Robotic companions in the news

There was a minor flurry of media activity a week or so ago concerning the ALIZ-E project, just after the university put out a press release:

-> "Robot Companions to Befriend Sick Kids at European Hospital" in the IEEE Spectrum magazine.

-> "Cyber Sensitive: Therapeutic Buddy Bots Get Emotional" in Scientific American.

-> And a bit closer to home, is "Robots developed in Plymouth to befriend sick children" on the BBC Devon News website.

In a somewhat surreal event, we were also invited for a radio interview, in which our Nao robot was a speaking guest!

There seems to be a common picture with all of these stories (probably because it appears on the ALIZ-E project homepage) - at least it's a good one :-)

New low-power MRI machine

As reported in January's issue of the IEEE Spectrum, what is essentially a very low power MRI (magnetic resonance imaging) machine has produced its first images of a human brain. Whereas a standard MRI machine produces magnetic fields of around 1.5 tesla, this new version produces only around 46 microtesla - an over thirty thousand-fold reduction, and a field apparently comparable in strength to the earths' magnetic field. This reduction in power results in a slightly different method for producing the images.

In a standard MRI machine, a strong magnetic field is used to align the proton in each of the hydrogen atoms before using an RF pulse to knock them out of alignment. As they snap back into alignment with the magnetic field, they emit a signal which can be detected and used to create a 3D image. In the new version, the very small magnetic field isn't enough to align the protons, so a short duration (1 second) magnetic pulse of slightly higher magnitude (30 millitesla). The resulting signals are very small, so an array of highly sensitive magnetometers are used (so-called superconducting quantum interference devices, or SQUIDS). A hugely important additional advantage of using these SQUIDS is that they are also used in the MEG (magnetoencephalography) imaging technique. This potential for MRI and MEG using the same machine raises the intriguing possibility of producing simultaneous structural images (using the MRI) and brain activation maps (using the MEG).

One other major advantage of using this low-power MRI technique is its potential to image tumors. Due to the subtle differences between cancerous and non-cancerous tissue, the differences are not readily captured by standard MRI pictures - whereas the low-power version can. Furthermore, the possibility arises of using this type of imaging during operations themselves, as the very low magnetic fields used would not interfere with the use of metal surgical implements. As with any newly developed technology though, it will be a fair few years before it will be in full use - although this situation will be helped due to comparatively low cost of the new device: due to the absent need for high magnetic fields, the new machines may cost as little as one tenth of its high-powered counterpart.

UPDATE 29/01: Vaughan at MindHacks has pointed out the downsides of using SQUIDs, which I didn't mention.

Hierarchical Temporal Memory (HTM)

Some very brief thoughts and notes on this article: In Aprils issue of the IEEE Spectrum, Jeff Hawkins (of Palm Pilot fame, and his book "On Intelligence") briefly discusses the Hierarchical Temporal Memory theory/framework as a novel engineering tool, and actual and potential applications. The HTM framework is based on the proposed operation of the human neocortex, which makes up around 60% of the brain. Although the neocortex is very uniform at both the macro- and micro-scopic levels, different regions of it are 'responsible' for a wide range of functions and differing modalities, leading to the view that its underlying functionality (that is, the 'mode of neural processing') is also uniform - that it is a general purpose learning machine. Jeff Hawkins proposes that (as further detailed in his book) that the interconnectivity of the neocortex may be traced out forming a hierarchy. It is this hierarchical connectivity, between elements of equivalent functionality, which forms the basis of the HTM. It would be useful to quote one of the concluding paragraphs which gives insight into the motivation of the work:

"HTM is not a model of a full brain or even the entire neocortex. Our system doesn't have desires, motives, or intentions of any kind. Indeed, we do not even want to make machines which are humanlike. Rather, we want to exploit a mechanism that we believe to underlie much of human thought and perception. This operating principle can be applied to many problems of pattern recognition, pattern discovery, prediction and, ultimately, robotics. But striving to build machines that pass the Turing Test is not our mission."

This emphasis on HTM's as an engineering solution is made quite explicit, with a number of examples mentioned where the tools which have been developed on these principles have been used. These include modelling networks (e.g. computer or social), and image processing (e.g. for use in the automotive industry). The limitations of the system, on the other hand, are acknowledged: HTM's work best when there is inherent hierarchical structure in the data, due to the hierarchical structure and nature of the HTM's themselves. Also, in its current state, HTM's are unable to deal with long memory sequences, or specific timing events, rendering them unable to deal with natural language processing or robotics, however there is nothing in principle that makes it impossible at some point in the future.

The basic principles of operation are of course not completely novel in themselves, even as acknowledged by the author. A number of other efforts and theories have used similar hierarchical structures, including Hierarchical Hidden Markov Models, and the Network Memory theory of Professor Fuster, which I have writen about in previously. I think it serves as another example of how this type of hybrid between parallel processing (a central tenet of the theory of brain information processing) and hierarchical structure is a promising line of research (indeed, it is in this area that I am working), which may be considered biologically non-implausible given our current understanding of the brain.

IEEE Spectrum - December 2006

Notes on December 2006 edition of IEEE Spectrum:

Engineers and autism:
Simon Baron-Cohen, of Cambridge university, has proposed a theory concerning the link between engineers (and, others systemizers - such as mathematicians) and autism spectrum disorders. According to this theory, in the past, these people did not meet people like themselves. However, at the present time, because professions tend to organise people by their psychological types, the probability that two such people marry and bear children greatly increases. This situation has then led to a 'concentration' of the genes responsible for systemizing behaviour, which in turn has led to the increased chances of a child with extreme instances of such traits; i.e. autism. He uses some striking statistics which appear to support his theory: engineers are twice as likely to have autistic children, and the relatives of autistics display higher than average levels of systemizing. Despite being seemingly bleak news, these 'autistic traits' may not necessarily be all bad. There is no doubting the severe disability that autistics suffer, however, taking the example of Asperger's syndrome. Whereas people with this condition often leads to isolation, it is often accompanied by by very positive mental capacities, sometimes even cited as genius (Einstein and Newton are two widely quoted possible examples).
From IEEE Spectrum, December 2006 issue, p6

Robot waiters:
A restaurant in Hong Kong has attempted to dispense with human waiters and replace them with automated robots. Built by Cyber Robotics Technology (and costing US$5000 each), they were designed to seat customers, take orders (via touchscreen), avoid customers, deliver the food, and even respond to single word commands. A great idea one would think. However, in reality, they needed direct human supervision, thereby defeating their practical purpose - leaving them as novelty items. I think this story is fairly indicative (from my limited experience anyway) of other supposedly autonomous robots - requiring the helping hand of human control to be able to operate to specification.
From IEEE Spectrum, December 2006 issue, p17

Other stories:
- The emergence of the London Stock exchange as the location of choice for technology start-up companies, over the more traditional NASDAQ - p10
- India's space aspirations, including their own GPS-style system and rocket systems - p12
- The possible disappearance of traditional film-cameras? The ever increasing forays of electronics companies into the realm of photography - p13
- Smart, wireless parking systems - p14
- A review of Sony's PS3 system and its 'monster' 8-core processor, the cell - p18
- Social entrepreneurship: Benetech and the human rights project - p25
- The story of Jack Morton: the brilliant man who pioneered the transistor at Bell Labs, but who never appreciated its potential for microchips, which ultimately led to the falling behind of AT&T in the microchip race - p31
- The present and potential of the digital cinema setup and experience, with an insert on the past and future of 3D cinema - p37
- A short exposee on taking risks with your career - p44
- The benefits, and drawbacks, of virtual private networks: a case study of Relakks (www.relakks.com) - p45
- The Faraday cage wallet, designed to protect personal information from RFID bearing identity thieves (especially with the new proposed RFID passports fast becoming a reality) - p46
- The 'unobvious' rule in patent applications: put to the test in the US court of appeals. I think this one has the potential to change the way in which research is commercialised, depending on the outcome of the challenge - p47
- The Wiki world: the rise of the wiki, and the way it's changing the world, especially the language - p52