Brain-i-Nets Mission = General Artificial Intelligence.

As the hunt for general artificial intelligence aka “thinking, conscious machines” heats up some of the more promising projects are getting a modest level of funding, and it now seems likely we’ll have some significant progress over the next few years. Hopefully

We’ve written a lot about DARPA SyNAPSE and the BLUE BRAIN projects, but a new exciting one in Europe (not sure about the name though) is called …



Novel Brain‐Inspired Learning Paradigms for Large‐Scale
Neuronal Networks

• Our vision: To build a novel type of computing
machinery, exhibiting human‐like learning

• Our approach: To port leaning and adaptation
mechanisms in the brain to brain‐inspired

• Our path: An interdisciplinary roadmap from
neuroscience to technology.
•Explore: Use cutting‐edge techniques to gain
insight in how the brain learns.

•Understand: Understand the results through
mathematical analysis and simulation.

• Implement: Study the implementation in novel
brain‐inspired hardware.


Read more at the University of Heidleberg’s Brain-i-Nets website

Google’s Norvig on “Strong AI”

Google’s Peter Norvig on “Strong AI” and other technology topics. Peter Norvig is a pioneer in Artificial Intelligence, and in this video answers a question about “strong AI”. His take on the topic is a bit different and I’d say more skeptical than folks like Ray Kurzweil who are both optimistic and very enthusiastic about the prospects for a technological singularity in the near future. Norvig is considerably more cautious, suggesting that the issue of “consciousness” is not even all that relevant. I spoke with Norvig briefly at a conference in 2008 and asked him about machine consciousness. There he gave me a similar answer to here – he wasn’t even sure how we could define the term. Norvig’s approach and philosophy is very practical, and like many computer engineers he seems to think “strong AI” could take some time.

Wordlens – a free iPhone text translator

Update:  After seeing the demo of Wordlens and hearing that reviewers were “disappointed” due to speed and effectiveness I think this application needs a lot of work.

Remains, however, a great idea

Kudos to the folks at Quest Visual:   Their free  iPhone application “Wordlens” allows real time translation by simply pointing your iPhone at a sign or other text.

As any traveler knows it’s very helpful to be able to interpret signs, menus, and  other text.   This is naturally very difficult in countries where you don’t speak the language.    Wordlens is only available in spanish now but other languages are on the way, and this is clearly a great step in the direction of our phones and handheld devices becoming “universal translators”

Via Singularity Hub

more at Quest Visual:

Computer Consciousness – let the games begin!

Over at the Neurdon blog we’re following a great series about Artificial Intelligence “AI” in general and about developments in Darpa SyNAPSE, the best funded project to date that is working on a “general artificial intelligence” – in short a machine that can think pretty much like we do.

This is the article, about a new chip called a “Memristor”  that seemed to spawn a lot of discussion.   It’s a new approach under development as part of the DARPA SyNAPSE project.  [thanks to my good pal Roy K who always forwards me very interesting stuff!]

It’s encouraging to see the debate over computer consciousness take such a serious tone as this topic is arguably one of the most intriguing in all of human history.    Many experts believe we’ll see machines become self-aware within 10-20 years.    Given the massive computational superiority computers already enjoy over humans, one can make a strong case that a conscious computer – or more likely a computer + human brain hybrid – will  clone its intellect and improve that intellect over and over in a very short time, leading to levels of intelligence far beyond that of “normal” humans.

Also encouraging that pioneers in the field like the article’s authors:  Sean Lorenz, Heather Ames & Massimiliano Versace are willing to discuss this topic rather than shelve it as so many in computer research have done.    I think early inflated optimism about artificial intelligence led to so much disappointment in the computer community that the “old guard” programmers are being too stubborn now, especially in the face of very significant advances in the understanding of human neurobiology and in computational speeds and memory capacities.

From the post ” Moneta_And_The_C_Word”

Although Searle has argued for biological embodiment as a necessity for causation of consciousness, this paper puts forth the argument that biological embodiment is not the only embodiment that can produce consciousness. Instead, we argue that the brain is an optimal form of embodiment giving rise to consciousness because it can produce observable reports, oral reports, and observed and measured activity. The first two qualifications of consciousness can be replicated with computer simulations as discussed by the proponents of WBE. However, the third qualification requires a unique stipulation for embodiment that is able to self organize and generate unique global and local patterns of activities within its constituent elements. At this point in time, this is only achievable within brain tissue. However, with the advancement of neural chip development, we would argue that embodiment necessary for consciousness would be achievable in a new medium, the neuromorphic chip.

IBM Watson search algorithm vs Jeopardy’s Best Players

IBM’s Watson search routine is one of the best in the world.   Watson is not as popular as Google search partly because it takes longer to answer questions, but in many ways Watson may be a more powerful “Search Algorithm” than Google search.

Watson’s brilliancy will be tested in February against Jeopardy’s best contestants:

IBM had announced a Jeopardy test for Watson over a year ago and we are checking on why there has been such a long delay in the contest, now scheduled for three episodes in February 2011.

See Technology Report’s Jeopardy post from CES 2009

Brain Chips from DARPA

Wired’s  Danger Room is reporting on a new DARPA project to build brain implant chips that will fix brain injuries.    The focus appears to have come from the large number of  returning veterans who suffer from brain injuries.

However the implications of this type of research go far beyond simple repair.   As science improves the current state of the art of brain implants (which now offer only rudimentary connections to actual brain functions), we are likely to see a spectacular increase in human intellectual capabilities.   Our current limitations to information processing include the very slow speeds with which we can interact with computers – usually via keyboards.   When implants will allow brains to *directly* interface with, for example, internet information, we are very likely to experience an explosion of human capabilities.

IBM’s Artificial Intelligence – is the cat brain out of the bag or not?

We’ve profiled two of the world’s most promising AI efforts here at Technology Report.     Blue Brain in Switzerland and DARPA SyNAPSE here in the USA, a newer project that appears to be getting better funding thanks to backing from the US Defense Department.   Both of these projects rely on IBM supercomputers for their simulations of neurons and their interactions, and both are optimistic about the potential to develop thinking machines within the next decade.

The project leader of Blue Brain, Dr. Henry Markram, has been very vocal and very critical of claims by  the IBM team leader Dr. Dharmendra S. Modha.    Markram’s concerns are expressed here in his Technology Report guest post about the IBM project claims.

We asked Dr. Modha for a response but didn’t hear back, so I’d like to refer folks to the Modha blog here, especially to the post called ‘The Cat is Out of the bag and BlueMatter”, which details progress in the SyNAPSE project and explains the claims made that they are simulating brain activity that is roughly equivalent to that we’d see from a cat.  Here’s an excerpt from that post:

Towards this end, we are announcing two major milestones.

First, using Dawn Blue Gene / P supercomputer at Lawrence Livermore National Lab with 147,456 processors and 144 TB of main memory, we achieved a simulation with 1 billion spiking neurons and 10 trillion individual learning synapses. This is equivalent to 1,000 cognitive computing chips each with 1 million neurons and 10 billion synapses, and exceeds the scale of cat cerebral cortex. The simulation ran 100 to 1,000 times slower than real-time.

Second, we have developed a new algorithm, BlueMatter, that exploits the Blue Gene supercomputing architecture to noninvasively measure and map the connections between all cortical and sub-cortical locations within the human brain using magnetic resonance diffusion weighted imaging. Mapping the wiring diagram of the brain is crucial to untangling its vast communication network and understanding how it represents and processes information.

Finally, here is an excellent presentation by Dr. Modha that outlines in simple terms what they are trying to do with DARPA SyNAPSE, which is build a human scale brain by 2018.

New Artificial Intelligence Initiative Begins in group of European Universities

A new initiative to develop something of a “strong AI” computer has begun in Europe, coordinated by this group:

Strong AI is, for many, the “holy grail” of computing and in general terms means the development of a machine that thinks as well or better than a human.    Computers already have surpassed humans in most very focused intelligence tasks such as mathematical calculations, game playing, most forms of data analysis, and many more of the tasks we often use to define  “intelligence”.     However no machine comes close to the capabilities of a full human brain at this time, our remarkable three pound package that includes a high level of consciousness and self-awareness, adaptive mechanisms, deep creativity, and more.

With a fairly modest budget compared to the DARPA SyNAPSE,  Brain-i-nets goals appear more modest.   Science Daily suggests the goal as:

The scientists want to design a new generation of neuro-computers based on the principles of calculation and learning mechanisms found in the brain, and at the same time gain new knowledge about the brain’s learning mechanisms.

The Brain-i-nets website puts this …. somewhat differently, leading one to wonder if they were writing for public understanding or a science fiction movie script:

The goal of this project is to produce a set of rules for synaptic plasticity and network reorganisation that describe the actual adaptive processes that take place in the living brain during learning and to port these rules into current and next-generation neuromorphic hardware.

“Future Emerging Technologies” (FET) is the key agency behind   “Brain-i-Nets” which appears to have a budget of about 2.6 million Euros (though I’m not clear if this is just the matching partner funding or the entire budget).

The research partnership includes the University College London, the Ecole Polytechnique Federale de Lausanne, the French Centre National de la Recherche Scientifique, Ruprecht-Karls-Universität Heidelberg und the University of Zurich.

Neuroscience Expert Dr. Henry Markram on the IBM “Cat Brain” Simulation: “IBM’s claim is a HOAX”

Editors Note:   We’re hoping for more information from Dr. Modha who is also welcome to a Guest post here at Technology Report.

——   Guest Post by Dr. Henry Markram of the Blue Brain Project —-

IBM’s claim is a HOAX.

This is a mega public relations stunt – a clear case of scientific deception of the public. These simulations do not even come close to the complexity of an ant, let alone that of a cat. IBM allows Mohda to mislead the public into believing that they have simulated a brain with the complexity of a cat – sheer nonsense.

Here are the scientific reasons why this is a hoax and misleading PR stunt:

How complex is their model?
They claim to have simulated over a billion neurons interacting. Their so called “neurons” are the tiniest of points you can imagine, a microscopic dot. Over 98% of the volume of a neuron is branches (like a tree). They just cut off all the branches and roots and took a point in the middle of the trunk to represent a entire neuron. In real life, each segment of the branches of a neuron contains dozens of ion channels that powerfully controls the information processing in a neuron. They have none of that. Neurons contain 10’s of thousands of proteins that form a network with 10’s of millions of interactions. These interactions are incredibly complex and will require solving millions of differential equations. They have none of that. Neurons contain around 20’000 genes that produce products called mRNA, which builds the proteins. The way neurons build proteins and transport them to all the corners of the neuron where they are needed is an even more complex process which also controls what a neuron is, its memories and how it will process information. They have none of that. They use an alpha function (up fast down slow) to simulate a synaptic event. This is a completely inaccurate representation of a synapse. There are at least 6 types of synapses that are highly non-linear in their transmission (i.e. that transform inputs and not only transmit inputs). In fact you would need a 10’s of thousands of differential equations to simulate one synapse. Synapses are also extremely complex molecular machines that would themselves require thousands of differential equations to simulate just one. They simulated none of this. There are complex differential equations that must be solved to simulate the ionic flow in the branches, to simulate the ion channels biophysics, the protein-protein interactions, as well as the complete biochemical and genetic machinery as well as the synaptic transmission between neurons. 100’s of thousands of more differential equations. They have none of this. Then there are glia – 10 times more than neurons..And the blood supply…and more and more. These “points” they simulated and the synapses that they use for communication are literally millions of times simpler than a real cat brain. So they have not even simulated a cat’s brain at more than one millionth of it’s complexity.

Is it nonetheless the biggest point neuron simulation ever run?
No. These people simulated 1 billion points interacting. They used a formulation to model the summing up and threshold spiking of the “points” called the Izhikevik Formulation (an extremely simple equation). Eugene Izhikevik himself already in 2005 ran a simulation with 100 billion such points interacting just for the fun of it: (over 60 times larger than Modha’s simulation). This simulation ran on a cluster of desktop PCs and which every graduate student can run This is no technical achievement and certainly not even a record number of point neurons. That model exhibited oscillations, but that always happens so even simulating 100 Billion such points interacting is light years away from a brain.

Is the simulator they built a big step?
Not even close. There are numerous proprietary and peer-reviewed neurosimulators (e.g., NCS, pNEURON, SPLIT, NEST) out there that can handle very large parallel models that are essentially only bound by the available memory. The bigger the machine you have available, the more neurons you can simulate. All these simulators apply optimizations for the particular platform in order to make optimal use of the available hardware. Without any comparison to existing simulators, their publication is a non-peer reviewed claim.

Did they learn anything about the brain?
They got very excited because they saw oscillations. Oscillations are an obligatory artifact that one always gets when many points interact. These findings that they claim on the neuroscience side may excite engineers, but not neuroscientists.

Why did they get the Gordon Bell Prize?
They submitted a non-peer reviewed paper to the Gordon Bell Committee and were awarded the prize almost instantly after they made their press release. They seem to have been very successful in influencing the committee with their claim, which technically is not peer-reviewed by the respective community and is neuroscientifically outrageous.

But is there any innovation here?
The only innovation here is that IBM has built a large supercomputer – which is irrelevant to the press release.

Why did IBM let Mohda make such a deceptive claim to the public?
I don’t know. Perhaps this is a publicity stunt to promote their supercompter. The supercomputer industry is suffering from the financial crisis and they probably are desperate to boost their sales. It is so disappointing to see this truly great company allow the deception of the public on such a grand scale.

But have you not said you can simulate the Human brain in 10 years?
I am a biologist and neuroscientist that has studied the brain for 30 years.  I know how complex it is. I believe that with the right resources and the right strategy it is possible. We have so far only simulated a small part of the brain at the cellular level of a rodent and I have always been clear about that.

Would other neuroscientists agree with you?
There is no neuroscientist on earth that would agree that they came even close to simulating the cat’s brain – or any brain.

But did Mohda not collaborate with neuroscientists?
I would be very surprised if any neuroscientists that he may have had in his DARPA consortium realized he was going to make such an outrages claim. I can’t imagine that that the San Fransisco neuroscientists knew he was going to make such a stupid claim. Modha himself is a software engineer with no knowledge of the brain.

But did you not collaborate with IBM?
I was collaborating with IBM on the Blue Brain Project at the very beginning because they had the best available technology to faithfully allow us to integrate the diversity and complexity found in brain tissue into a model. This for me is a major endeavor to advance our insights into the brain and drug development. Two years ago, when the same Dharmendra Mhoda claimed the “mouse-scale simulations”, I cut all neuroscience collaboration with IBM because this is an unethical claim and it deceives the public.

What IBM allowed Modha to do here is not only wrong, but outrageous. They deceived millions of people.

Henry Markram
Blue Brain Project