenic drugs have been documented to trigger such preternatural experiences, such as the sense of floating and flying stimulated by atropine and other belladonna alkaloids. These can be found in mandrake and jimsonweed and were used by European witches and American Indian shamans, probably for this very purpose.32 Dissociative anesthetics such as the ketamines are also known to induce out-of-body experiences. Ingestion of methylenedioxyamphetamine (MDA) may bring back long-forgotten memories and produce the feeling of age regression, while dimethyltryptamine (DMT)—also known as “the spirit molecule”—causes the dissociation of the mind from the body and is the hallucinogenic substance in ayahuasca, a drug taken by South American shamans. People who have taken DMT report “I no longer have a body,” and “I am falling,” “flying,” or “lifting up.

Our brain is therefore not simply passively subjected to sensory inputs. From the get-go, it already possesses a set of abstract hypotheses, an accumulated wisdom that emerged through the sift of Darwinian evolution and which it now projects onto the outside world. Not all scientists agree with this idea, but I consider it a central point: the naive empiricist philosophy underlying many of today's artificial neural networks is wrong. It is simply not true that we are born with completely disorganized circuits devoid of any knowledge, which later receive the imprint of their environment. Learning, in man and machine, always starts from a set of a priori hypotheses, which are projected onto the incoming data, and from which the system selects those that are best suited to the current environment. As Jean-Pierre Changeux stated in his best-selling book Neuronal Man (1985), “To learn is to eliminate.

In the 1990s, a set of renegade researchers set aside many of the earlier era’s assumptions, shifting their focus to machine learning. While machine learning dated to the 1950s, new advances enabled practical applications. The methods that have worked best in practice extract patterns from large datasets using neural networks. In philosophical terms, AI’s pioneers had turned from the early Enlightenment’s focus on reducing the world to mechanistic rules to constructing approximations of reality. To identify an image of a cat, they realized, a machine had to “learn” a range of visual representations of cats by observing the animal in various contexts. To enable machine learning, what mattered was the overlap between various representations of a thing, not its ideal—in philosophical terms, Wittgenstein, not Plato. The modern field of machine learning—of programs that learn through experience—was born.

Yann LeCun's strategy provides a good example of a much more general notion: the exploitation of innate knowledge. Convolutional neural networks learn better and faster than other types of neural networks because they do not learn everything. They incorporate, in their very architecture, a strong hypothesis: what I learn in one place can be generalized everywhere else. The main problem with image recognition is invariance: I have to recognize an object, whatever its position and size, even if it moves to the right or left, farther or closer. It is a challenge, but it is also a very strong constraint: I can expect the very same clues to help me recognize a face anywhere in space. By replicating the same algorithm everywhere, convolutional networks effectively exploit this constraint: they integrate it into their very structure. Innately, prior to any learning, the system already “knows” this key property of the visual world. It does not learn invariance, but assumes it a priori and uses it to reduce the learning space-clever indeed!

One of the most remarkable properties of our brain is its capacity to change and adapt to our individual world. Neurons and neural networks actually make physical changes when stimulated; this is called neuroplasticity. The way they become stimulated is through our particular experiences: The brain changes in a “use dependent” way. The neural networks involved in piano playing, for example, will make changes when activated by a child practicing her piano. These experience-dependent changes translate into better piano playing. This aspect of neuroplasticity—repetition leads to change—is well known and is why practice in sports, arts, and academics can lead to improvement. A key principle of neuroplasticity is specificity. In order to change any part of the brain, that specific part of the brain must be activated. If you want to learn to play the piano, you can’t simply read about piano playing, or watch and listen to YouTube clips of other people playing piano. You must put your hands on the keys and play; you have to stimulate the parts of the brain involved in piano playing in order to change them. This principle of “specificity” applies to all brain-mediated functions, including the capacity to love. If you have never been loved, the neural networks that allow humans to love will be undeveloped, as in Gloria’s case. The good news is that with use, with practice, these capabilities can emerge. Given love, the unloved can become loving.

Our conscious memory is full of gaps, of course, which is actually a good thing. Our brains filter out the ordinary and expected, which is utterly necessary to allow us to function. When you drive, for example, you rely automatically on your previous experiences with cars and roads; if you had to focus on every aspect of what your senses are taking in, you’d be overwhelmed and would probably crash. As you learn anything, in fact, your brain is constantly checking current experience against stored templates—essentially memory—of previous, similar situations and sensations, asking “Is this new?” and “Is this something I need to attend to?” So as you move down the road, your brain’s motor vestibular system is telling you that you are in a certain position. But your brain is probably not making new memories about that. Your brain has stored in it previous sitting experiences in cars, and the pattern of neural activity associated with that doesn’t need to change. There’s nothing new. You’ve been there, done that, it’s familiar. This is also why you can drive over large stretches of familiar highways without remembering almost anything at all that you did during the drive. This is important because all of that previously stored experience has laid down the neural networks, the memory “template,” that you now use to make sense out of any new incoming information. These templates are formed throughout the brain at many different levels, and because information comes in first to the lower, more primitive areas, many are not even accessible to conscious awareness.

While there are more neural connections within a half brain than between the two halves, there are still massive connections across the hemispheres. Even so, cutting those connections does little to one’s sense of conscious experience. That is to say, the left hemisphere keeps on talking and thinking as if nothing had happened even though it no longer has access to half of the human cortex. More important, disconnecting the two half brains instantly creates a second, also independent conscious system. The right brain now purrs along carefree from the left, with its own capacities, desires, goals, insights, and feelings. One network, split into two, becomes two conscious systems. How could one possibly think that consciousness arises from a particular specific network? We need a new idea to cope with this fact.

Here are some practical Dataist guidelines for you: ‘You want to know who you really are?’ asks Dataism. ‘Then forget about mountains and museums. Have you had your DNA sequenced? No?! What are you waiting for? Go and do it today. And convince your grandparents, parents and siblings to have their DNA sequenced too – their data is very valuable for you. And have you heard about these wearable biometric devices that measure your blood pressure and heart rate twenty-four hours a day? Good – so buy one of those, put it on and connect it to your smartphone. And while you are shopping, buy a mobile camera and microphone, record everything you do, and put in online. And allow Google and Facebook to read all your emails, monitor all your chats and messages, and keep a record of all your Likes and clicks. If you do all that, then the great algorithms of the Internet-of-All-Things will tell you whom to marry, which career to pursue and whether to start a war.’ But where do these great algorithms come from? This is the mystery of Dataism. Just as according to Christianity we humans cannot understand God and His plan, so Dataism declares that the human brain cannot fathom the new master algorithms. At present, of course, the algorithms are mostly written by human hackers. Yet the really important algorithms – such as the Google search algorithm – are developed by huge teams. Each member understands just one part of the puzzle, and nobody really understands the algorithm as a whole. Moreover, with the rise of machine learning and artificial neural networks, more and more algorithms evolve independently, improving themselves and learning from their own mistakes. They analyse astronomical amounts of data that no human can possibly encompass, and learn to recognise patterns and adopt strategies that escape the human mind. The seed algorithm may initially be developed by humans, but as it grows it follows its own path, going where no human has gone before – and where no human can follow.

When General Genius built the first mentar [Artificial Intelligence] mind in the last half of the twenty-first century, it based its design on the only proven conscious material then known, namely, our brains. Specifically, the complex structure of our synaptic network. Scientists substituted an electrochemical substrate for our slower, messier biological one. Our brains are an evolutionary hodgepodge of newer structures built on top of more ancient ones, a jury-rigged system that has gotten us this far, despite its inefficiency, but was crying out for a top-to-bottom overhaul. Or so the General genius engineers presumed. One of their chief goals was to make minds as portable as possible, to be easily transferred, stored, and active in multiple media: electronic, chemical, photonic, you name it. Thus there didn't seem to be a need for a mentar body, only for interchangeable containers. They designed the mentar mind to be as fungible as a bank transfer. And so they eliminated our most ancient brain structures for regulating metabolic functions, and they adapted our sensory/motor networks to the control of peripherals. As it turns out, intelligence is not limited to neural networks, Merrill. Indeed, half of human intelligence resides in our bodies outside our skulls. This was intelligence the mentars never inherited from us. ... The genius of the irrational... ... We gave them only rational functions -- the ability to think and feel, but no irrational functions... Have you ever been in a tight situation where you relied on your 'gut instinct'? This is the body's intelligence, not the mind's. Every living cell possesses it. The mentar substrate has no indomitable will to survive, but ours does. Likewise, mentars have no 'fire in the belly,' but we do. They don't experience pure avarice or greed or pride. They're not very curious, or playful, or proud. They lack a sense of wonder and spirit of adventure. They have little initiative. Granted, their cognition is miraculous, but their personalities are rather pedantic. But probably their chief shortcoming is the lack of intuition. Of all the irrational faculties, intuition in the most powerful. Some say intuition transcends space-time. Have you ever heard of a mentar having a lucky hunch? They can bring incredible amounts of cognitive and computational power to bear on a seemingly intractable problem, only to see a dumb human with a lucky hunch walk away with the prize every time. Then there's luck itself. Some people have it, most don't, and no mentar does. So this makes them want our bodies... Our bodies, ape bodies, dog bodies, jellyfish bodies. They've tried them all. Every cell knows some neat tricks or survival, but the problem with cellular knowledge is that it's not at all fungible; nor are our memories. We're pretty much trapped in our containers.