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.

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?


Research platforms of Human Brain Project released

The Human Brain Project (HBP), a flagship project of the European Union, has just released the initial versions of its six Information and Communications Technology (ICT) platforms to users worldwide.

The six HBP Platforms are:

  • Neuroinformatics
  • Brain Simulation
  • High Performance Computing
  • Medical Informatics
  • Neuromorphic Computing
  • Neurorobotics


These platforms enable researchers to use the tools developed by the Human Brain Project to search and analyse neuroscience data, simulate brain sections, run complex simulations, searching of real data to understand similarities and differences among brain diseases, access computer systems that emulate brain microcircuits,  and test virtual models of the brain by connecting them to simulated robot bodies and environments.
All the Platforms can be accessed via the HBP Collaboratory, a web portal where users can also find additional information.