David Chalmers on the technological singularity [podcast]

Check out this excellent Philosophy Bites podcast featuring David Chalmers who is asked about the technological singularity, whole brain emulation, uploads, and the possibility that the Universe is a kind of simulation.

Carboncopies: "Realistic routes to substrate independent minds"

Check these guys out: Carboncopies. Operating under the tagline, "Realistic routes to substrate independent minds," they are a nonprofit organisation with the goal of creating a networking and outreach community around the central idea of Advancing Substrate Independent Minds (ASIM). This is a field of research which seeks to "understand the brain and nervous system of a wide range of organisms, including humans, in order to facilitate emulation of these organisms in an artificial substrate, for example a computer processor."

Why is such an organization required. According to their site:

In order for progress to be made in the field of ASIM, advancements in many key technologies and research areas are required. These include: 

Nanotechnology, biotechnology, brain imaging, neuroscience, artificial intelligence, computational hardware and architectures, cognitive psychology and philosophy.

ASIM sits at the confluence of many subjects, and cross-disciplinary research is a necessity. However, it can be difficult to manage and organise ideas from many different fields of expertise. ASIM offers tantalizing possibilities, but they need to be understood and pursued in a structured fashion.

Carboncopies will help by offering a networking platform and hub around which experts in the individual fields relevant to ASIM can gather and exchange ideas. It will also promote these ideas and explain the motivation behind ASIM to a wider audience. 

To this end, Carboncopies organises workshops and conferences where interested parties can exchange ideas, network with others, and keep updated on the latest developments in the field. They're also gather up-to-date literature and news relevant to the ASIM community.

David Chalmers: Consciousness is not substrate dependent

A popular argument against uploads and whole brain emulation is that consciousness is somehow rooted in the physical, biological realm. Back in 1995, philosopher David Chalmers addressed this problem in his seminal paper, "Absent Qualia, Fading Qualia, Dancing Qualia." His abstract reads,

It is widely accepted that conscious experience has a physical basis. That is, the properties of experience (phenomenal properties, or qualia) systematically depend on physical properties according to some lawful relation. There are two key questions about this relation. The first concerns the strength of the laws: are they logically or metaphysically necessary, so that consciousness is nothing "over and above" the underlying physical process, or are they merely contingent laws like the law of gravity? This question about the strength of the psychophysical link is the basis for debates over physicalism and property dualism. The second question concerns the shape of the laws: precisely how do phenomenal properties depend on physical properties? What sort of physical properties enter into the laws' antecedents, for instance; consequently, what sort of physical systems can give rise to conscious experience? It is this second question that I address in this paper.

Chalmers sets up a series of arguments and thought experiments which point to the conclusion that functional organization suffices for conscious experience, what he calls nonreductive functionalism. He argues that conscious experience is determined by functional organization without necessarily being reducible to functional organization. This bodes well for the AI and whole brain emulation camp.

Chalmers concludes:

In any case, the conclusion is a strong one. It tells us that systems that duplicate our functional organization will be conscious even if they are made of silicon, constructed out of water-pipes, or instantiated in an entire population. The arguments in this paper can thus be seen as offering support to some of the ambitions of artificial intelligence. The arguments also make progress in constraining the principles in virtue of which consciousness depends on the physical. If successful, they show that biochemical and other non-organizational properties are at best indirectly relevant to the instantiation of experience, relevant only insofar as they play a role in determining functional organization.

Of course, the principle of organizational invariance is not the last word in constructing a theory of conscious experience. There are many unanswered questions: we would like to know just what sort of organization gives rise to experience, and what sort of experience we should expect a given organization to give rise to. Further, the principle is not cast at the right level to be a truly fundamental theory of consciousness; eventually, we would like to construct a fundamental theory that has the principle as a consequence. In the meantime, the principle acts as a strong constraint on an ultimate theory.

Entire paper.

Making brains: Reverse engineering the human brain to achieve AI

The ongoing debate between PZ Myers and Ray Kurzweil about reverse engineering the human brain is fairly representative of the same debate that's been going in futurist circles for quite some time now. And as the Myers/Kurzweil conversation attests, there is little consensus on the best way for us to achieve human-equivalent AI.

That said, I have noticed an increasing interest in the whole brain emulation (WBE) approach. Kurzweil's upcoming book, How the Mind Works and How to Build One, is a good example of this—but hardly the only one. Futurists with a neuroscientific bent have been advocating this approach for years now, most prominently by the European transhumanist camp headed by Nick Bostrom and Anders Sandberg.

While I believe that reverse engineering the human brain is the right approach, I admit that it's not going to be easy. Nor is it going to be quick. This will be a multi-disciplinary endeavor that will require decades of data collection and the use of technologies that don't exist yet. And importantly, success won't come about all at once. This will be an incremental process in which individual developments will provide the foundation for overcoming the next conceptual hurdle.

But we have to start somewhere, and we have to start with a plan.

Rules-based AI versus whole brain emulation

Now, some computer theorists maintain that the rules-based approach to AI will get us there first. Ben Goertzel is one such theorist. I had a chance to debate this with him at the recent H+ Summit at Harvard. His basic argument is that the WBE approach over-complexifies the issue. "We didn't have to reverse engineer the bird to learn how to fly," he told me. Essentially, Goertzel is confident that the hard-coding of artificial general intelligence (AGI) is a more elegant and direct approach; it'll simply be a matter of identifying and developing the requisite algorithms sufficient for the emergence of the traits we're looking for in an AGI—things like learning and adaptation. As for the WBE approach, Goertzel thinks it's overkill and overly time consuming. But he did concede to me that he thinks the approach is sound in principle.

This approach aside, like Kurzweil, Bostrom, Sandberg and a growing number of other thinkers, I am drawn to the WBE camp. The idea of reverse engineering the human brain makes sense to me. Unlike the rules-based approach, WBE works off a tried-and-true working model; we're not having to re-invent the wheel. Natural selection, through excruciatingly tedious trial-and-error, was able to create the human brain—and all without a preconceived design. There's no reason to believe that we can't figure out how this was done; if the brain could come about through autonomous processes, then it can most certainly come about through the diligent work of intelligent researchers.

Emulation, simulation and cognitive functionalism

Emulation refers to a 1-to-1 model where all relevant properties of a system exist. This doesn't mean recreating the human brain in exactly the same way as it resides inside our skulls. Rather, it implies the recreation of all its properties in an alternative substrate, namely a computer system.

Moreover, emulation is not simulation. We're not looking to give the appearance of human-equivalent cognition. A simulation implies that not all properties of a model are present. Again, it's a complete 1:1 emulation that we're after.

Now, given that we're looking to model the human brain in digital substrate, we have to work according to a rather fundamental assumption: computational functionalism. This goes back to the Church-Turing thesis which states that a Turing machine can emulate any other Turing machine. Essentially, this means that every physically computable function can be computed by a Turing machine. And if brain activity is regarded as a function that is physically computed by brains, then it should be possible to compute it on a Turing machine. Like a computer.

So, if you believe that there's something mystical or vital about human cognition you should probably stop reading now.

Or, if you believe that there's something inherently physical about intelligence that can't be translated into the digital realm, you've got your work cut out for you to explain what that is exactly—keeping in mind that any informational process is computational, including those brought about by chemical reactions. Moreover, intelligence, which is what we're after here, is something that's intrinsically non-physical to begin with.

The roadmap to whole brain emulation

A number of critics point out that we'll never emulate a human brain on account of the chaos and complexity inherent in such a system. On this point I'll disagree. As Bostrom and Sandberg have pointed out, we will not need to understand the whole system in order to emulate it. What's required is a functional understanding of all necessary low-level information about the brain and knowledge of the local update rules that change brain states from moment to moment. What is meant by low-level at this point is an open question, but it likely won't involve a molecule-by-molecule understanding of cognition. And as Ray Kurzweil has revealed, the brain contains masterful arrays of redundancy; it's not as complicated as we currently think.

In order to gain this "low-level functional understanding" of the human brain we will need to employ a series of interdisciplinary approaches (most of which are currently underway). Specifically, we're going to require advances in:

• Computer science: We have to improve the hardware component; we're going to need machines with the processing power required to host a human brain; we're also going to need to improve the software component so that we can create algorithmic correlates to specific brain function.
• Microscopy and scanning technologies: We need to better study and map the brain at the physical level; brain slicing techniques will allow us to visibly study cognitive action down to the molecular scale; specific areas of inquiry will include molecular studies of individual neurons, the scanning of neural connection patterns, determining the function of neural clusters, and so on.
• Neurosciences: We need more impactful advances in the neurosciences so that we may better understand the modular aspects of cognition and start mapping the neural correlates of consciousness (what is currently a very grey area).
• Genetics: We need to get better at reading our DNA for clues about how the brain is constructed. While I agree that our DNA will not tell us how to build a fully functional brain, it will tell us how to start the process of brain-building from scratch.

Essentially, WBE requires three main capabilities: (1) the ability to physically scan brains in order to acquire the necessary information, (2) the ability to interpret the scanned data to build a software model, and (3) the ability to simulate this very large model.

Time-frames

Inevitably the question as to 'when' crops up. Personally, I could care less. I'm more interested in viability than timelines. But, if pressed for an answer, my feeling is that we are still quite a ways off. Kurzweil's prediction of 2030 is uncomfortably short in my opinion; his analogies to the human genome project are unsatisfying. This is a project of much greater magnitude, not to mention that we're still likely heading down some blind alleys.

My own feeling is that we'll likely be able to emulate the human brain in about 50 to 75 years. I will admit that I'm pulling this figure out of my butt as I really have no idea. It's more a feeling than a scientifically-backed estimate.

Lastly, it's worth noting that, given the capacity to recreate a human brain in digital substrate, we won't be too far off from creating considerably greater than human intelligence. Computer theorist Eliezer Yudkowsky has claimed that, because of the brain's particular architecture, we may be able to accelerate its processing speed by a factor of a million relatively easily. Consequently, predictions as to when we may hit the Singularity will likely co-incide with the advent of a fully emulated human brain.

Myers still thinks Kurzweil does not understand the brain

The blog war between PZ Myers and Ray Kurzweil continues. Myers has now retorted to Kurzweil's retort:

...you can't measure the number of transistors in an Intel CPU and then announce, "A-ha! We now understand what a small amount of information is actually required to create all those operating systems and computer games and Microsoft Word, and it is much, much smaller than everyone is assuming." Put it in those terms, and the Kurzweil fanboys would laugh at him; put it in terms of something they don't understand at all, like the development and function of the brain, and they're willing to go along with the pretense that the genome tells us that the whole organism is simpler than they thought.

I presume they understand that if you program a perfect Intel emulator, you don't suddenly get Halo: Reach for free, as an emergent property of the system. You can buy the code and add it to the system, sure, but in this case, we can't run down to GameStop and buy a DVD with the human OS in it and install it on our artificial brain. You're going to have to do the hard work of figuring out how that works and reverse engineering it, as well. And understanding how the processor works is necessary to do that, but not sufficient.

Myers concludes,

In short, here's Kurzweil's claim: the brain is simpler than we think, and thanks to the accelerating rate of technological change, we will understand it's basic principles of operation completely within a few decades. My counterargument, which he hasn't addressed at all, is that 1) his argument for that simplicity is deeply flawed and irrelevant, 2) he has made no quantifiable argument about how much we know about the brain right now, and I argue that we've only scratched the surface in the last several decades of research, 3) "exponential" is not a magic word that solves all problems (if I put a penny in the bank today, it does not mean I will have a million dollars in my retirement fund in 20 years), and 4) Kurzweil has provided no explanation for how we'll be 'reverse engineering' the human brain. He's now at least clearly stating that decoding the genome does not generate the necessary information — it's just an argument that the brain isn't as complex as we thought, which I've already said is bogus — but left dangling is the question of methodology. I suggest that we need to have a combined strategy of digging into the brain from the perspectives of physiology, molecular biology, genetics, and development, and in all of those fields I see a long hard slog ahead. I also don't see that noisemakers like Kurzweil, who know nothing of those fields, will be making any contribution at all.

Link.

Kurzweil responds to PZ Myers

Ray Kurzweil has retorted to PZ Myers's claim that he does not understand the brain:

For starters, I said that we would be able to reverse-engineer the brain sufficiently to understand its basic principles of operation within two decades, not one decade, as Myers reports.

Myers, who apparently based his second-hand comments on erroneous press reports (he wasn’t at my talk), goes on to claim that my thesis is that we will reverse-engineer the brain from the genome. This is not at all what I said in my presentation to the Singularity Summit. I explicitly said that our quest to understand the principles of operation of the brain is based on many types of studies — from detailed molecular studies of individual neurons, to scans of neural connection patterns, to studies of the function of neural clusters, and many other approaches. I did not present studying the genome as even part of the strategy for reverse-engineering the brain.

I mentioned the genome in a completely different context. I presented a number of arguments as to why the design of the brain is not as complex as some theorists have advocated. This is to respond to the notion that it would require trillions of lines of code to create a comparable system. The argument from the amount of information in the genome is one of several such arguments. It is not a proposed strategy for accomplishing reverse-engineering. It is an argument from information theory, which Myers obviously does not understand.

Be sure to read the entire response.

Sandberg: Whole Brain Emulation: The Logical Endpoint of Neuroinformatics?

Anders Sandberg delivered a talk on whole brain emulation at Google last month:

IBM's claim to have simulated a cat's brain grossly overstated

This is not a brain.

I'm a big fan of IBM's Brain and Mind Institute (BMI) and the Blue Brain project. Initiated in May 2005, the Blue Brain project is an attempt to to model the mammalian cerebral cortex with computers. The intention is not to re-create the actual physical structure of the brain, but to simulate it using arrays of supercomputers. Ultimately, the developers are hoping to create biologically realistic models of neurons. In fact, the results of the simulation will be experimentally tested against biological columns.

But I take exception to the recent claim that IBM has created a simulation that is supposedly on par, in terms of complexity and scale, with an actual cat's brain. The media tends to sensationalize these sorts of achievements, and in this case, grossly overstate (and even misstate) the actual accomplishment.

Contrary to what some people may believe, IBM has not created a virtual cat. There's no simulated cat somewhere pouncing around simulated fields chasing simulated mice inside a supercomputer. All IBM has done is replicate the power of a cat's cebebral coretex using a bunch of powerful computers. Nothing more -- there's no psychological or AI element involved whatsoever. They're merely creating a physical power structure and computational infrastructure that may someday run a properly engineered mind.

But credit where credit is due.

IBM has made incredible progress in the sophistication and detail level of human brain mapping. By reverse engineering the human brain, IBM hopes to bring about the era of "cognitive computing," -- a development that would bring about new ways for building computers which mimic natural brain structures.

Essentially, IBM is hoping to simulate a neocortical column, which is the smallest functional unit of the neocortex. This is the part of the brain that is responsible for higher functions such as conscious thought. In humans, the neocortical column is 2mm tall, has a diameter of 0.5mm and contains 60,000 neurons. Project developers initially worked to replicate the neocortical column of a rat, which has only 10,000 neurons, and now they've achieved the same thing with the cat brain. Developers hope to model the human brain in about seven to eight years.

To model these components the developers use a Blue Gene supercomputer that runs the MPI-based 'Neocortical Simulator' combined with 'NEURON' software. Blue Gene is a computer architecture project that has will spawn several next-generation supercomputers -- computers that will reach operating speeds in the petaflops range, and are currently reaching speeds over 280 sustained teraflops. Its 8,000 processors will crunch away at 23 trillion operations per second.

I don't want to take away from IBM's accomplishment, but it's important to note that we are extremely far off in terms of our ability to emulate the true complexity of a mammalian brain. Creating an array of supercomputers that mimics the brute force of a biological brain and then claiming that it matches the 'complexity' and 'scale' of the real thing is pure hyperbole. True whole brain emulation (PDF) is still a far ways off.

SS09: Randal Koene "The Time is Now We Need Whole Brain Emulation"

Benjamin Peterson is covering the Singularity Summit for Sentient Developments.

"Is the brain enough? Is the mind enough?"

Don't bother wasting time on the engineering biospheres for humans to live in space! Just figure out how to move what's in our skulls into a different substrate.

Physicality of the mind ... information must be preserved. move the mind off the meat substrate. Randal is impressing upon his audience the importance of shedding the fleshbag.

Theodore Berger building hippocampus replacement.

"In-vivo techniques, neural recording, neural interfacing:

• Scary/risky procedures

• chronic implantation

• power supply

• scale and bandwidth .."

Different technologies could provide less-invasive (?) modalities: qdots.

Multiscale scanning requirements, need to record neuronal activity at different levels of activity (voxel, group, spike, analog, spatial, molecular)

The human connectome. Automated tape-collecting lathe ultramicrotome ... o.O

Question from the audience regarding continuity. "If you make a copy the original dies ... what about the problem of continuity?"

SS09: Anders Sandberg "Whole Brain Emulation"

Benjamin Peterson is covering the Singularity Summit for Sentient Developments.

George covered neuroscientist Anders Sandberg's WBE (Whole Brain emulation) presentation during Convergence08. Anders is talking about the feasibility and paths to WBE.

"Whole Brain Emulation: feasibility, timescales and key challenges. Humans as existence proof for intelligent systems (so it can be done.) Why whole brain emulation? Exercise in forecasting, well defined problem, little understanding of intelligence needed, if it occurs it will likely be big (philo, scientific, economic, existential implications)

In order to emulate a brain we're going to need greater scanning capability:

• need enough resolution - rough consensus 5x5x50 nm resolution scanning

• need enough information

• need enough volume

• likely destructive" :[

Anders distinguishes WBE from mind-uploading ... maybe the wiki is misinformed?

"The step from mouse to man is 20 years in terms of brain emulation. First scan or simulate then computer power gradual emergence of emulation."

Lights up, Anders fields questions from the audience.

Anissimov on the benefits of mind uploading

Transhumanist and Accelerating Future blogger Michael Anissimov has posted a thought-provoking article about universal mind uploading and the potential benefits it may bring.

Mind uploading, sometimes called whole brain emulation, refers to the hypothetical transfer of a human mind to a substrate different from a biological brain, such as a detailed computer simulation of an individual human brain. Given the (likely) functionalist nature of the human brain, and given steady advances across a number of scientific disciplines, mind transfer may eventualy become reality; this is not just idle fantasy.

And as Anissimov notes, even if this technology doesn't arrive for a hundred years, it's still something worth speculating about and working towards; the ramifications would be, quite obviously, profound for the human species.

Indeed, as Anissimov notes, there are at least 7 benefits to mind uploading:

1. Massive economic growth
2. Intelligence enhancements
3. Greater subjective well-being
4. Complete environmental recovery
5. Escape from direct governance by the laws of physics
6. Closer connections with other human beings
7. Indefinite lifespans

Mind uploading, which may or may not be possible, would clearly represent an existential gamechanger. As Anissimov concludes,

From a utilitarian perspective, it practically blows everything else away besides global risk mitigation, as the number of new minds leading worthwhile lives that could be created using the technology would be astronomical. The number of digital minds we could create using the matter on Earth alone would likely be over a quadrillion, more than 10,000 people for every star in the 400 billion star Milky Way. We could make a “Galactic Civilization”, right here on Earth in the late 21st or 22nd century. I can scarcely imagine such a thing, but I can imagine that we’ll be guffawing heartily as how unambitious most human goals were in the year 2009.

Read the entire article.

Convergence08: Anders Sandberg on Whole Brain Emulation

The term 'whole brain emulation' sounds more scientific than it does science fiction like, which may bode well for its credibility as a genuine academic discipline and area for inquiry.

Sandberg presented his whole brain emulation roadmap which had a flowchart like quality to it -- which he quipped must be scientific because it was filled with arrows.

Simulating memory could be very complex, possibly involving chemical transference in cells or drilling right down to the molecular level. We may even have to go down to the quantum level, but no neuroscientist that Anders knows takes that possibility seriously.

Validation has been overlooked in discussions of uploading/downloading. In other words, we don't know if our simulations will convert to reality or not. We need to find ways of testing -- to take pieces of neuron tissue and know exactly how it's working. The retina is a good candidate for beginning this sort of research.

Scanning technologies are painfully slow; research to improve this aspects needs to happen. Electron microscopy will be required. It would be nice to to get down to 50 nanometers. Destructive scanning may be necessary in some cases.

Functional simulation of neurons is relatively easy and is currently being done in research labs.

In regards to computer power, memory storage will not be a bottleneck at all. In terms of raw power, we should plot and plan our emulations around the expected time-frames for processing power (i.e. Moore's Law graphs).

Interesting ethical problems emerge about testing with non-human animals and their potential suffering. It will also be difficult to suss subjective data from animals -- like getting their perspective on changes to perception, discomfort level, etc. Anders wants to write an entire paper on the matter.

There are also significant differences between large and small brains (like mouse brains).

This will be a massive iterative process that will take lots of time and effort; it will also be driven by technological advances. There are still a large number of purely philosophical challenges. For example, we may find that scanning is not a panacea that will always reveal function.

___________
Read more about whole brain simulation.

Anders Sandberg wants to emulate your brain

Transhumanists have long speculated about the possibility of uploading a brain into a computer. In fact, a big part of the supposed posthuman future depends on it.

Soooo, how the hell do we do it?

This is the issue that Swedish neuroscientist Anders Sandberg tackled for his talk at TransVision 2007. Uploading, or what Sandberg refers to as ‘whole brain emulation,’ has become a distinct possibility arising from the feasibility of the functionalist paradigm and steady advances in computer science. Sandberg says we need a strategic plan to get going.

Levels of understanding

To start, Sandberg made two points about the kind of understanding that is required. First, we do not need to understand the function of a device to build it from parts, and second, we do not need to understand the function of the brain to emulate it. That said, Sandberg admitted that we still need to understand the brain's lower level functions in order for us to be able to emulate them.

The known unknown

Sandberg also outlined the various levels of necessary detail; we can already start to parse through the “known unknown.” He asked, “what level of description is necessary to capture enough of a particular brain to mimic its function?”

He described several tiers that will require vastly more detail:

• Computational model
• Brain region connectivity
• Analog network population model
• Spiking neural network
• Electrophysiology
• Metabolome
• Proteome
• Etc. (and all the way down to the quantum level)

Requirements

Sandberg believes that the ability to scan an existing brain will be necessary. What will also be required is the proper scanning resolution. Once we can peer down to the sufficient detail, we should be able to construct a brain model; we will then be required to infer structure and low-level function.

Once this is done we can think about running a brain emulation. Requirements here will include a computational neuroscience model and the requisite computer hardware. Sandberg noted that body and environment simulations may be added to the emulation; the brain emulator, body simulator and environment simulator would be daisy-chained to each other to create the sufficient interactive link. The developers will also have to devise a way to validate their observations and results.

Neural simulations

Neural simulations are nothing new. Hodgkin and Huxley began working on these sorts of problems way back in 1952. The trick is to perfectly simulate neurons, neuron parts, synapses and chemical pathways. According to Sandberg, we are approaching 1-1 for certain systems, including the lamprey spinal cord and lobster ganglia.

Compartment models are also being developed with miniscule time and space resolutions. The current record is 22 million 6-compartment neurons, 11 billion synapses, and a simulation length of one second real-time. Sandberg cited advances made by the development of IBM’s Blue Gene.

Complications and Exotica

Sandberg also provided a laundry list of possible ‘complications and exotica’:

• dynamical state
• spinal cord
• volume transmission
• glial cells
• synaptic adaptation
• body chemical environment
• neurogensis
• ephaptic effects
• quantum computation
• analog computation
• randomness

Reverse engineering is all fine and well, suggested Sandberg, but how much function can be deduced from morphology (for example)?

Scanning

In regards to scanning, we'll need to determine the kind of resolution and data needed. Sandberg argued that nondestructive scanning will be unlikely; MRIs have been the closest thus far but are limited to less than 7.7 micrometers resolution. More realistically, destructive scanning will likely be used; Sandberg noted such procedures as fixation and ‘slice and scan.’

Once scanning is complete the postprocessing can begin. Developers at this stage will be left wondering about the nature of the neurons and how they are all connected.

Given advances in computation, Sandberg predicted that whole brain emulation may arrive sometime between 2020 and 2060. As for environment and body simulation, we’ll have to wait until we have 100 terraflops at our disposal. We’ll also need a resolution of 5x5x50nm to do meaningful work.

Conclusions

Sandberg made mention of funding and the difficultly of finding scan targets. He named some subfields that lack drivers, namely basic neuroscience, electrophysiology, and large scale scanning (so far). He did see synergies arising from the ongoing development and industrialization of neuroscience, robotics and all the various –omics studies.

As for the order of development, Sandberg suggested 1) scanning and/or simulation, then 2) computer power, and then 3) the gradual emergence of emulation. Alternately, 1) first computer power, then 2) simulation and finally 3) scanning followed by 4) the rapid emergence of simulation.

Any volunteers for slice and scan?