I have been attached to the BBC News coverage through their website and I saw an interesting tweet posted there:

At first I thought. Pre-empt where the next bout would take place? How on earth would they manage that?

But it actually isn’t that hard. They have a mountain of CCTV data, they have a good amount of servers, all they lack is a bit of artificial intelligence.

The best way I can think of to determine where possible bouts of violence could sprout in what seems like an apparent random non-deterministic method of choice is as follows:

The IT team of the police should annotate the direction of each CCTV camera, including which streets are in view and the coordinates.

Afterwards, the CCTV cameras should be plotted on a 2D map, as vectors (pointing in the direction they are facing, with the length of the vector being the distance the camera covers).

Additionally, all points of interest should be mapped, such as shopping centres, residential areas, commercial areas, shops with high-value items, and shops with low-value items. Most of this data can be readily obtained from Google Maps, amongst other online maps. This data can be extracted and annotated with the values we require (such as the value of the goods sold per area, etc.)

If you think this is a very hard task, it is not. A very simple way of doing this would be to go to the website (or ask by phone) of each major retailer and chain for a list of addresses of their shops. Google Maps can plot them on a map using a spreadsheet as input. There you go, simple as that!

A Machine Learning program could be developed using WEKA (for instance), in which an SVN is programmed to take data from the map-plot, where priority spots include places where high-value items are sold. Additionally, it would take data from each CCTV camera.

Now, how do we represent the data from CCTV cameras? One way would be to take a selection of pixels from each camera, measure the amount of change for a second, and wherever there is a large enough change in different areas of the same camera, we might have a lot of movement going on. So we automatically annotate the data per CCTV camera as having “movement” or “no movement”. Additionally, a range from 0-1 would produce better results (hopefully).

So now we run an SVN machine on the data and hopefully come up with some interesting results.

What could essentially be obtained from this is a vector describing the movement of as mass of people from camera to camera, this vector would be projected on the 2d map. Multiple vectors could be plotted at the same time if there were multiple riots taking place at the same time in the city. A confidence level can be given to each vector (assuming we have built in a few mechanisms to differentiate people from cars, etc). The places of interest could be mapped as hotspots, and furthermore we can predict paths to possible places of interest, derived from the speed and direction of each vector.

So there you go. If you belong to the MET, please share this blog post with your boss (or the IT team) and get working on a system to perform such actions, it would certainly help prevent further stupidity in the future. 6,000 police officers should be able to deal with outbreaks of crime provided they knew where the rioters would be gathering and where they are heading.

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I recently read an interesting article on TechCrunch which talks about the 6 or so operating systems geared towards tablets which will soon have to face a battle for who gains the most popularity in the limited market of tablet PCs.

Linda Lawrey posted this article on her Google Buzz which sparked a discussion about who might be coming out as winner, but it also generated a conversation about why anyone would want a tablet in the first place. I think 3+ million iPad owners would have something to add to that conversation, however, my post is not about that.

I personally believe tablets are useful for certain things today: While not exactly great for use on-the-go such as mobile phones they are useful as a replacement for net-books, say, for use while having a coffee at Starbucks, for taking notes while at meetings, or as a bed-side computer to check mail and browse the web before bed. But my thoughts about their usefulness are centred on the future: Internet-powered centralised intelligent home & office devices.

I can see them integrated to each room in a house, possibly on the wall, where one can quickly browse their calendar, program their alarm, control the lights of the house, communicate with the house’s security system, view CCTV video from other rooms and program DVR recording, control other digital devices from their room, etc.

Imagine: You’re going to bed so you go to your wall and program the alarm clock for 8 AM, you also program your children’s alarm clock for 7:30 AM, activate the home security system, and set up chilled-out relaxing music for the bedrooms in the house. You also program the device to start up the radiators at 6:00 AM and the hot water at the same time. At the same time you set up the A/C to maintain a certain ideal room temperature during the night. John, your kid, doesn’t like the music so he gets up and sets his own device to mute for his room. You wake up to the sound of music, increasing gradually in volume in each room, as a start to a great new day.

You might have a party that evening and you are having a discussion about a certain word definition, or the location of a country, so you get up, unplug the tablet from the wall, and perform a search on Wikipedia, bringing the tablet to the table and sorting out the discussion in moments.

In the office, you create a powerpoint presentation with interactive graphs and cool pictures on your PC. You store it on the local network, pop in to the conference room, take a tablet down from the wall, then you can discuss the points and make changes directly on the tablet, making the meeting a more productive one than the usual guy talking in front of a projector while people take notes. Not good enough? Connect a pico-projector to it, then you can have your boring meeting with the capability of making changes or taking meeting notes directly on the tablet, which makes the use of paper basically redundant.

So how useful do you believe they are? Useful enough right now? Or more useful in the near future?

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This is CHARLI, the United State’s first ever human-sized autonomous robot. In contrast to other humanoid robots such as ASIMO, CHARLI seems rather obsolete. However, they have a goal, they have a prototype, and they have a good project leader to take them through the long winding path towards the construction of a robot that can help people around their homes and around the city.

As Awesom-o writes in the Artificial Intelligence and Robotics blog:

Minus the face, it looks quite like the robot from the 2004 movie I, Robot (and story by Isaac Asimov), and that’s because it is partly based on it. The inspiration behind CHARLI is quite simple—we live in a world tailored for humans, and so it makes sense that our robot helpers will look and be able to do most of the things we can. At five-feet tall, it is a little bit shorter than the average human, but CHARLI will be able to walk, run, jump, open doors or squeeze through tight places. Basically, it will be able to mimic us in almost all ways.

What is really curious to me is that I have just finished reading the book “The Essence of Artificial Intelligence” by Alison Cawsey and in one of the final chapters she speaks about humanoid robots:

To automate human intelligence, it is better to start by building a complete human-like system with the abilities of a human baby (or even an insect!), and progress from there, rather than concentrate on “adult” versions of isolated skills, and then hope that we will be able to eventually glue the various components together. The hope is that a robot able to interact with its environment in all the complex ways that a human can will be able to learn the more advanced skills, rather than have them pre-programmed into it as symbolic reasoning programs.

The interesting thing is that this book was published in 1998, twelve years ago! It looks like the concepts imagined back then are just being put into practice. So little have we advanced? I mean, I concur with the fact that computing speed was not the same 12 years ago and it would have been impossible to do the amount of calculations we can do nowadays. However, robotics as a whole seems to have progressed very little since then.

It seems we still have a lot to learn, and a lot to discover.

One trend I have seen popping up a lot is the fact that all development of humanoid robots tends to be oriented towards “helping people in the house or around the street”. I think that sole aim of building them is limiting research as a whole. I believe it is better to tackle the whole solution to the problem, than to focus on a specific goal. This may be completely debatable, but in my own opinion single-mindedness limits the ability to go further than the initial solution of the problem. Never set limits.

Read more about CHARLI at the Virginia Tech blog.

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According to Wikipedia, Francis Galton was the first scientist to propose a theory of general intelligence; that intelligence is a true, biologically-based mental faculty that can be studied by measuring a person’s reaction times to cognitive tasks.

Alfred Binet, in contrast, believed intelligence was a median average of dissimilar abilities, not a unitary entity with specific, identifiable properties.

Over the course of my life I have heard different things about intelligence. I’ve heard a couple of times that we are all equally intelligent beings. Then again, we all have heard typical phrases such as “He is more intelligent than you”, or “she must be really intelligent”. These usually refer to the fact that an individual may have a higher or lower level of IQ, which after all is just a figure of determining capacity based on results.

What really got me going about looking for information on brain use was the memory of people telling me that we use different percentages of our brain. Then in school I was taught that the several sections of our brain process different functions. How then can we use only a fraction of it if studies have been performed that claim that we do use different parts at the same time?

PET scans (positron emission tomography) and fMRI (functional magnetic resonance imaging) clearly show that the vast majority of the brain does not lie fallow. The nature of claims such as the one which describes that psychic powers may be obtained if we master the percentage of unused brain have been proven wrong, but it is the mass media, literature, and shows performed by different personalities which has ensured the endurance of the claims. More information about that may be obtained at this page at snopes.com, which details an investigation performed by Benjamin Radford.

I have a theory

It is not that we do not fully use our brain. I believe, instead, that it is the capacity of interpreting messages that varies. We may be able to interpret more signals as we train our brain to do so, therefore increasing our ability to integrate more thoughts together, reason them, and process more results, in a faster and more accurate manner.

Clearly we use different sections of our brain to process different signals. Your innate reaction to things such as getting burned is processed in one area. Memories are stored in another area. Likewise, vision is also computed by another section of your brain. However, some people manage to understand things faster than others, just as some people are better with creative issues than others. We have Math geeks, Computer wizards, Programming geniuses, Scientists, Artists, etc. All of them have a certain facility for some areas.

I believe the clue to this lies in the speed, the accuracy, and the depth of the processing of signals from each area of the brain.

The frontal lobe is in charge of recognizing future consequences resulting from current actions, choosing between good and bad actions, overriding and suppressing unacceptable social responses, and determining similarities and differences between things or events.

Now, for example, when you read a book and don’t understand a word, many times you skip it. Then you might hear it a few times in movies. There might come a time when you ask someone what it means, or you hear or read the definition for it somewhere. Then you start noticing it much more commonly, in places where it might have always been but you were unaware of its presence.

Likewise, my theory is that the brain’s sections can process so many things that you are not able to understand, or to grasp entirely, but as you become aware of how to understand that information, then you begin to actually use it more thoroughly and exploit that new ability.

An example of this would be painting. You may have seen many pieces of art, and your brain processes how the shadows and mixtures of colours look like. Then you see a painter actually perform the job. You might then try painting yourself and you are not successful at it the first few times. Your friend, Jack, has not been to many art galleries, nor has he seen a painter do his job, but the first time he grabs a brush he seems naturally talented.

I would explain this by his ability to process those signals in a better way. He may not know precisely how an artist mixes his colours, but he knows how the colours of a face should look like, and he tests mixing the colours until he achieves the one he is looking for. You may be trying too hard to find a scientific approach to it, a perfect balance, but he may be doing it by actually understanding these brainwaves, or what others would call “by heart”.

I do not fully understand how capable we will ever be in certain areas. It may be that some people are just “blocked” in certain area, psychologically, and therefore can’t achieve the understanding of those signals. However, I believe it more to be a matter of really wanting to do so. Someone may want to play guitar, but when he grabs it he thinks he is rubbish, then he claims that he has no ability to play and blocks his creative path. This, however, is a matter of psychologically blocking his ability to understand the patterns that are naturally forming in his brain.

I could say the same for myself. It could chose not to publish this post because I may not fully understand the patterns that form in my brain, I may choose to stay behind and keep my thoughts to myself, but the act of letting it out improves me a bit every day. I believe if anyone tries hard enough at something, the patterns will emerge, and sooner or later he/she will be able to understand those patterns and to exercise the knowledge to deliver a product, action or thought.

It’s all about using it. Don’t you think?

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Robots are widely used but few are considered intelligent

The Massachusetts Institute of Technology has begun a project to re-think artificial intelligence research.

The Mind Machine Project will return to the basics of AI research to re-examine what lies behind human intelligence.

Spanning five years and funded by a $5m (£3.1m) grant, it will bring together scientists who have had success in distinct fields of AI.

By uniting researchers, MIT hopes to produce robotic companions smart enough to aid those suffering from dementia.

“Essentially, we want to rewind to 30 years ago and revisit some ideas that had gotten frozen,” said Neil Gershenfeld, one of the scientists leading the MMP and director of the MIT Center for Bits and Atoms.

via BBC News – Science goes back to basics on AI.

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Boston Dynamics has not released much information about PETMAN other than that the project has 2 phases : phase 1 has a 13-month duration focused on design and phase 2 has a 17-month duration for building, validating and installing the robot. The company expects to deliver the robot in 2011.“

via Artificial Intelligence and Robotics.

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It has been featured in many different shows, including CES, amongst others. Many believe ASIMO to be a step forward in the progress of true AI. I have read comments on forums and on the videos themselves of people who are alarmed that they would one day take over the world. There are concerned people voicing their thoughts on humans playing god.

All of this has been going on for decades. Some of us look for answers to our creation, wanting to explore the duplication of our processes, and genuinely believing that our mind is composed of algorithms that can be replicated into a machine that can be said to be intelligent. Some of us hate the fact that we are trying to recreate life, and composed others based on our intelligence, stating that it is immoral.

Well, for those of you who are scared about your safety: Robots won’t take over the earth, nor will they turn evil as pictured in the film “I, Robot”. However I do believe the age is coming in which the creations of the imagination and creativity of science fiction authors such as Isaac Asimov’s are turning into real life events. And I do believe that some day it might be possible that they could in turn right their own viruses, spyware, spam the whole internet, conduct highly specialised cracking attacks, amongst other things.

I mean, computer programs can already compile and recompile themselves, as several professional adware programmers have shown in the past. It is only a matter of time before the creation of the *spark* that will give life to a rational being, one that can act not only for the wellbeing of others, but for it’s own wellbeing. One that can induce creative thoughts, and produce creative output.

That will be an age in which a computer will be able to effectively upload it’s code to the web, allowing expansion over the net, replication in different programming languages, and collaboration of thousands of millions of bots infesting supercomputer clusters.

However, back to earth, back to the 21st century. I found 3 really impressive videos of ASIMO that I would like to share with you. Voice your comments back to me if it causes any interest.

A rundown on ASIMO’s main features:

ASIMO coordination intelligence and interaction with other ASIMO’s:

ASIMO conducts the Detroit Symphony Orchestra:

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Integrate this with camera’s, inflared sensors, stereo microphones, speakers, motion detectors, and give it a little spark of memory, a sense of direction, and a wireless internet connection. This could be unstoppable. We’re definitively getting there, slowly, but marching on.

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English, particularly, is much more complex than I thought. As you may already know, I am rather into AI. One of the fields of AI is Natural Language Processing which involves speech recognition, syntactic and semantic organisation, separating words into parts of speech, language understanding, and finally speech generation, amongst others.

I genuinely used to believe there were only 8 parts of speech in English: Verbs, Adverbs, Nouns, Pronouns, Adjectives, Preopsitions, Conjunctions and Interjections. I stand corrected by Wikipedia. There are about 17 different types if we classify them correctly.

The open word classes:

• Adjectives
• Adverbs
• Interjections
• Nouns
• Verbs (except auxilliary verbs)

According to Wikipedia, “an open class (or open word class) is a word class that accepts the addition of new items, through such processes as compounding, derivation, coining, borrowing, etc.”

The closed word classes:

• Auxiliary verbs
• Clitics
• Coverbs
• Conjunctions
• Determiners (articles, quantifiers, demonstrative adjectives, and possessive adjectives)
• Particles
• Measure words
• Adpositions (prepositions, postpositions, and circumpositions)
• Preverbs
• Pronouns
• Contractions
• Cardinal numbers

According to Wikipedia, “a closed class (or closed word class) is a word class to which no new items can normally be added, and that usually contains a relatively small number of items.”

Now, I was not aware of such classification, but this for sure must have an impact on language parsers. I am currently starting to write my first Language Parser, and thought I would start out with an SQL dictionary structure. I will be posting my findings in this blog as I get along with this.

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