IEEE Spectrum special issue on whether we can duplicate a brain

Maybe you have read The Digital Mind or The Singularity is Near, by Ray Kurzweil, or other similar books, thought it all a bit farfetched, and wondered whether the authors are bonkers or just dreamers.

Wonder no more. The latest issue of the flagship publication of the Institute for Electrical and Electronic Engineers, IEEE Spectrum , is dedicated to the interesting and timely question of whether we can copy the brain, and use it as blueprint for intelligent systems.  This issue, which you can access here, includes many interesting articles, definitely worth reading.

I cannot even begin to describe here, even briefly, the many interesting articles in this special issue, but it is worthwhile reading the introduction, on the perspective of near future intelligent personal assistants or the piece on how we could build an artificial brain right now, by Jennifer Hasler.

Other articles address the question on how expensive, computationally, is the simulation of a brain at the right level of abstraction. Karlheinz Meier’s article on this topic explains very clearly why present day simulations are so slow:

“The big gap between the brain and today’s computers is perhaps best underscored by looking at large-scale simulations of the brain. There have been several such efforts over the years, but they have all been severely limited by two factors: energy and simulation time. As an example, consider a simulation that Markus Diesmann and his colleagues conducted several years ago using nearly 83,000 processors on the K supercomputer in Japan. Simulating 1.73 billion neurons consumed 10 billion times as much energy as an equivalent size portion of the brain, even though it used very simplified models and did not perform any learning. And these simulations generally ran at less than a thousandth of the speed of biological real time.

Why so slow? The reason is that simulating the brain on a conventional computer requires billions of differential equations coupled together to describe the dynamics of cells and networks: analog processes like the movement of charges across a cell membrane. Computers that use Boolean logic—which trades energy for precision—and that separate memory and computing, appear to be very inefficient at truly emulating a brain.”

Another interesting article, by Eliza Strickland, describes some of the efforts that are taking place to use  reverse engineer animal intelligence in order to build true artificial intelligence , including a part about the work by David Cox, whose team trains rats to perform specific tasks and then analyses the brains by slicing and imaging them:

“Then the brain nugget comes back to the Harvard lab of Jeff Lichtman, a professor of molecular and cellular biology and a leading expert on the brain’s connectome. ­Lichtman’s team takes that 1 mm3 of brain and uses the machine that resembles a deli slicer to carve 33,000 slices, each only 30 nanometers thick. These gossamer sheets are automatically collected on strips of tape and arranged on silicon wafers. Next the researchers deploy one of the world’s fastest scanning electron microscopes, which slings 61 beams of electrons at each brain sample and measures how the electrons scatter. The refrigerator-size machine runs around the clock, producing images of each slice with 4-nm resolution.”

Other approaches are even more ambitious. George Church, a well-known researcher in biology and bioinformatics, uses sequencing technologies to efficiently obtain large-scale, detailed information about brain structure:

“Church’s method isn’t affected by the length of axons or the size of the brain chunk under investigation. He uses genetically engineered mice and a technique called DNA bar coding, which tags each neuron with a unique genetic identifier that can be read out from the fringy tips of its dendrites to the terminus of its long axon. “It doesn’t matter if you have some gargantuan long axon,” he says. “With bar coding you find the two ends, and it doesn’t matter how much confusion there is along the way.” His team uses slices of brain tissue that are thicker than those used by Cox’s team—20 μm instead of 30 nm—because they don’t have to worry about losing the path of an axon from one slice to the next. DNA sequencing machines record all the bar codes present in a given slice of brain tissue, and then a program sorts through the genetic information to make a map showing which neurons connect to one another.”

There is also a piece on the issue of AI and consciousness, where Christoph Koch and Giulio Tononi describe their (more than dubious, in my humble opinion) theory on the application of Integrated Information Theory to the question of: can we quantify machine consciousness?

The issue also includes interesting quotes and predictions by famous visionairies, such as Ray Kurzweil, Carver Mead, Nick Bostrom, Rodney Brooks, among others.

Images from the special issue of IEEE Spectrum.

To Be a Machine: Adventures Among Cyborgs, Utopians, and the Futurists Solving the Modest Problem of Death

Mark O’Connell witty, insightful and sometimes deeply moving account of his research on the topic of transhumanism deserves a place in the bookshelf of anyone interested in the future of humanity. Reading To Be a Machine is a delightful trip through the ideals, technologies, places and characters involved in transhumanism, the idea that science and technology will one day transform human into immortal computer based lifeforms.

For reasons that are not totally clear to me, transhumanism remains mostly a fringe culture, limited to a few futurists, off-the-mainstream scientists and technology nuts. As shared fictions go (to use Yuval Harari’s notation), I would imagine transhumanism is one idea whose time has come. However, it remains mostly unknown by the general public. While humanists believe that the human person, with his/her desires, choices, and fears, should be the most important value to be preserved by a society (check my review of Homo Deus), transhumanists believe that biological based intelligence is imperfect, exists purely because of historical reasons (evolution, that is) and will go away soon as we move intelligence into other computational supports, more robust than our frail bodies.

O’Connell, himself a hard-core humanist, as becomes clear from reading between the lines of this book, pursued a deep, almost forensic, investigation on what transhumanists are up to. In this process, he talks with many unusual individuals involved in the transhumanist saga, from Max More, who runs Alcor, a company that, in exchange for a couple hundred dollars, will preserve your body for the future in liquid nitrogen (or 80k for just the head) to Aubrey de Grey, a reputed scientist working in life extension technologies, who argues that we should all be working on this problem. In de Grey’s words, cited by O’Connell “aging is a human disaster on an unimaginably vast scale, a massacre, a methodical and comprehensive annihilation of every single person that ever lived“. These are just two of the dozens of fascinating characters in the book interviewed in place by O’Connell.

The narrative is gripping, hilarious at times, but moving and compelling, not the least because O’Connell himself provides deep insights about the issues the book discusses. The characters in the book are, at once, alien and deeply human, as they are only trying to overcome the limits of our bodies. Deservedly, the book has been getting excellent reviews, from many sources.

In the end, one gets the idea that transhumanists are crazy, maybe, but not nearly as crazy as all other believers in immortality, be it by divine intervention, by reincarnation, or by any other mechanisms so ingrained in mainstream culture.

The Digital Mind: How Science is Redefining Humanity

Following the release in the US,  The Digital Mind, published by MIT Press,  is now available in Europe, at an Amazon store near you (and possibly in other bookstores). The book covers the evolution of technology, leading towards the expected emergence of digital minds.

Here is a short rundown of the book, kindly provided by yours truly, the author.

New technologies have been introduced in human lives at an ever increasing rate, since the first significant advances took place with the cognitive revolution, some 70.000 years ago. Although electronic computers are recent and have been around for only a few decades, they represent just the latest way to process information and create order out of chaos. Before computers, the job of processing information was done by living organisms, which are nothing more than complex information processing devices, created by billions of years of evolution.

Computers execute algorithms, sequences of small steps that, in the end, perform some desired computation, be it simple or complex. Algorithms are everywhere, and they became an integral part of our lives. Evolution is, in itself, a complex and long- running algorithm that created all species on Earth. The most advanced of these species, Homo sapiens, was endowed with a brain that is the most complex information processing device ever devised. Brains enable humans to process information in a way unparalleled by any other species, living or extinct, or by any machine. They provide humans with intelligence, consciousness and, some believe, even with a soul, a characteristic that makes humans different from all other animals and from any machine in existence.

But brains also enabled humans to develop science and technology to a point where it is possible to design computers with a power comparable to that of the human brain. Artificial intelligence will one day make it possible to create intelligent machines and computational biology will one day enable us to model, simulate and understand biological systems and even complete brains with unprecedented levels of detail. From these efforts, new minds will eventually emerge, minds that will emanate from the execution of programs running in powerful computers. These digital minds may one day rival our own, become our partners and replace humans in many tasks. They may usher in a technological singularity, a revolution in human society unlike any other that happened before. They may make humans obsolete and even a threatened species or they make us super-humans or demi-gods.

How will we create these digital minds? How will they change our daily lives? Will we recognize them as equals or will they forever be our slaves? Will we ever be able to simulate truly human-like minds in computers? Will humans transcend the frontiers of biology and become immortal? Will humans remain, forever, the only known intelligence in the universe?


Is mind uploading nearer than you might think?

A recent article published in The Guardian, an otherwise mainstream newspaper, openly discusses the fact that mind uploading may become a real possibility in the near future. Mind uploading is based on the concept that the behavior of a brain can be emulated completely in a computer, ultimately leading to the possibility of transporting individual brains, and individual consciousnesses, into a program, which would emulate the behavior of the “uploaded” mind. Mind uploading represents, in practice, the surest and most guaranteed way to immortality, far faster than any other non-digital technologies can possibly aim to achieve in the foreseeable future.

This idea is not new, and the article makes an explicit reference to Hans Moravec book, The Mind Children, published by Harvard University Press in 1988. In fact, the topic has been already been addressed by a large number of authors, including Ray Kurzweil, in The Singularity is Near, Nick Bostrom, in Superintelligence, and even by me in The Digital Mind.

The article contains an interesting list of interesting sites and organizations, including CarbonCopies, a site dedicated to making whole brain emulation possible, founded by Randal A Koene, and a reference to the 2045 initiative, with similar goals, created by Dmitry Itskov.

The article, definitely worthwhile reading, goes into some detail in the idea of “substrate independent minds”, an idea clearly reminiscent of the concept of virtualization, so in vogue in today’s business world.

Picture source: The Guardian

How to create a mind

Ray Kurzweil’s latest book, How to Create a Mind, published in 2012, is an interesting read and shows some welcome change on his views of science and technology. Unlike some of his previous (and influntial) books, including The Singularity is Near, The Age of Spiritual Machines and The Age of Intelligent Machines, the main point of this book is not that exponential technological development will bring in a technological singularity in a few decades.


True, that theme is still present, but takes second place to the main theme of the book, a concrete (although incomplete) proposal to build intelligent systems that are inspired in the architecture of the human neocortex.

Kurzweil main point in this book is to present a model of the human neocortex, what he calls The Pattern Recognition Theory of the Mind (PRTM). In this theory, the neocortex is simply a very powerful pattern recognition system, built out of about 300 million (his number, not mine) similar pattern recognizers. The input from each of these recognizers can come from either external inputs, through the senses, or from the older parts (evolutionary speaking) of the brain, or from the output of other pattern recognizers in the neocortex. Each recognizer is relatively simple, and can only recognize a simple pattern (say the word APPLE) but, through complex interconnections with other recognizers above and below, it makes possible all sorts of thinking and abstract reasoning.

Each pattern consists, in its essence, in a short sequence of symbols, and is connected, through bundles of axons, to the actual place in the cortex where these symbols are activated, by another pattern recognizer. In most cases, the memories these recognizers represent must be accessed in a specific order. He gives the example that very few persons can recite the alphabet backwards, or even their social security number, which is taken as evidence of the sequential nature of operation of these pattern recognizers.

The key point of the book is that the actual algorithms used to build and structure a neocortex may soon become well understood, and used to build intelligent machines, embodied with true strong Artificial Intelligence. How to Create a Mind falls somewhat short of the promise in the subtitle, The Secret of Human Thought Revealed, but still makes for some interesting reading.

IBM TrueNorth neuromorphic chip does deep learning

In a recent article, published in the Proceedings of the National Academy of Sciences, IBM researchers demonstrated that the TrueNorth chip, designed to perform neuromorphic computing, can be trained using deep learning algorithms.


The TrueNorth chip was designed to efficiently simulate the efficient modeling of spiking neural networks, a model for neurons that closely mimics the way biological neurons work. Spiking neural networks are based on the integrate and fire model, inspired on the fact that actual neurons integrate the incoming ion currents caused by synaptic firing and generate an output spike only when sufficient synaptic excitation has been accumulated. Spiking neural network models tend to be less efficient than more abstract models of neurons, which simply compute the real valued output directly from the values of the real valued inputs multiplied by the input weights.

As IEEE Spectrum explains: “Instead of firing every cycle, the neurons in spiking neural networks must gradually build up their potential before they fire. To achieve precision on deep-learning tasks, spiking neural networks typically have to go through multiple cycles to see how the results average out. That effectively slows down the overall computation on tasks such as image recognition or language processing.

In the article just published, IBM researchers have adapted deep learning algorithms to run on their TrueNorth architecture, and have achieved comparable precision, with lower energy dissipation. This research raises the prospect that energy-efficient neuromorphic chips may be competitive in deep learning tasks.

Image from Wikimedia Commons

The User Illusion: Cutting consciousness down to size

In this entertaining and ambitious book Tor Nørretranders argues that consciousness, that hallmark of higher intelligence, is nothing more than an illusion, a picture of reality created by our brain that we mistake by the real thing. The book received good reviews and was very well received in his native country, Denmark, and all over the world.

Using fairly objective data, Nørretranders makes his main point that consciousness has a very limited bandwidth, probably no more than 20 bits a second. This means that we cannot, consciously, process more than a few bits a second, distilled from the megabytes of information processed by our senses in the same period. Furthermore, this stream of information creates a simulation of reality, which we mistake for the real thing, and the illusion that our conscious self (the “I”) in in charge, while the unconscious self (the “me”) follows the orders given by the “I”.


There is significant evidence that Nørretranders’ main point is well taken. We know (and he points it out in his book) that consciousness lags behind our actions, even conscious ones, by about half a second. As is also pointed out by another author, Daniel Dennett, in his book Consciousness Explained, consciousness controls much less than we think. Consciousness is more of a module that observes what is going on and explains it in terms of “conscious decisions” and “conscious attention”. This means that consciousness is more of an observer of our actions, than the agent that determines them. Our feeling that we consciously control our desires, actions, and sentiments is probably far from the truth, and a lot of what we consciously observe is a simulation carefully crafted by our “consciousness” module. Nørretranders refers to the fact that some people believe that consciousness is a recent phenomenon, maybe no more than a few thousand years old, as Julian Jaynes defended in his famous book, The Bicameral Mind.

Nørretranders uses these arguments to argue that we should pay less attention to conscious decisions (the “I”, as he describes it) and more to unconscious urges (the “me”, in his book), letting the unconscious “me”, who has access to vastly larger amounts of information, in control of more of your decisions.