Neuronion Blog: Brain theory, eBrain architecture & robot intelligence

SyNAPSE: IBM's brain

2011-08-19T08:23:00.003Z

Published by BBC on 19/08/11

IBM has developed a microprocessor which it claims comes closer than ever to replicating the human brain. The system is capable of "rewiring" its connections as it encounters new information, similar to the way biological synapses work. Researchers believe that that by replicating that feature, the technology could start to learn. Cognitive computers may eventually be used for understanding human behaviour as well as environmental monitoring. Click here for more...

Google and the Machine Age

2011-02-14T16:09:00.003Z

Published by New York Post on 13/02/11

An excellent article on the advances of Artificial Intelligence:

Dealing with uncertainty turned out to be more important than thinking with logical precision. We think of a clever argument or solution to a problem as one that contains a series of irrefutable logical steps and are impressed when someone can come up with such a sequence. But this is exactly what computers do well. The hard part is dealing with uncertainty, and choosing a good answer from among many possibilities. The fundamental tools of A.I. shifted from Logic to Probability in the late 1980s, and fundamental progress in the theory of uncertain reasoning underlies many of the recent practical advances...

Click here for more...

Blue Brain: A supercomputing project

2010-10-17T22:13:00.000Z

Published by TED on October 2009

"Henry Markram says the mysteries of the mind can be solved -- soon. Mental illness, memory, perception: they're made of neurons and electric signals, and he plans to find them with a supercomputer that models all the brain's 100,000,000,000,000 synapses."

Blind soldier 'sees' with his tongue

2010-03-16T10:43:00.004Z

Published by The Engineer on 16/03/10

"A British serviceman who lost his sight while serving in Iraq is using the BrainPort vision device in order to ‘see’ with his tongue. The new system — known as the BrainPort vision device — was developed by the Centre for Vision Restoration for the US Armed Forces Institute of Regenerative Medicine (AFIRM) and is being trialled in the UK by retired Lance Corporal, Craig Lundberg, who served with 2nd Battalion The Duke of Lancaster’s Regiment. Lundberg was hit by a rocket-propelled grenade in March 2007 while he was serving in Basra. As a result of the explosion his left eye had to be removed and his right eye was severely damaged, leaving him profoundly blind". Click for more...

How does the brain learn to see?

2010-03-01T10:13:00.003Z

"Pawan Sinha details his groundbreaking research into how the brain's visual system develops. Sinha and his team provide free vision-restoring treatment to children born blind, and then study how their brains learn to interpret visual data. The work offers insights into neuroscience, engineering and even autism."

[G.K. Comment: Life is like a pyramid. By grouping the small details available at every level of a pyramid, you reach the top. This is called abstraction. The way we learn is like a pyramid and this video proves how it works. Amazing! ]

IBM, EPFL & ETH to build 3D brain-density processors

2009-12-16T10:08:00.002Z

Published by The Register on 14/12/09

"Boffins in Switzerland have warned that increasingly powerful computer processors are set to guzzle the entire world electricity supply by the year 2100. They say that only 3D myria-core chips can save the day." Click for more...

Is quantum computing the future of image processing?

2009-12-16T09:43:00.006Z

Published by The Register on 15/12/09

"Google says it has developed a kind of quantum computer capable of identifying objects that appear in digital photos and videos. According to the company, the system outperforms the classical algorithms running across its current network of worldwide data centers. Hartmut Neven, Google technical lead manager for image recognition, recently unveiled the company's ongoing quantum computing work with a post to the company's research blog, saying he was due to demonstrate the technology at last week's Neural Information Processing Systems conference in Vancouver." Click for more...

[Image credit: http://abyss.uoregon.edu/~js/ast123/lectures/lec17.html]

Google Goggles brings image processing to the masses

2009-12-16T09:26:00.008Z

The recent release of Google Goggles brings sophisticated image processing algorithms to the masses for free. Just point your phone-camera onto something you are interested about and in no time you have all the information on your screen. Impressive! But how do they do it? The latest computer vision techniques can transform an image into a bag of words, which represent the main image features. This approach would make sense for Google because then they could use their normal search engine to index millions of images in no time. Just a guess! Anyway, enjoy the video below... it's a must see!

Simulated brain closer to thought

2009-04-23T13:54:00.004Z

Published by Jason Palmer - BBC on 22/04/09

A detailed simulation of a small region of a brain built molecule by molecule has been constructed and has recreated experimental results from real brains. The "Blue Brain" has been put in a virtual body, and observing it gives the first indications of the molecular and neural basis of thought and memory. Scaling the simulation to the human brain is only a matter of money, says the project's head. The work was presented at the European Future Technologies meeting in Prague. The Blue Brain project launched in 2005 as the most ambitious brain simulation effort ever undertaken. While many computer simulations have attempted to code in "brain-like" computation or to mimic parts of the nervous systems and brains of a variety of animals, the Blue Brain project was conceived to reverse-engineer mammal brains from real laboratory data and to build up a computer model down to the level of the molecules that make them up. Click for more...

Robot scientist 'Adam' solves genetic problems

2009-04-03T09:10:00.006Z

Published by Lewis Smith - The Times on 03/04/09

A robot has become the first of its kind to make a scientific discovery by solving a problem that human researchers have failed to crack for decades. The robot, called Adam, was able to work out where an important gene would be located and to develop experiments to prove its theory. It had been challenged to identify a gene in yeast for which its human counterparts had been searching since at least the 1960s. The robot, devised at Aberystwyth University, was able to identify the gene, which controls an enzyme crucial to the production of lysine, an amino acid essential to growth. It is thought that robots like Adam, and its successor, Eve, which is soon to be switched on at Aberystwyth, offer new hope in the battle against disease. Professor Ross King, who led the project, said that malaria and schistosomiasis, an infection caused by a parasitic worm, were among the diseases that robots should be able to help to defeat. Adam’s discovery, he said, was likely to play an important role in developing new treatments for fungal diseases such as athlete’s foot. [Click for more...]

CADIE: April fools or not?

2009-04-01T10:37:00.009Z

As you are reading these lines you have probably already read Google's April fools joke on CADIE (Cognitive Autoheuristic Distributed-Intelligence Entity), a self-conscious computer system. Good sense of humour you may say, or great imagination! But could this just be a fun way of introducing a new reality? Could Google be close to building the first self-conscious machine that passes the Turing test? What do you think? After all, if Google cannot make it who can?

Intelligent computers put to the test

2008-10-05T19:28:00.004Z

Published by The Observer on 05/10/2008

Can machines think? That was the question posed by the great mathematician Alan Turing. Half a century later six computers are about to converse with human interrogators in an experiment that will attempt to prove that the answer is yes. In the 'Turing test' a machine seeks to fool judges into believing that it could be human. The test is performed by conducting a text-based conversation on any subject. If the computer's responses are indistinguishable from those of a human, it has passed the Turing test and can be said to be 'thinking'. No machine has yet passed the test devised by Turing, who helped to crack German military codes during the Second World War. But at 9am next Sunday, six computer programs - 'artificial conversational entities' - will answer questions posed by human volunteers at the University of Reading in a bid to become the first recognised 'thinking' machine. If any program succeeds, it is likely to be hailed as the most significant breakthrough in artificial intelligence since the IBM supercomputer Deep Blue beat world chess champion Garry Kasparov in 1997. It could also raise profound questions about whether a computer has the potential to be 'conscious' - and if humans should have the 'right' to switch it off. Click here for more...

Team Stellar wins the MoD Grand Challenge

2008-08-20T16:58:00.005Z

Published by The Guardian on 19/08/2008

The Grand Challenge winner, announced today, was Team Stellar – a collaboration of small firms, researchers from Cranfield University and large industrial manufacturers. It beat off competition from 10 other teams whose creations included a swarm of quadropters (helicopters with four rotors), a scaled-down JCB lookalike and a mini flying saucer. The strange collection of craft were taking part in an ambitious competition to develop uncrewed surveillance vehicles that can help the military identify enemy positions in a town or city before sending in troops. The MoD earmarked £4.5m to stage the contest and develop the technologies for the battlefield. The teams competed over three days at Copehill Down, a mocked-up German village on Salisbury Plain that the army uses for training soldiers in house-to-house fighting. Click here for more...

[G.K Comment: What a challenge! It was such a great experience to be working with Team Stellar. Everybody worked incredibly hard, so it's a well deserved victory.]

IBM's new 'human brain' supercomputer

2008-06-06T08:28:00.006Z

Published by ITPro on 04/06/08

IBM says next week will see the release of a successor to the world's fastest supercomputer Blue Gene, which it claims will have the calculating capability of the average human brain. The Blue Gene/P will be capable of operating at 'petascale' speeds (one quadrillion operations per second). This a significant jump in processing power from the previous version, the Blue Gene/L which was 'only' capable of terascale speeds (one trillion operations per second).The news was announced by Nicholas M. Donofrio, IBM's soon to be retired executive vice president for Innovation and Technology, at IBM's first European Information on Demand conference in the Netherlands. He was making a speech on how innovation and the ability to transform invention into products, services, methods, processes and policies was a vital part of business in the past, present and future. Click for more...

Computer model knows what you're thinking

2008-05-30T09:48:00.005Z

Published by Kerri Smith on Nature journal (29/05/08)

A computer model has been developed that can predict what word you are thinking of. The model may help to resolve questions about how the brain processes words and language, and might even lead to techniques for decoding people’s thoughts. Researchers led by Tom Mitchell of Carnegie Mellon University in Pittsburgh, Pennsylvania, 'trained' a computer model to recognize the patterns of brain activity associated with 60 images, each of which represented a different noun, such as 'celery' or 'aeroplane'. The team started with the assumption that the brain processes words in terms of how they relate to movement and sensory information. Words such as 'hammer', for example, are known to cause movement-related areas of the brain to light up; on the other hand, the word 'castle' triggers activity in regions that process spatial information. Click for more...

Free choice activates a decision circuit between frontal and parietal cortex

2008-05-29T00:18:00.004Z

Published by Bijan Pesaran, Matthew J. Nelson & Richard A. Andersen on Nature journal (16/04/08)

We often face alternatives that we are free to choose between. Planning movements to select an alternative involves several areas in frontal and parietal cortex that are anatomically connected into long-range circuits. These areas must coordinate their activity to select a common movement goal, but how neural circuits make decisions remains poorly understood. Here we simultaneously record from the dorsal premotor area (PMd) in frontal cortex and the parietal reach region (PRR) in parietal cortex to investigate neural circuit mechanisms for decision making. We find that correlations in spike and local field potential (LFP) activity between these areas are greater when monkeys are freely making choices than when they are following instructions. We propose that a decision circuit featuring a sub-population of cells in frontal and parietal cortex may exchange information to coordinate activity between these areas. Cells participating in this decision circuit may influence movement choices by providing a common bias to the selection of movement goals. Click for more...

Neuroscience: Brain control of a helping hand

2008-05-28T23:56:00.005Z

Published by John F. Kalaska on Nature journal (28/05/08)

Paralysed patients would benefit if their thoughts could become everyday actions. The demonstration that monkeys can use brain activity for precise control of an arm-like robot is a step towards that end. Strokes, spinal-cord injuries and degenerative neuromuscular disease all cause damage that can severely compromise the ability of patients to use their muscles. The loss of mobility and independence that results from such motor deficits takes a devastating toll on their quality of life. Medical research is striving on many fronts to reverse the disease or injury state of such patients. Meanwhile, other approaches are needed to enhance their quality of life. Often, the patient's condition leaves intact parts of the cerebral cortex involved in voluntary motor control, including the primary motor cortex, premotor cortex and posterior parietal cortex. These patients are still able to produce the brain activity that would normally result in voluntary movements, but their condition prevents those signals from either getting to the muscles or activating them adequately. In such cases, one possible solution is to let the subjects think about what they would like to do as if they were mentally rehearsing the desired actions, record the resulting brain activity, and use those signals to control a robotic device. The development of such brain–machine interfaces (BMIs), or neuroprosthetic controllers, is being pursued in several laboratories. Click for more...

Hierarchical Temporal Memory Lecture - Conference on Cognitive Computing

2008-04-20T09:30:00.011Z

By Jeff Hawkins of Numenta

Click here to view the video on Google...

The man with two brains

2008-03-19T17:07:00.005Z

Published on E&T magazine of IET by Paul Dempsey

Jeff Hawkins sired the personal digital assistant and today’s smartphones as the founder of Palm Computing. But, frankly, this was never much of a priority for him. Even as a young engineer at Intel, he was nagging microprocessor pioneer Ted Hoff to let him investigate parallels between computing and the human brain. Back in the 1970s, Hoff said no – a decision Hawkins now agrees with – but as science and theory advanced, he returned to his obsession. In 2002, Hawkins set up the Redwood Neuroscience Institute, concentrating on brain theory, and in 2004, launched the start-up Numenta, which is developing a computing architecture called Hierarchical Temporal Memory (HTM). At this year’s International Solid State Circuits Conference (ISSCC), Hawkins described prototype HTM visual recognition systems, addressing a task that remains hugely challenging for computers. But it is one that the animal brain finds quite straightforward. It is one reason why a growing body of people, such as Hawkins, are looking more closely at the structure of the brain. Click fore more...

It thinks... therefore...

2008-03-19T16:59:00.003Z

Published on E&T magazine of IET by Chris Edwards

Research into machine consciousness is leading engineers to re-evaluate the relevance of philosophy, discovers Chris Edwards. Inventor Ray Kurzweil has a dream. And he intends to live to see it. He claims he takes a daily cocktail of pills to help make sure he is around to witness the creation of the first artificial brain: something he reckons will happen by the end of the 2020s. One of Kurzweil’s hopes is that this will make it possible to cheat death: we could upload our consciousness into the machine and remain conscious just as long as the computer receives power and maintenance. But the prospect raises a conundrum: would that machine actually be conscious? Would it think? How would we know? Even if it told us it could see and feel, would we believe it? Or would we consider it no more than a simulation of consciousness, where the lights are on but nobody is home? Questions like these are leading engineers to consider whether it is time for the discipline to merge with philosophy, as engineering by itself will be unable to provide the answers. Philosophy as such still struggles with the questions. We don’t really know what intelligence is and whether consciousness is effectively synonymous with it. But the quest to uncover consciousness in an artificial entity may provide clues that classic philosophical introspection has not managed to uncover. Click for more...

Chemical brain controls nanobots

2008-03-11T12:06:00.004Z

Published by BBC on 11/03/2008

A tiny chemical "brain" which could one day act as a remote control for swarms of nano-machines has been invented.
The molecular device - just two billionths of a metre across - was able to control eight of the microscopic machines simultaneously.
Writing in Proceedings of the National Academy of Sciences, scientists say it could also be used to boost the processing power of future computers. Many experts have high hopes for nano-machines in treating disease. "If you want to remotely operate on a tumour you might want to send some molecular machines there," explained Dr Anirban Bandyopadhyay of the National Institute for Materials Science, Tsukuba, Japan. "But you cannot just put them into the blood and [expect them] to go to the right place." Dr Bandyopadhyay believes his device may offer a solution. One day they may be able to guide the nanobots through the body and control their functions, he said. "That kind of device simply did not exist; this is the first time we have created a nano-brain". Click for more...

Plan to teach baby robot to talk

2008-03-02T22:36:00.003Z

Published by BBC on 28/02/2008

A university in Devon is preparing to find out if a baby robot can be taught to talk. Staff at the University of Plymouth will work with a 1m-high (3ft) humanoid baby robot called iCub. Over the next four years robotics experts will work with language development specialists who research how parents teach children to speak. Their findings could lead to the development of humanoid robots which learn, think and talk. The project is believed to be the first of its kind in the world and typical experiments with the iCub robot will include activities such as inserting objects of various shapes into the corresponding holes in a box, serialising nested cups and stacking wooden blocks. Click fore more...

Visionary Research: Teaching Computers to See Like a Human

2008-02-28T15:58:00.005Z

Published 20/02/08 on Scientific American by Larry Greenemeier

For all their sophistication, computers still can't compete with nature's gift—a brain that sorts objects quickly and accurately enough so that people and primates can interpret what they see as it happens. Despite decades of development, computer vision systems still get bogged down by the massive amounts of data necessary just to identify the most basic images. Throw that same image into a different setting or change the lighting and artificial intelligence is even less of a match for good old gray matter.

These shortcomings become more pressing as demand grows for security systems that can recognize a known terrorist's face in a crowded airport and car safety mechanisms such as a sensor that can hit the brakes when it detects a pedestrian or another vehicle in the car's path. Seeking the way forward, Massachusetts Institute of Technology researchers are looking to advances in neuroscience for ways to improve artificial intelligence, and vice versa. The school's leading minds in both neural and computer sciences are pooling their research, mixing complex computational models of the brain with their work on image processing. Click for more...

Harnessing Digital Evolution

2008-01-21T11:09:00.001Z

The following article has been published in the IEEE Computer magazine (January 2008), describing the evolution of digital organisms. It makes a very interesting reading and it is definitely one of the most promising areas of computer design & robotics. Look out for it!

Abstract

In digital evolution, self-replicating computer programs—digital organisms—experience mutations and selective pressures, potentially producing computational systems that, like natural organisms, adapt to their environment and protect themselves from threats. Such organisms can help guide the design of computer software. Click here for more information...

Citation: Philip McKinley, Betty H.C. Cheng, Charles Ofria, David Knoester, Benjamin Beckmann, Heather Goldsby, "Harnessing Digital Evolution," Computer, vol. 41, no. 1, pp. 54-63, Jan., 2008

Words of wisdom for scientists...

2008-01-05T20:19:00.000Z

A. "...intuition is often the biggest obstacle to discovering the truth"
B. "...the best solutions to scientific problems are simple and elegant"
Jeff Hawkins, "On Intelligence" p.32, p34

Baby's errors are crucial first step for a smarter robot

2007-12-13T15:08:00.002Z

Published on 05.10.07 by Michael Reilly and David Robson
on NewScientist Magazine issue 2624

When your software crashes, you probably restart your PC and hope it doesn't happen again, or you get the bug fixed. But not Rachel Wood. When a program she was testing screwed up a task that a 2-year-old would find easy, she was elated. The reason for this seemingly perverse reaction is that Wood's program didn't contain a bug, but had committed a famous cognitive goof identified by the psychology pioneer Jean Piaget. Known as the A-not-B error, it is made by babies between 7 and 12 months old and is seen as one of the hallmarks of fledgling human intelligence. Wood's robot has a brain far simpler than a baby's. But unravelling the events that led to this human-like behaviour - something that is easier to do in a computer program than a real brain - could help improve our understanding of artificial intelligence. Click for more...

[G.K Comment: Robots with built-in trial & error functionality for fixing "bugs"... that's the future.]

Essential circuits of cognition: The brain’s basic operations, architecture, and representations

2007-11-26T01:21:00.000Z

Published by Richard Granger (University of California Irvine and Dartmouth College) on BrainEngineering.com

The goals of artificial intelligence have always been twofold: i) formal explanation of the mechanisms underlying human (and animal) intelligence and ii)construction of powerful intelligent artifacts based on those mechanisms. The latter engineering goal may pragmatically benefit from the former scientific one: extant face recognition systems and automated telephone operators might have been considered the best possible mechanisms were it not for our own abilities. The only reason that we know that these industrial systems can be outperformed is that humans do so. Biological systems achieve their cognitive capabilities solely through brain mechanisms: the physiological operation of anatomical circuitries. Brain circuits are circuits; that is, they can be understood in computational terms. An explosion of knowledge in neuroscience and related fields is revealing the data crucial for characterizing the layout and properties of these circuits. Click for more... (.pdf)

Automated Killers and the Computing Profession

2007-11-22T10:40:00.000Z

Published by Noel Sharkey of the University of Sheffield on Computer.org

When will we realize that our artificial-intelligence and autonomous-robotics research projects have been harnessed to manufacture killing machines? This is not terminator-style science fiction but grim reality: South Korea and Israel have both deployed armed robot border guards, while other nations—including China, India, Russia, Singapore, and the UK—increasingly use military robots. Currently, the biggest player, the US, has robots playing an integral part in its Future Combat Systems project, with spending estimated to exceed $230 billion. The US military has massive and realistic plans to develop unmanned vehicles that can strike from the air, under the sea, and on land. The US Congress set a goal in 2001 for one-third of US operational ground combat vehicles to be unmanned by 2015. More than 4,000 robots presently serve in Iraq, with others deployed in Afghanistan. The US military will spend $1.7 billion on more ground-based robots over the next five years, several of which will be armed and dangerous. Click for more...

[G.K Comment: Computer ethics is an extremely complex issue that is going to play a major role in the months and years to come, as more and more robots are deployed in the battlefield. Autonomous systems are always going to fail under specific circumstances regardless of how intelligent they become. But who is responsible if a robot unfairly causes a casualty? This article raises many valid questions that all computer scientists should be concerned about.]

Scientific Revolution: Skin transformed into stem cells through reprogramming!

2007-11-20T19:27:00.000Z

Published by BBC on 20/11/2007

Human skin cells have been reprogrammed by two groups of scientists to mimic embryonic stem cells with the potential to become any tissue in the body. The breakthrough promises a plentiful new source of cells for use in research into new treatments for many diseases. Crucially, it could mean that such research is no longer dependent on using cells from human embryos, which has proved highly controversial. The US and Japanese studies feature in the journals Science and Cell. Until now only cells taken from embryos were thought to have an unlimited capacity to become any of the 220 types of cell in the human body - a so-called pluripotent state. Click for more...

[G.K Comment: You may wonder why such an article appears on an eBrain blog. Well it was suspected for many years that cells are generic structures that can be programmed to perform different body functions. Now with this revolutionary discovery, scientists have proven that theory to be true. Likewise neurons are generic structures that get programmed differently for vision, speech, abstract thinking etc... Only if we can decode the way they process and exchange information then one of the few remaining unsolved mysteries of science may come to light.]

Future directions in computing

2007-11-14T09:42:00.000Z

Published on 14/11/2007 by BBC

Silicon electronics are a staple of the computing industry, but researchers are now exploring other techniques to deliver powerful computers. Quantum computers are able to tackle complex problems. A quantum computer is a theoretical device that would make use of the properties of quantum mechanics, the realm of physics that deals with energy and matter at atomic scales. In a quantum computer data is not processed by electrons passing through transistors, as is the case in today's computers, but by caged atoms known as quantum bits or Qubits. "It is a new paradigm for computation," said Professor Artur Ekert of the University of Oxford. "It's doing computation differently." Click for more...

[G.K Comment: This article lists some new technologies that could potentially replace silicon in computers. They are all very exciting prospects that could have a positive effect on the way eBrains are designed in the future.]

Belief Propagation and Wiring Length Optimization as Organizing Principles for Cortical Microcircuits

2007-10-16T13:25:00.001Z

Published by Dileep George and Jeff Hawkins

This paper explores how functional and anatomical constraints and resource optimization could be combined to obtain a canonical cortical micro-circuit and an explanation for its laminar organization. We start with the assumption that cortical regions are involved in Bayesian Belief Propagation. This imposes a set of constraints on the type of neurons and the connection patterns between neurons in that region. In addition there are anatomical constraints that a region has to adhere to. There are several different configurations of neurons consistent with both these constraints. Among all such configurations, it is reasonable to expect that Nature has chosen the configuration with the minimum wiring length. We cast the problem of finding the optimum configuration as a combinatorial optimization problem. A near-optimal solution to this problem matched anatomical and physiological data. As the result of this investigation, we propose a canonical cortical micro-circuit that will support Bayesian Belief Propagation computation and whose laminar organization is near optimal in its wiring length. We describe how the details of this circuit match many of the anatomical and physiological findings and discuss the implications of these results to experimenters and theorists. Click fore more (.pdf)

Attention and consciousness: two distinct brain processes

2007-10-10T16:00:00.000Z

Published by Christof Koch and Naotsugu Tsuchiya on Neuron.org

The close relationship between attention and consciousness has led many scholars to conflate these processes. This article summarizes psychophysical evidence, arguing that top-down attention and consciousness are distinct phenomena that need not occur together and that can be manipulated using distinct paradigms. Subjects can become conscious of an isolated object or the gist of a scene despite the near absence of top-down attention; conversely, subjects can attend to perceptually invisible objects. Furthermore, top-down attention and consciousness can have opposing effects. Such dissociations are easier to understand when the different functions of these two processes are considered. Untangling their tight relationship is necessary for the scientific elucidation of consciousness and its material substrate. Click for more... (.pdf)

Theory of Brain Function, Quantum Mechanics and Superstrings

2007-10-05T15:08:00.000Z

Published by D.V. Nanopoulos

"Theory of brain function, quantum mechanics, and superstrings are three fascinating topics, which at first look bear little, if any at all, relation to each other. Trying to put them together in a cohesive way, as described in this task, becomes a most demanding challenge and unique experience. The main thrust of the present work is to put forward a, maybe, foolhardy attempt at developing a new, general, but hopefully scientifically sound framework of Brain Dynamics, based upon some recent developments, both in (sub)neural science and in (non)critical string theory. I do understand that Microtubules are not considered by all neuroscientists, to put it politely, as the microsites of consciousnes." Click for more...

.
[G.K Comment: Interesting... but is it all true? More to follow...]

Neural Networks vs. HTMs Part 2: From the OnIntelligence Forum

2007-09-19T17:04:00.000Z

Quote 1:
"HTMs are similar to Bayesian networks; however, they differ from most Bayesian networks in the way that time, hierarchy, action, and attention are used. An HTM can be considered a form of Bayesian network where the network consists of a collection of nodes arranged in a tree-shaped hierarchy. Each node in the hierarchy self-discovers a set of causes in its input through a process of finding common spatial patterns and then finding common temporal patterns. Unlike many Bayesian networks, HTMs are self-training, have a well-defined parent/child relationship between each node, inherently handle time-varying data, and afford mechanisms for covert attention."

Quote 2:
"HTM's are a type of neural network. But in saying that, you should know that there are many different types of neural networks (single layer feedforward network, multi-layer network, recurrant, etc). 99% of these types of networks tend to emulate the neurons, yet don't have the overall infrastructure of the actual cortex. Additionally, neural networks tend not to deal with temporal data very well, they ignore the hierarchy in the brain, and use a different set of learning algorithms that our implementation. But, in a nutshell, HTMs are built according to biology. Whereas neural networks ignore the structure and focus on the emulation of the neurons, HTMs tend to focus on the structure and ignores the emulation of the neurons. I hope that clears things up.
_________________
Phillip B. Shoemaker Director
Developer Services Numenta, Inc."

Neural Networks vs. HTMs: What does Jeff Hawkins think?

2007-09-14T13:59:00.000Z

Published by Evan Ratliff on Wired.com

Neural networks rose to prominence in the 1980s. But despite some successes in pattern recognition, they never scaled to more complex problems. Hawkins argues that such networks have traditionally lacked “neuro-realism”: Although they use the basic principle of inter-connected neurons, they don’t employ the information-processing hierarchy used by the cortex. Whereas HTMs continually pass information up and down a hierarchy, from large collections of nodes at the bottom to a few at the top and back down again, neural networks typically send information through their layers of nodes in one direction — and if they send information in both directions, it’s often just to train the system. In other words, while HTMs attempt to mimic the way the brain learns — for instance, by recognizing that the common elements of a car occur together — neural networks use static input, which prevents prediction. Click for more...

Learn Like A Human

2007-08-31T12:53:00.000Z

Published by Jeff Hawkins
IEEE Spectrum magazine, April 2007

By the age of five, a child can understand spoken language, distinguish a cat from a dog, and play a game of catch. These are three of the many things humans find easy that computers and robots currently cannot do. Despite decades of research, we computer scientists have not figured out how to do basic tasks of perception and robotics with a computer. Our few successes at building "intelligent" machines are notable equally for what they can and cannot do. Computers, at long last, can play winning chess. But the program that can beat the world champion can't talk about chess, let alone learn backgammon. Today's programs-at best-solve specific problems. Where humans have broad and flexible capabilities, computers do not. Perhaps we've been going about it in the wrong way. Click for more...

[G.K Comment: An excellent article by Jeff Hawkins on Hierarchical Temporal Memory. ]

“Forward” software engineering: "Brain-like software architecture... Confessions of an ex-neuroscientist"

2007-08-31T09:30:00.000Z

Published by Bill Softky

Which comes first: the problem or the solution?

Reverse engineering starts with hardware, works backward. Usually only succeeds if problem is understood. “Forward” software engineering starts with the problem, and saves hardware for last. Click for more... (.ppt file)

[G.K Comment: An interesting presentation by Bill Softky on how we could use forward software engineering to solve hard problems, such the "brain" one.]

Neural Darwinism

2007-08-14T07:53:00.000Z

Published by David Cofer of MindCreators.com

"There are a multitude of different theories on the mind. Many more than have been discussed in this document. However, of all the ones I have seen before, I feel that this one offers the greatest hope of coming up with a real, working understanding of the science and neurobiology of how the mind works and what consciousness really is. Its author, Gerald Edelman, is a former Nobel laureate who was instrumental in cracking the mystery of how our immune systems work. After that he turned his attention to something far more difficult, attempting to understand how the neurobiology of the brain forms the mind. The main thrust of his theory of neural Darwinism is that the brain is a somatic selection system similar to evolution, and not an instructional system. (Somatic means that is over the time scale of your body instead of being on the time scale of evolution.)" Click for more...

MindCreators.com

2007-08-13T18:59:00.000Z

Published by David Cofer of MindCreators.com

"I built this website to document the progress on my research into machine intelligence. Specifically, I am currently focused on building a computer simulation that behaves like a common, everyday insect using neural networks. Most researchers in the field of Artificial Intelligence (AI) try to understand and replicate human thought and abilities. I believe this is a mistake. You must start small and work your way up the evolutionary ladder, not immediately start with the most complicated thing in the known universe. Insects seem pretty stupid when compared with humans, but they are capable of a variety of intelligent, adaptive behaviors in a very unpredictable environment. And that is something that no man made system is yet capable of emulating. Also, when you get groups of insects working together in a cooperative manner they are capable of almost miraculous accomplishments. Once we begin to understand how these tiny brains work to produce such incredible behaviors then we will be able to harness that power for useful purposes. " Click for more...

[G.K Comment: David Cofer takes the approach of simulating a relatively simple insect's brain and then following the evolutionary ladder to understand more complex brain formations. Although this could make sense for solving some other real life problems, I believe that understanding an insect's brain is far more difficult than understanding a human baby's brain! I mean it! The reason is that human beings are the most incapable living organisms the moment of their birth. We also take a long time before we can perform even the most basic tasks such as walking & talking. In my opinion, we can develop a functional brain that looks nothing like any existing organism, as long as it can sense its environment and gain knowledge about it without pre-programming.]

Hierarchical Temporal Memory: Concepts, Theory, and Terminology

2007-07-24T21:52:00.000Z

Published by Jeff Hawkins and Dileep George, Numenta Inc.

There are many things humans find easy to do that computers are currently unable to do. Tasks such as visual pattern recognition, understanding spoken language, recognizing and manipulating objects by touch, and navigating in a complex world are easy for humans. Yet, despite decades of research, we have no viable algorithms for performing these and other cognitive functions on a computer. In a human, these capabilities are largely performed by the
neocortex. Hierarchical Temporal Memory (HTM) is a technology that replicates the structural and algorithmic properties of the neocortex. HTM therefore offers the promise of building machines that approach or exceed human level performance for many cognitive tasks. Click for more... (.pdf file)

Jeff Hawkins: Brain science is about to fundamentally change computing

2007-07-24T20:58:00.000Z

Click here to watch the video...

About this Talk
To date, there hasn't been an overarching theory of how the human brain really works, Jeff Hawkins argues in this compelling talk. That's because we still haven't defined intelligence accurately. But one thing's for sure, he says: The brain isn't like a powerful computer processor. It's more like a memory system that records everything we experience and helps us predict, intelligently, what will happen next. Bringing this new brain science to computer devices will enable powerful new applications -- and it will happen sooner than you think.

Evolution in Your Brain: A biological point of view from a great nobelist

2007-07-24T16:43:00.000Z

Published by Susan Kruglinski on the Discover magazine

Some of the most profound questions in science are also the least tangible. What does it mean to be sentient? What is the self? When the discussion turns to these imponderables, many minds defer rather than get mired in such muddy issues. Neuroscientist Gerald Edelman dives right in. A physician and cell biologist who won a Nobel Prize for his work on the structure of antibodies, Edelman is now obsessed with the enigma of human consciousness—except he doesn’t see it as a mystery. In Edelman’s grand theory of the mind, consciousness is a biological phenomenon. The developing brain undergoes its own process, similar to natural selection: Neurons proliferate and form connections in infancy; experience weeds out the useless from the useful, molding the adult brain in sync with its environment. Click for more...

Consciousness and Computers

2007-07-19T09:49:00.001Z

Published by Neville Holmes (University of Tasmania) on "Computer.org"
(Computer IEEE Magazine, July 2007)

Recently, the cover of an issue of Time (29 Jan. 2007) that appeared to promote ancient phrenology caught my attention. Closer inspection showed it to be a "Mind & Body Special Issue." This surprised me because The Economist's special Christmas/New Year issue (23 Dec. 2006) had featured the supplement "A Survey of the Brain." So I bought the copy of Time to compare with the earlier issue of The Economist. Although both started with a signed introduction, the rest of the content was stylistically opposed. The Economist had five anonymous reports compiled from interviews with, and quotations of, experts, the lot decorated with a few drawings and diagrams. Time had 10 richly illustrated essays informed and often written by experts, and followed by a short puzzle section. The contest, if indeed it was one, seemed to be a standoff, like a saber versus a shillelagh. The computing profession is relevant here. Click for more...

[G.K Comment: As Neville Holmes says: "The conscious mind is not mysterious, just misunderstood".]

Comparison of the brain and a computer

2007-07-17T22:40:00.000Z

Published in Wikipedia

Much interest has been focused on comparing the brain with computers. A variety of obvious analogies exist: for example, individual neurons can be compared with a microchip, and the specialised parts of the brain can be compared with graphics cards and other system components. However, such comparisons are fraught with difficulties. Perhaps the most fundamental difference between brains and computers is that today's computers operate by performing often sequential instructions from an input program, while no clear analogy of a program appears in human brains. The closest equivalent would be the idea of a logical process, but the nature and existence of such entities are subjects of philosophical debate. Given Turing's model of computation, the Turing machine, this may be a functional, not fundamental, distinction. However, Maass and Markram have recently argued that "in contrast to Turing machines, generic computations by neural circuits are not digital, and are not carried out on static inputs, but rather on functions of time" (the Turing machine computes computable functions). Click for more...

Robot unravels mystery of walking

2007-07-12T22:57:00.000Z

Published on 12/07/2007 by BBC

Roboticists are using the lessons of a 1930s human physiologist to build the world's fastest walking robot. Runbot is a self-learning, dynamic robot, which has been built around the theories of Nikolai Bernstein. "Getting a robot to walk like a human requires a dynamic machine," said Professor Florentin Woergoetter. Runbot is a small, biped robot which can move at speeds of more than three leg lengths per second, slightly slower than the fastest walking human. Click for more...

The hack of the century: Greek mobile wiretap scandal unpicked

2007-07-12T19:23:00.000Z

Published on 11/07/2007
by John Leyden on "The Register"

More details have emerged on how Vodafone's Greek network was bugged three years ago to spy on top government officials.
To recap one of the most extraordinary wiretapping scandals of the post-Cold War era: eavesdroppers tapped the mobile phones of Greek Prime Minister Costas Karamanlis, cabinet ministers and security officials for about nine months between June 2004-Mar 2005 around the time of the Athens Olympics.

The mobile phones of about 100 people, whose ranks include journalists and Arabs living in Greece, as well as the country's political and security elite and a US embassy worker, were monitored after snooping software was illegally installed on the systems of Vodafone Greece. Click for more...

How To Think About Cognitive Systems: Requirements and Designs

2007-07-09T19:08:00.000Z

Published by Aaron Sloman,

School of Computer Science,

The University of Birmingham, UK

http://www.cs.bham.ac.uk/~axs/

Much early thinking about AI was about forms of representation, the knowledge expressed, and the algorithms to operate on those representations. Later there was much in-fighting between factions promoting particular forms of representation and associated algorithms, e.g. neural computations, evolutionary algorithms, reactive behaviours, physics-inspired dynamical systems. More recently, attention has turned to ways of combining different mechanisms, formalisms and kinds of knowledge within a single multi-functional system, i.e. within one architecture. Minsky's Society of Mind was a major example. Click for more...

Grand Challenge 5 (GC-5): Architecture of Brain and Mind

2007-07-07T15:43:00.000Z

Integrating high level cognitive processes with brain mechanisms and functions in a working robot.

Click for more...

Rat-brained robot thinks like the real thing

2007-07-05T19:09:00.000Z

Published 04/07/07 by Duncan Graham-Rowe on "NewScientistTech"

A robot controlled by a simulated rat brain has proved itself to be a remarkable mimic of rodent behaviour in series of classic animal experiments. The robot's biologically-inspired control software uses a functional model of "place cells". These are neurons in an area of the brain called the hippocampus that help real rats to map their environment. They fire when an animal is in a familiar location. Alfredo Weitzenfeld, a roboticist at the ITAM technical institute in Mexico City, carried out the work by reprogramming an AIBO robot dog, made by Japanese firm Sony, with the rat-inspired control software. Click for more...

[G.K Comment: Please allow me to say that simulating animal brains by creating highly complex software is not the way forward. The question is how can we create a brain platform that can program itself in a complex way(!)... i.e. in the same way that a baby evolves into an adult. Does that make sense?"]

Brain - some basic concepts by IBM

2007-07-03T09:53:00.000Z

A very good webpage by IBM, listing some basic scientific concepts on the way the human brain works. Click here for more...

Supercomputer to build 3D brain

2007-06-29T10:33:00.000Z

Published 07/06/05 By BBC

The neocortex is organised into thousands of columns of neurons. Neuroscientists are to build the most detailed model of the human brain with the help of an IBM supercomputer. Experts at the École Polytechnique Fédérale de Lausanne, Switzerland, will spend the next two years creating a 3D simulation of the neocortex. Click for more...

Einstein(s) needed to simulate the human brain. Job specs below...

2007-06-28T15:40:00.000Z

Published 28/06/07 By Bill Softky on "The Register"

So the tinkerers can't do the math, and the boffins can't tinker. To break that logjam we need an Einstein of engineering. He would be part hacker, part statistician: a special blend of mathematical genius, programmer, and tinkerer. And hopefully a businessman too. Click for more...

[G.K Comment: Bill Softky has a point here. But surely with the vast amount of research that goes into the sector of simulating the human brain on a machine... you would think that the result would come as a result of teamwork rather than individual excellence. Let's wait and see...]

Statistical Inference Software - The future is here

2007-06-28T13:49:00.000Z

Published 25/05/07 By Bill Softky on "The Register"
...The fact is, what allowed Stanford's "Stanley" car (in the DARPA Grand Challenge competition) to cross a hundred miles of desert dirt unaided was not mechanical wizardry or "intelligence," but the careful application of statistical inference and software design to merging three kinds of sensor data: GPS coordinates, laser range-finders, and video color/texture signals. The secret sauce was in detecting the road fifty metres ahead and avoiding large obstacles, and even that apparently simple task consumed a year of the lives of a dozen computer science graduate students. It's hard to imagine Joe Tinkerer doing such things at home with his Mindstorms kit... Click here for the full article...

[G.K Comment: Well, another excellent article by Bill Softky. My favourite part of the article is the brief explanation of why statistical inference software is what really matters in some robot systems. I can't wait to see what other new technologies will emerge from the DARPA Urban Challenge which is due in late 2007.]

The flexi-laws of physics

2007-06-28T12:46:00.000Z

Published by Paul Davies on 30/06/2007
New Scientist Magazine issue 2610

SCIENCE WORKS because the universe is ordered in an intelligible way. The most refined manifestation of this order is found in the laws of physics, the fundamental mathematical rules that govern all natural phenomena. One of the biggest questions of existence is the origin of those laws: where do they come from, and why do they have the form that they do?

Until recently this problem was considered off-limits to scientists. Their job was to discover the laws and apply them, not inquire into their form or origin. Now the mood has changed. One reason for this stems from the growing realisation that the laws of physics possess a weird and surprising property: collectively they give the universe the ability to generate life and conscious beings, such as ourselves, who can ponder the big questions.

If the universe came with any old rag-bag of laws, life would almost certainly be ruled out. Indeed, changing the existing laws by even a scintilla could have lethal consequences. For example, if protons were 0.1 per cent heavier than neutrons, rather than the other way about, all the protons coughed out of the big bang would soon have decayed into neutrons. Without protons and their crucial electric charge, atoms could not exist and chemistry would be impossible.

Physicists and cosmologists know many such examples of uncanny bio-friendly "coincidences" and fortuitous fine-tuned properties in the laws of physics. Like Baby Bear's porridge in the story of Goldilocks, our universe seems "just right" for life. It looks, to use astronomer Fred Hoyle's dramatic description, as if "a super-intellect has been monkeying with physics". So what is going on?

A popular way to explain the Goldilocks factor is the multiverse theory. This says that a god's-eye-view of the cosmos would reveal a patchwork quilt of universes, of which ours is but an infinitesimal fragment. Crucially, each patch, or "universe", comes with its own distinctive set of local by-laws. Maybe the by-laws are assigned randomly, as in a vast cosmic lottery. It is then no surprise that we find ourselves living in a patch so well suited to ...

Software engineers – the ultimate brain scientists?

2007-05-26T14:59:00.000Z

Published 17/10/03 By Bill Softky on "The Register"

Can software engineers hope to create a digital brain? Not before understanding how the brain works, and that's one of the biggest mysteries left in science. Brains are hugely intricate circuits of billions of elements. We each have one very close by, but can't open it up: it's the ultimate Black Box. Click for more...

[G.K Comment: What do you think? Can a computer simulate the human brain? Can a robot start making sensible conclusions and even start having a high-level discussion with a human? This article answers only some of the questions on this very debatable issue. As a software engineer I believe it can be done. Let's discuss...]

Design patterns for a Black Box Brain?

2007-05-25T14:14:00.000Z

Published 20/10/03 By Bill Softky on "The Register"

The bad news is that biologists are very far from figuring out the grand mystery of the brain. The good news is that software engineers might get there first. [...] What we desperately need - and what software and signal processing can help us with - is a theory of what a brain ought to do. A human brain is a black box with a million wires coming in and half a million going out; a rat's brain is smaller, with fewer wires, but faces the same basic signal-processing problems: what kind of input patterns can it expect, and how can it deal with them? Click for more...

[G.K Comment]: Without a doubt, the most interesting article I have ever read. It is exactly what my favourite research topic is all about... i.e. using software to create a human-like brain. Science finction? ...well it's only 2 years away I say. Let's see...

How Google translates without understanding!

2007-05-20T14:30:00.000Z

Published 15/05/07 By Bill Softky on "The Register"

After just a couple years of practice, Google can claim to produce the best computer-generated language translations in the world - in languages their boffin creators don't even understand.

Last summer, Google took top honors at a bake-off competition sponsored by the American agency NIST between machine-translation engines, besting IBM in English-Arabic and English-Chinese. The crazy part is that no one on the Google team even understands those languages.... the automatic-translation engines they constructed triumphed by sheer brute-force statistical extrapolation rather than "understanding". Click for more...

[G.K Comment: I urge every one of you to try and understand this article even if you are not a software engineer. Google has proven that the time when machines will become more intelligent than humans is not very far away.]

Miracles of Nature - Lyre Bird - David Attenborough

2006-11-28T14:26:00.000Z

If you thought that parrots are the best imitators in nature then think again! The video below is presented by Sir David Attenborough:

http://www.youtube.com/watch?v=WuFyqzerHS8