Serendipity Seraph and Arisia Vita at my Future Day Lecture.

Serendipity Seraph and Arisia Vita at my Future Day Lecture.

Extropia DaSilva: Ok..welcome to my Future Day lecture!
[2013/03/01 15:34]  Lulu Lacrima: /me doesn’t see seren
[2013/03/01 15:35]  Seren (serendipity.seraph): oh please, make yourself comfy
[2013/03/01 15:35]  Extropia DaSilva: feel free to comment at any time, but I shall not respond to comments as I have a lot to get through.
[2013/03/01 15:35]  Extropia DaSilva: so..
[2013/03/01 15:35]  Extropia DaSilva: the topic of this lecture is..
[2013/03/01 15:35]  Extropia DaSilva: IT’S ALIVE! HOW TECHNOLOGY EVOLVES AND WHAT IT MEANS.
[2013/03/01 15:36]  Extropia DaSilva: The search for a workable theory of technological evolution is almost as old as the theory of natural selection itself, and the belief that inanimate matter can have lifelike abilities attributed to it is as old as mythology. Think of the gollem from Hebrew legend, or Poseidon the Greek god of the sea. Just four years after Darwin had published ‘On The Origin Of Species’, Samuel Butler was calling for a theory of evolution for machines. Most attempts at such a theory have tried to frame it in terms of the steady accumulation of changes, recognisable as Darwinian.
[2013/03/01 15:36]  Extropia DaSilva: ..
[2013/03/01 15:36]  Extropia DaSilva: But natural selection has certain constraints which make it quite incapable of explaining certain technologies. The first constraint is that a new species can only be created through incremental steps. This is problematic, because no amount of steady accumulations could ever transform a piston engine into a jet engine, nor could a candle evolve into a light bulb. Another constraint is that every incremental step must produce something viable. Inventors, though, are quite capable of creating machines that have irreducible
[2013/03/01 15:37]  Extropia DaSilva: ..
[2013/03/01 15:37]  Extropia DaSilva: complexity, meaning an organization of parts, the loss of any one of which is fatal to the whole. They can do this because human inventors have some degree of foresight and can see how a component that has no use by itself may become useful when part of a complex organization of other parts. Nature, by contrast, is a ‘blind watchmaker’ with no capacity for foresight.
[2013/03/01 15:37]  Extropia DaSilva: ..
[2013/03/01 15:37]  Seren (serendipity.seraph): if anything was ever a case for intelligent design..
[2013/03/01 15:38]  Lulu Lacrima: no foresight=intelligent?
[2013/03/01 15:38]  Extropia DaSilva: So where does that leave us in the search for an evolutionary theory for machines? It certainly does not mean there is no such thing, only that Darwinian selection is not always applicable. How, then, can we explain the appearance of radically new technologies that cannot have come about through the steady accumulation of changes to existing technologies?
[2013/03/01 15:38]  Seren (serendipity.seraph): technology <- intelligent design plus not on purpose “stuff”
[2013/03/01 15:38]  Extropia DaSilva: Judged from outward appearances, some machines appear quite unrelated to anything else. But then, the same thing could be said of life. From outward appearances, one would see no relation between a wolf and a dolphin, or a bat and a mushroom. It was only through studies of animal anatomy, comparisons of the skeletal structures of fossilized remains, and how embryos develop that a common ancestry was suspected and later, with the ability to map and compare genes, confirmed.
[2013/03/01 15:39]  Extropia DaSilva: Similarly we have to consider technology in its entirety- not just physical inventions but all processes, devices, modules, methods and algorithms that ever existed- in order to see a kind of evolution at work.
 When we do that, we discover that the cartoon cliché of some light bulb flashing over a genius’s head as a great idea comes from nowhere is quite wrong. The history of technology is by no means one of more-or-less independent discoveries. This is because any new technology can only come about by using components and methods that already exist. A jet engine, for example, is created by combining compressors, turbines and combustion systems, all of which pre-existed in other technologies.
[2013/03/01 15:39]  Extropia DaSilva: ..
[2013/03/01 15:40]  Extropia DaSilva: W. Brian Arthur, who is a professor at the Santa Fe Institute, calls this ‘Combinatorial Evolution’. Any and all novel technologies are created through combinations of existing technologies. Some combinations prove useful, and so they persist and spread around the world, becoming potential building blocks for further technologies. Or, a time may come when they are clearly surpassed by other technologies and so they go extinct. Also, there are many possible combinations that make little sense, and they too become nothing.
[2013/03/01 15:40]  Seren (serendipity.seraph): well the cartoon isn’t meant to say it comes from literally nowhere..
[2013/03/01 15:40]  Extropia DaSilva: Combinatorial evolution is observed in the natural world from time to time. The most obvious example would be multicellular organisms, which evolved from combinations of single-celled organisms. Clearly, though, evolution through variation and selection is the norm in the natural world. We see the opposite in the technological world. Here, combinations are the norm and while Darwinian variation and selection also plays a role, it follows behind combinatorial evolution, working on structures already formed.
[2013/03/01 15:41]  Extropia DaSilva: ..
[2013/03/01 15:41]  Extropia DaSilva: When technology and all its related practices are considered in their entirety, it becomes apparent that every invention stands upon a pyramid of others that made it possible. All future technologies will derive from those that exist today, because these are the building blocks that will be combined to make further technologies that will go on to become potential building blocks, and so on in an accumulation of useful combinations.
[2013/03/01 15:42]  Seren (serendipity.seraph): I disagree. should I hold it until later?
[2013/03/01 15:42]  Extropia DaSilva: But what about the base of the pyramid? If the technologies of today came about through combinations of yesterday’s technology, where did those building blocks come from? Technologies that existed in even earlier times, of course. But this is starting to sound like a problem of infinite regress. Where does it all end?
[2013/03/01 15:42]  Lulu Lacrima: variation is not Darwinian; it just is; and from this (random) variation natural selection emerges
[2013/03/01 15:42]  Extropia DaSilva: (no fore away(
[2013/03/01 15:42]  Extropia DaSilva: (I mean, fire away)
[2013/03/01 15:42]  Extropia DaSilva: ..
[2013/03/01 15:42]  Seren (serendipity.seraph): *grins*
[2013/03/01 15:42]  Extropia DaSilva: The reason any technology ultimately works at all is because it successfully taps into some kind of natural phenomena. The jet engine works thanks to the law that every action has an equal and opposite reaction. The light bulb exploits electromagnetism. Essentially, technology is a programming of nature. Tracing the evolutionary pyramid of technology therefore takes us back to the earliest natural phenomenon that humans captured.
[2013/03/01 15:43]  Seren (serendipity.seraph): the difference is that there is ID in technology by definition
[2013/03/01 15:43]  Extropia DaSilva: So, the history of technology is an evolutionary story of related devices, methods, and exploitations of natural phenomena. It results from people taking what is known at the time, plus a modicum of inspiration, and then combining bits and pieces that already exist in just the right way in order to link some need with some effect or effects that can fulfil it.
[2013/03/01 15:43]  Lulu Lacrima: sounds like pop music 😉
[2013/03/01 15:43]  Seren (serendipity.seraph): it is not just variation by running a genetic algorithm on some fitness function
[2013/03/01 15:43]  Extropia DaSilva: But, in what sense can technology be said to be alive? As yet, no formal definition of life exists. The best we can do is judge whether or not any system meets certain criteria, namely reproduction, growth, and response and adaptation to the environment. Technology does indeed meet all these requirements, but of course, so far it has required human agency for its buildout and reproduction. It is therefore alive, but only in the sense that a coral reef (built from the activities of small organisms) can be said to be a living thing.
[2013/03/01 15:44]  Extropia DaSilva: …
[2013/03/01 15:44]  Extropia DaSilva: Richard Dawkins once observed, “genetics today is pure information technology. This, precisely, is why an antifreeze gene can be copied from an arctic fish and pasted into a tomato”. Because life is fundamentally an information technology (in other words, something that operates on the basis of coded instructions) it can be translated into languages understandable to computers, which operate according to the same principles. Another point to consider is that evolution is basically an algorithm, a repeatable procedure, and our understanding of that algorithm has revealed core principles that apply to any adaptive system. They are:
[2013/03/01 15:45]  Seren (serendipity.seraph): It does not. It does not reproduce. It does not grow. not naturally and in and of itself at least.
[2013/03/01 15:45]  Extropia DaSilva: (Nor do men, they require handy mobile reproduction factories aka wombs, carried in women, to reproduce)
[2013/03/01 15:46]  Extropia DaSilva: RECOMBINATION: The driving force of innovation, not to mention of technological evolution itself.
 AGENTS: Decision-making units, following rules that determine their choices. Cells are biological agents following chemical rules, trading programs are agents following rules in a financial market.
 SELF-ORGANIZATION: The ability to organize autonomously to create something more complex. As we have already seen, the only way to have something more complex than a single agent, is by connecting multiple agents.
[2013/03/01 15:46]  Seren (serendipity.seraph): not at all the same thing. living things have their ability to reproduce in their own nature.
[2013/03/01 15:46]  Lulu Lacrima: I think “alive” requires a metaphysical level of definition that cannot (perhaps as of yet) be reproduced by humans
[2013/03/01 15:46]  Extropia DaSilva: SELECTIVE PRESSURE: If the process is to generally move towards improvement, there has to be some method for determining which agents get the opportunity to recombine in the next generation. Where technology is concerned, the market provides that selective pressure. Our purchasing decisions ultimately decide what has survivability, and what does not.
 ADAPTATION: Fitness landscapes are not static. They change shape with each round of evolution, as new competitors emerge forcing rivals to adapt to the new threat.
[2013/03/01 15:47]  Lulu Lacrima: the process of evolution has no intent
[2013/03/01 15:47]  Lulu Lacrima: humans do
[2013/03/01 15:47]  Extropia DaSilva: CO-EVOLUTION: Because rivals must continually adapt to one another, they affect the evolution of industry (or the ecology) as a whole.
 EMERGENCE: Certain behaviours that the system itself exhibits are not to be found in any of the parts. Instead, complex global phenomena arises from simple local processes and local interaction rules. No central control over the entire thing is necessary. Indeed, such top-down governance would screw things up.
[2013/03/01 15:47]  Seren (serendipity.seraph): So there is no inbuilt fitness function. A difference. The same difference as the obvious intelligent design external to the tech itself.
[2013/03/01 15:47]  Extropia DaSilva: ..
[2013/03/01 15:47]  Extropia DaSilva: Because these core principles apply to any adaptive system, we can swap between domains and see nature in terms of mechanism; the economy as an organism. Biology, information, technology and business are likely to converge on general evolution, as the theories which drive biology are adapted in the way we manage our enterprises. Christopher Meyer and Stan Davies, who both work at the Centre For Business Innovation, coined the phrase “Code Is Code”, explaining:
[2013/03/01 15:48]  Extropia DaSilva: ..
[2013/03/01 15:48]  Extropia DaSilva: “you can translate biology into information, and information into biology because both operate on the basis of coded instructions, and those codes are translatable. When you get down to it, code is simply code”.
[2013/03/01 15:49]  Extropia DaSilva: ..
[2013/03/01 15:49]  Extropia DaSilva: Our most complex technologies have reached a point where we must look to the principles of nature to make or govern them. There is a kind of myth that has grown up around computers, one whose origin can be traced to a comment made by Ada Lovelace, the first programmer. She said:
 “The Analytical Engine has no pretensions to originate anything. It can do whatever we know how to order it to perform”. Most people recognise this in the form expressed by IBM’s marketing department:
 “Computers can only do what their programs specify”.
[2013/03/01 15:49]  Seren (serendipity.seraph): an adaptive system is not necessarilly one that evolves
[2013/03/01 15:49]  Extropia DaSilva: ..
[2013/03/01 15:49]  Extropia DaSilva: If they have no pretensions to originate anything, there can never be such a thing as artificial intelligence, because it is always the programmers themselves (never the programs) that are intelligent. But is it true?
[2013/03/01 15:49]  Lulu Lacrima: the theories are adaptable (no pun intended) not b/c the process of natural selection can be generalized to nonliving entities, but b/c “evolution” suits a metaphorical paradigm to explain changeability in other, nonliving systems
[2013/03/01 15:50]  Extropia DaSilva: The way computers have been designed has, itself, evolved over time. This evolution was enabled and made necessary by certain developments triggered by previous rounds of computing technology.
[2013/03/01 15:50]  Seren (serendipity.seraph): that you can someday may a program refine and program itself in no wise says this is an inherent characteristic of all technology though
[2013/03/01 15:50]  Extropia DaSilva: …
[2013/03/01 15:50]  Extropia DaSilva: After the 1960s, the number of components on a chip had risen by a factor of a million, while the manufacturing cost per transistor had fallen to mere pennies. This had the effect of making computer circuitry designed step-by-step by draughtsmen an uneconomical prospect. As nanotech pioneer Eric Drexler explained:
[2013/03/01 15:50]  Seren (serendipity.seraph): *make a
[2013/03/01 15:50]  Extropia DaSilva: “If a million transistor design has an expected market of 100,000 units, then every dollar of design cost per transistor adds tens of dollars to the price of each chip. Yet, a dollar can’t buy much time from a human design team”.
[2013/03/01 15:51]  Extropia DaSilva: ..
[2013/03/01 15:51]  Extropia DaSilva: This lead to the invention of ‘silicon compilers’, software systems capable of producing a chip- ready to manufacture- with very little human help beyond specifying the chip’s function. Having gained a foothold, silicon compilers gradually improved, and the result of this is that human programmers have had to work at increasing levels of abstraction, entrusting ever-larger details to computer search and pre-programmed expertise. Programs consisting of hundreds of instructions might be completely understood by their designers, but modern software is built from millions of instructions and we have learned to expect the unexpected.
[2013/03/01 15:52]  Seren (serendipity.seraph): there is a difference between automating work and having the technology spontaneously do the work and think of other kinds of work to do. The line can get murky though
[2013/03/01 15:52]  Extropia DaSilva: Since the 1980s, another automated design process (one with obvious parallels to the natural world) emerged. This is known as ‘evolutionary algorithms’ (EA). An EA takes two parent designs and blends components of each to produce multiple offspring. Each offspring combines the features of its parents in different ways. The EA then selects which offspring it considers worth re-breeding, and they are replicated with occasional mutations (which involves changing a 1 to a 0 here, a 0 to a 1 there) resulting in variation in the next generation. The fittest of that generation is then selected, and so it goes on. As the random mutations and non-random selection process continues for thousands of generations, useful features accumulate in the same design.
[2013/03/01 15:52]  Seren (serendipity.seraph): EA is purpose built to refine/create designs by evolving them, yes.
[2013/03/01 15:52]  Extropia DaSilva: Whereas a human designer does not have time to test all possible combinations, an EA comes closer to doing so, thanks to the sheer speed with which computers can explore mathematical space. However, so far their use has been limited to a few niche applications, because the need to breed and evaluate thousands of generations requires ultra-fast computers. But now, thanks to the emergence of multicore chips that make it easy to divide tasks between cores (something that suits EAs) that is changing. EA pioneer John Koza explained:
[2013/03/01 15:52]  Lulu Lacrima: excellent example of “evolution” as a term to describe the mutability of a nonliving system, being conflated with the process of natural selection
[2013/03/01 15:53]  Extropia DaSilva: ..
[2013/03/01 15:53]  Extropia DaSilva: “We can now undertake evolutionary problems that were once too complicated or time-consuming. Things we couldn’t do in the past, because it would have taken two months to run the genetic program, are now possible in days or less”.
[2013/03/01 15:53]  Seren (serendipity.seraph): the problems EA can be used for are pretty small and constrained due to the brute force combinatorial explosion involved.
[2013/03/01 15:53]  Extropia DaSilva: ..
[2013/03/01 15:53]  Extropia DaSilva: Systems such as these can employ vast quantities of data, more than enough to be overwhelming to humans. While each procedure may be simple by itself, they may be linked in ways that make the overall result complex and surprising. Many thousands of rules can be incorporated, as opposed to the small number that are in diagrams and equations that humans use.
[2013/03/01 15:54]  Extropia DaSilva: ..
[2013/03/01 15:54]  Extropia DaSilva: But, we pay a price for this, because the code that results from this evolutionary process is so different from conventional code that programmers find it impossible to follow. The complexity is beyond human capability to design or debug. This is something unprecedented in the scientific era of invention. While the layperson may use technology without understanding it, we at least expect the professional to have complete knowledge of how their designs function. No longer. Our most complex technologies are no longer designed and built. They are grown and trained, and have to be studied as we now study nature: by probing and experimenting.
[2013/03/01 15:55]  Seren (serendipity.seraph): we generally do not evolve code except for pretty small things.
[2013/03/01 15:55]  Extropia DaSilva: ..
[2013/03/01 15:55]  Extropia DaSilva: The two trends of the falling cost of transistors and increasing numbers of components on a chip, combine to drive Moore’s Law. This can either be expressed as:
 A fixed amount of money buys twice the computing power every 18-24 months. Or:
 A fixed amount of computing power will cost half as much every 18-24 months.
[2013/03/01 15:55]  Lulu Lacrima: I disagree with the amount of data that can be managed by humans; perhaps only those data which humans can consciously monitor, but in terms of sheer quantity & levels of processing, our bodies & brains handle more data than one could even think of inputting into any other system
[2013/03/01 15:55]  Lulu Lacrima: currently
[2013/03/01 15:55]  Seren (serendipity.seraph): this is not true. Our most complex technologies are not grown and trained as a rule.
[2013/03/01 15:55]  Extropia DaSilva: ..
[2013/03/01 15:55]  Extropia DaSilva: The first tells us that, as calculations beyond the capabilities of today’s computers become possible with tomorrow’s, we can simulate things which once could only be investigated with practical experiments. For instance, we now have enough computational power to model turbulance and airflow, and as a result companies like NASA Ames no longer use wind-tunnels to test out aerodynamic designs. Airplanes can be reliably tested as virtual models. Also, we have sophisticated models of metabolic, immune, nervous and circulatory systems as well as structural models of the heart and other muscles. As computing power increases (along with our understanding of biology) these models will increase in fidelity and eventually we will see the integration of all the subsystem models into one systematic model. The era of animal experiments will then be made obsolete by the era of the biologically-accurate virtual human.
[2013/03/01 15:56]  Extropia DaSilva: ..
[2013/03/01 15:56]  Extropia DaSilva: The second way of expressing Moore’s Law tells us that today’s expensive, high-end computer is tomorrow’s cheap item. Power that only $2000 could buy will, in ten year’s time, be available for $31.25, and the cost keeps falling. A time comes when computing power that was once available only on the most expensive desktops effectively disappears into cell-phones, credit cards, all manner of things. What is more, nobody notices it much, simply because it has become so unremarkable by now.
[2013/03/01 15:56]  Lulu Lacrima: computational models of the nervous system are, while much more sophisticated than ever before, cannot approach the capabilities of the human brain
[2013/03/01 15:57]  Lulu Lacrima: I don’t believe such complexity can be achieved in as many as 100 years
[2013/03/01 15:57]  Lulu Lacrima: although I don’t believe it to be impossible
[2013/03/01 15:57]  Extropia DaSilva: ..
[2013/03/01 15:57]  Extropia DaSilva: But, think about what it means. As the trend progresses, it becomes possible to integrate more and more computers and sensors into more and more objects. Also, the first way of expressing Moore’s Law tells us that, over time, sensors will be able to capture new kinds of data, more accurately, using less space and energy. We have already deployed tens of thousands of sensors of many types, gathering information ranging from the location of vehicles, to potential chemical or radioactive leaks, to migratory patterns of animals, and even a person‘s emotional state. Thanks to wireless networks and telecommunication, the newly-sensed data is available anywhere in realtime, and can be combined in almost limitless ways to produce new products and services.
[2013/03/01 15:57]  Seren (serendipity.seraph): the improvements in algorithms have nearly swamped improvements from Moore’s Law in some cases.
[2013/03/01 15:58]  Extropia DaSilva: ..
[2013/03/01 15:58]  Extropia DaSilva: Information has become codified and information technology modularized, and because of this we can install upgrades and add-ons and plug-ins much more quickly. Just think how much time and expertise it takes to add a turbo-charger to a car, versus adding a new graphics card to your computer. As for software upgrades, they can happen automatically, without you needing to be aware it is happening. This all allows innovation to spread faster than ever before. In relatively short order, our business and social lives have been restructured to be totally dependent on powerful computation and telecommunication networks.
 But, as any network becomes more intensely connected, it starts to become ‘nonlinear’. Small changes can lead to large effects. Because a signal created in any market, society or system can travel further than ever before, our world is one of increasing volatility.
[2013/03/01 15:58]  Lulu Lacrima: all biological models fail to capture the metaphysical aspect of that which constitutes “living”–it’s a gestalt, and yes, emergent process
[2013/03/01 15:58]  Extropia DaSilva: ..
[2013/03/01 15:58]  Extropia DaSilva: In order to get the best out of systems of self-organized behaviour, leaders will need to establish guidelines and constraints that govern independent actions. Corporate behaviour will need to be unpacked into rules that drive the choices individuals make, in order to affect that larger structures that emerge. Therefore, it will be a priority to create the connected capabilities that enable cooperation and autonomous action.
[2013/03/01 15:59]  Seren (serendipity.seraph): my primary is a hacker well aware of both improvements and gotchas in software technology and data handling.
[2013/03/01 15:59]  Extropia DaSilva: ..
[2013/03/01 15:59]  Extropia DaSilva: Davis and Meyer came up with principles that they reckon will be fundamental to corporate behaviour in the years ahead. These are “Seed, Select, Amplify’, “Sense and Respond” and “Learn and Adapt”.
 Because almost any kind of business can now use simulation to experiment with, the cost of testing has fallen dramatically. A “seed” is an idea, something with potential value. A company should seek to produce as many seeds as it can afford to, and test them for potential value across diverse economic opportunities. There must, of course, be a way to weed out inferior ideas, freeing up resources to spread good seeds (“select” and “amplify”) and that is where “Sense and Respond” comes in.
[2013/03/01 15:59]  Seren (serendipity.seraph): what leader? thouse outside the tech sphere have not a clue
[2013/03/01 16:00]  Extropia DaSilva: As we have seen, the increasing capability and falling cost of networked sensors and microprocessors is approaching a point where we can imbue products with qualities vital to anything alive. That is, the ability to sense environmental changes and respond appropriately to them. Information from every stage in the consumer-item relationship will one day be gathered by software that can learn from what it senses, adapting the system to make it better. Davis and Meyer wrote:
[2013/03/01 16:00]  Seren (serendipity.seraph): simulation is not evolution and most simulation is not hooked to an EA
[2013/03/01 16:00]  Lulu Lacrima: again, learning itself is an emergent process; how can one program insight, for example?
[2013/03/01 16:00]  Seren (serendipity.seraph): and most business processes and software process cannot be handled by EA, at least not in its current form
[2013/03/01 16:00]  Extropia DaSilva: ..
[2013/03/01 16:00]  Extropia DaSilva: “As our enterprises become chiefly composed of coded messages connecting human and software agents, the concepts of evolution become more central to their behaviour. Information will move to a framework of biology, as autonomous software and increasing connectivity make networked systems behave as if alive”.
[2013/03/01 16:01]  Extropia DaSilva: ..
[2013/03/01 16:01]  Extropia DaSilva: Indeed, this shift from a top-down, clockwork like view of technology to a bottom-up organic one, can clearly be seen in terms such as “artificial evolution”, “genetic algorithms”, “emergence”, “viral marketing”, “neural networks” and other kinds of software challenges related to growing complex systems. As we strive to create technologies and organizations that adapt continually and rapidly in order to keep pace with shifts in their market; as technology is organized into networks of systems that sense, respond, and configure themselves in appropriate ways, will “it’s alive” become more than mere metaphor?
[2013/03/01 16:02]  Lulu Lacrima: the integration of soft- and hardware devices with the chemoelectrical force of the brain is another story
[2013/03/01 16:02]  Extropia DaSilva: ..
[2013/03/01 16:02]  Extropia DaSilva: Much of what has been discussed so far can be attributed to two digital revolutions. In the 40s, telephone calls got worse with distance, a problem that was fixed by Claude Shannon when he digitized communication. Von Neumann did likewise for computers. So, what is the third digital revolution?
[2013/03/01 16:02]  Extropia DaSilva: ..
[2013/03/01 16:02]  Extropia DaSilva: We have seen that technological evolution is fundamentally driven by the capturing of natural phenomena, and that this leads to the development of instruments that allow for increasingly fine observations and manipulations of natural phenomena. Chemists would welcome instruments that would enable them to measure and modify molecules so that they might study their structures, behaviours and interactions. Materials science would welcome technology that allowed them to be more systematic and thorough, building new materials according to plan and allowing one laboratory to make more new materials in a day, than all of today’s materials scientists put together. Biologists would welcome technology that lets them map cells completely and study their interactions in detail.
 Can we identify a technological capability that would be able to fulfil all of the wishes listed above?
[2013/03/01 16:03]  Extropia DaSilva: ..
[2013/03/01 16:03]  Extropia DaSilva: Indeed we can. If you follow Moore’s Law into the future, you can see that computers will one day have switches that are molecular in size and connected in complex three-dimensional patterns. Bill Degrado, who is a protein chemist at Du Pont, said:
[2013/03/01 16:03]  Extropia DaSilva: ..
[2013/03/01 16:03]  Extropia DaSilva: “People have worked for years making things smaller and smaller until we’re approaching molecular dimensions. At that point, one can’t make smaller things, except by starting with molecules and building them up into assemblies”.
[2013/03/01 16:04]  Extropia DaSilva: …
[2013/03/01 16:04]  Extropia DaSilva: Computers contain fast-cycling parts that make complex patterns from the building blocks of information (binary digits), and the third digital revolution will result from machines that contain fast-cycling parts that can make complex patterns from the building blocks of matter (the elements of the periodic table).
[2013/03/01 16:04]  Seren (serendipity.seraph): I don’t agree it is fundamentally driven by capturing natural phenomenon. Understand and manipulate yes.
[2013/03/01 16:04]  Lulu Lacrima: /me nods with Seren
[2013/03/01 16:04]  Lulu Lacrima: b/c who does the capturing?
[2013/03/01 16:04]  Extropia DaSilva: How can you not agree?
[2013/03/01 16:05]  Extropia DaSilva: This is in marked contrast to most manufacturing today, which is almost entirely analogue in its nature. We take a batch of materials and chop them, bake them, melt them, mix them, in order to arrive at a final product. It takes a lot of raw material in order to make something like a car, which is why quarries look like such scars on the landscape. Natural things, on the other hand, get built in a fundamentally different way. Tiny biological machines called rhybosomes build things under digital control.
[2013/03/01 16:05]  Seren (serendipity.seraph): molecural nanotech. before that we have 3D chips
[2013/03/01 16:05]  Lulu Lacrima: in the long run, it is we humans who do so, whether by initiating the process, or by deciding what is to be captured
[2013/03/01 16:05]  Seren (serendipity.seraph): because of emphasis which I think may slant it a bit wrong.
[2013/03/01 16:05]  Extropia DaSilva: ..
[2013/03/01 16:05]  Extropia DaSilva: No wonder, then, that one of the main contenders for the post-silicon paradigm is molecular electronics, which promises to dramatically extend the power of IT. To get an idea of how powerful molecular computing could be, consider that a single drop of water contains more molecules than all transistors ever built. This is partly because the molecules are tiny, even by the standards of modern computer components, but mostly because they are organized into three-dimensional patterns. Every IC, in contrast, is a thin two-dimensional layer of computation on a thick and inert substrate.
[2013/03/01 16:06]  Seren (serendipity.seraph): but some day AIs will do all we do and more, Lulu
[2013/03/01 16:06]  Lulu Lacrima: and therefore, all such captures eliminate sources of variation, required by natural selection for evolution to truly work, that might exist beyond the capacity of humans to conceive
[2013/03/01 16:06]  Extropia DaSilva: ..
[2013/03/01 16:06]  Extropia DaSilva: Now consider that the company Zettacore, who build molecular memories from porphyin molecules that self-assemble on exposed sillicon, have already demonstrated up to eight stable digital states per molecule.
 In short, molecular electronics might one day deliver sugar-cube sized devices with more processing power than all of today’s computers combined, or super computers the size of viruses. That, however, is not the most exciting prospect of molecular manufacturing. As Neil Gershenfeld said:
[2013/03/01 16:06]  Lulu Lacrima: I don’t disagree with you, Seren, I just don’t believe we’re nearly as close as we’d like to be
[2013/03/01 16:07]  Extropia DaSilva: ..
[2013/03/01 16:07]  Extropia DaSilva: “It’s not when a program describes a thing, it’s when a program becomes a thing that we bring the programmability of the digital world to the physical world”.
[2013/03/01 16:07]  Extropia DaSilva: …
[2013/03/01 16:07]  Seren (serendipity.seraph): I have heard some lab got 11 distinguishable states – for a single electron!
[2013/03/01 16:07]  Extropia DaSilva: So, what we are talking about here is the reimplementation of all molecular biology in engineered materials to code construction. We are looking to create the ability to take a description of an object, and then have it self-assemble from molecular or atomic building blocks. We are talking about machines with the capability to self-repair, and even self-replicate. But, what about machines with cognition?
[2013/03/01 16:07]  Extropia DaSilva: (WOW!)
[2013/03/01 16:08]  Extropia DaSilva: ..
[2013/03/01 16:08]  Extropia DaSilva: Electrical engineers who wish to reverse-engineer a rival’s computer chip do so by placing precise sensors at specific points in the circuitry. This enables them to follow the actual information being transformed in real time, thereby creating a detailed description of how the circuits actually work.
[2013/03/01 16:08]  Lulu Lacrima: and so we have a circular definition: that which is alive is that “program which becomes a thing,” which is essentially the product of something which was alive
[2013/03/01 16:08]  Seren (serendipity.seraph): the world is becoming more intelligent and programmable – no question
[2013/03/01 16:08]  Extropia DaSilva: ..
[2013/03/01 16:08]  Extropia DaSilva: Molecular nanotechnology would enable us to do the same thing with living brains, and indeed we are using our increasingly accurate and refined sensor technologies (along with ever more powerful computers) to do just that, developing techniques such as marking specific cells in lab animals by genetically engineering the organisms to incorporate fluorescent proteins found in marine species, thereby enabling researchers to monitor biochemical reactions and track the movements of cellular proteins in real time, to diffusion tensor imaging, a technique that infers the location of nerve fibers by tracking water molecules in the brain as they move along them.
[2013/03/01 16:09]  Seren (serendipity.seraph): actually that sort of reverse engineering is very very difficult.
[2013/03/01 16:09]  Extropia DaSilva: ..
[2013/03/01 16:09]  Extropia DaSilva: In other words, our technologies are now beginning to sense the natural phenomena responsible for the design and function of the human brain. Neuroscientist Lloyd Watts pointed out that:
 “Scientific advances are enabled by a technology advance that allows us to see what we have not been able to see before…we collectively know enough about our own brains, and have developed such advanced computing technology, that we can now seriously undertake the construction of a verifiable, real-time, high-resolution model of significant parts of our intelligence”.
[2013/03/01 16:09]  Seren (serendipity.seraph): you can get an IO mapping without having much clue as to precise functions that produced it or their arrangement.
[2013/03/01 16:10]  Lulu Lacrima: deconstructing the brain, as in reverse engineering, does not reveal the aspects of the entire functioning of that brain which constitute cognition, consciousness, awareness, & intelligence
[2013/03/01 16:10]  Extropia DaSilva: IBM’s Blue Brain project has so far succeeded in reverse-engineering the cortical column, which can be thought of as the basic microprocessor, the building block from which the neocortex is made. Many other areas of R+D in bio, neuro and computer sciences are also following paths to complete the reverse-engineering of the human brain, for reasons that range from treating neurological disorders, to eliminating the need for animal experiments, to nothing more than the urge to understand how the mind works.
[2013/03/01 16:10]  Extropia DaSilva: ..
[2013/03/01 16:10]  Seren (serendipity.seraph): and trying to be exhaustive across an unknown domain at the bit level doesn’t tell you what a bit pattern means to those unknown functions.
[2013/03/01 16:10]  Extropia DaSilva: …
[2013/03/01 16:10]  Extropia DaSilva: But, if it is indeed true that the brain IS the mind, and it becomes possible to build brains or, rather, to have machines which can self-assemble a body and a brain to control it, do we then have machines who think? Who feel? Who create? Would this lead to technology conceiving of, designing, and manufacturing its own next-generation? If so, how might the human/machine relationship be affected? In pondering questions like these, Carl Zimmer came up with the following:
[2013/03/01 16:11]  Seren (serendipity.seraph): no it has not. Humans reverse engineered it and built their understanding as Blue Brain
[2013/03/01 16:11]  Extropia DaSilva: ..
[2013/03/01 16:11]  Lulu Lacrima: what if the mind IS the brain?
[2013/03/01 16:11]  Extropia DaSilva: “The Web is encircling the Earth, subsuming not only computers but cars and cash registers and televisions. We have surrounded ourselves with a global brain, which taps into our own brains, an intellectual forest dependent on a hidden fungal network”.
[2013/03/01 16:12]  Extropia DaSilva: …
[2013/03/01 16:12]  Extropia DaSilva: Whether something appears to be a single entity or a collection of individuals, often depends on your perspective. On a molecular scale, a single cell is a collection of chemicals and molecules. On the macro scale, a vast number of different cell types appears as a single animal. Maybe it is the case that, seen from the perspective of space, our planet seems less like a vast number of people and technologies, and more like a single entity slowly teasing apart the laws of nature? It is as if, in at least one tiny corner of the cosmos, the Universe is organizing itself into patterns of matter/energy that pursue the directive, Temet Nosce- ‘Know Thyself’.
[2013/03/01 16:12]  Seren (serendipity.seraph): I think it is much easier to get to true AGI than emulating the human brain
[2013/03/01 16:12]  Extropia DaSilva: phew!
[2013/03/01 16:12]  Extropia DaSilva: Done!
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