I chose to study Chemistry and Physics simply because they were the subjects I enjoyed most, so I enrolled on a B.Sc. (Hons) degree at the University of Malta without having a clear idea about what I would be doing once the four years are over. I was not the best brain in the class but in 2004 I graduated with a 2:1 grade and it was quite obvious that I needed a plan. A couple of opportunities to embark on a Ph.D. in Britain came along through local contacts and applications on jobs websites. Despite not knowing much about the subject, I decided to go with the Ph.D. at Exeter University because it was about Nuclear Magnetic Resonance, a subject that sits right on the verge of Chemistry and Physics.
Obviously the idea of moving abroad, living away from my parents and starting this amazing new adventure was incredibly exciting. From the start of my Ph.D. things went incredibly well, it was immediately obvious that I was much better at doing research than studying for exams. I started with looking into dynamics in solid materials on the microsecond timescale, which is the less studied type of motion. It bridges the gap between very fast (spin-lattice relaxation motions, nanosecond) and slow (millisecond to second) timescales. I published my first scientific paper a year into my Ph.D., and five more followed by the time I defended my thesis.
Because of the contacts I built during my Ph.D. as soon as I finished I was offered a post at University College London, Institute of Child Health, working as a research fellow in renal imaging. I carry out research at Great Ormond Street Children’s Hospital using novel non-invasive Magnetic Resonance Imaging (MRI) techniques. I work mainly with children requiring a kidney transplant. The aim of my work is to eventually be able to furnish doctors with information about their patients, which is currently either unavailable to them or they can only get through invasive clinical techniques such as biopsies. My work here has produced six peer-reviewed papers and I am currently working on a few more.
The research I carried out during my Ph.D. involved dealing with basic scientific concepts like Quantum Mechanics — that studies sub-atomic phenomena — and I was at liberty to experiment as I saw fit, which I enjoyed. However, despite being much more restrictive, I find clinical research extremely rewarding. Coming face to face with the people benefiting from all your hard work is really priceless.
Just after my Ph.D. I married my husband. We are now very proud parents of a two-year-old son. Any working mum would tell you that raising a family while maintaining a career is not easy, but I believe that if you like your job enough, combing the two is very worthwhile. Obviously research does not wait for anyone, and luckily for me, having colleagues that supported me meant that I was able to carry on publishing while I was on maternity leave.
Being in the second year of my banking, finance and management studies, innovation in these sectors is a key part of my curriculum. In banking one can easily see developments with the introduction of banking by telephone, internet and mobile. Similarly with management, recent growth has allowed the sector to grow and develop expertise in management of projects, accounting and supply chains.
Innovation has exponential potential to foster new solutions, initiatives and jobs. Younger graduates need to create new opportunities. For Malta to improve its competitiveness and attract investment we must turn challenges into opportunities. During Ireland’s EU Presidency, in the first half of 2013, the negotiations led by Dublin saw Malta secure €1.128 billion for the 2014-2020 Multi-Annual Financial Framework. The possibilities for Malta are endless. On top of this framework lies the Horizon 2020 Programme, where countries can compete for over €80 billion set aside for innovation. These funds should be used strategically in Malta to improve existing sectors and to find a way to create new markets and jobs. This growth would build Malta’s competitiveness.
“For Malta to improve its competitiveness and attract investment we must turn challenges into opportunities”
SMEs (small and medium sized enterprises) are being greatly encouraged by the EU since they are seen as a route out of the recent economic crisis. The Horizon 2020 programme gives priority to SMEs.
Malta can win more of these funds by looking at what Horizon 2020 aims to achieve, that is leadership in a world of competitive science and to realise innovations leading to societal change. These could be in the areas of biotechnology, clinical research and green technologies. We need systems that change the way we live and think.
In the global economy, it can be hard to be innovative and entrepreneurial as we have grown accustomed to depending on other countries to do our work. Instead of waiting for new technologies and developments to emerge so that we can replicate them, we should encourage the young generation to open new doors that could lead them to success. Thus, inspiring people to think outside the box and to be creative starts from an early age. This train of thought must be cultivated at the heart of the education system where students start to think about jobs and the future.
Last December, I had the opportunity to see this when I visited Facebook’s Headquarters in Dublin as part of the ASCS study trip. There is considerable scope for further research into virtual platforms linking social media with innovation in business.
Albert Einstein once said ‘Most people see what is, and never see what can be,’ which is exactly why we need to shift the focus on what can be done, rather than what has already been done.
Research — that would be the simplest way to answer the question above. Really and truly this answer would only apply to a small niche of individuals throughout the world.
It is a big challenge to explain to people what you do with a science university degree. The questions “Int għal tabib?” (Are you aiming to become a doctor?) or “Issa x’issir, spiżjar?” (Will you become a pharmacist?) are usually the responses. The thing is, people have trouble understanding non-vocational careers — if you are not becoming a lawyer, an accountant, a doctor or a priest, the concept of your job prospects is quite difficult to grasp for the average Joe.
In truth, it is not really 100% Joe Public’s fault — research is a tough concept to come to terms with, ask a good portion of Ph.D. students about that. There seems to be a lack of clarity in people’s minds about what goes on behind the scenes. If you boil it down, everything we use in our daily lives from mobile phones to hand warmers are the spoils of research — a laborious process with the ultimate goal of increasing our knowledge and, consequently, the utility of our surroundings.
“People need to stop feeling threatened by big words and abstract concepts they cannot grasp”
So, then, why exactly is it such an alien concept? I think the reason is that research is very slow and sometimes very abstract. Gone are the days when a simple experiment meant a novel, ground-breaking discovery — research nowadays delves into highly advanced topics, building on past knowledge to add a little bit more. I have complained about this to many of my colleagues on several occasions — and it is more complicated when you are studying something like Chemistry and Physics, or worse, Maths and Statistics — people just do not get it!
Research is exciting. The challenge is how to infect others with this enthusiasm without coming off as someone without a hint of a social life (just ask my girlfriend). It is nice to see initiatives like the RIDT and Think magazine trying hard to get the message out there that research is a continuous process with often few short-term gains. It can be surprising when you realise how much is really going on at our University, despite its size and budget.
To befriend the general public researchers still need to do more. The first step is relaying the message in the simplest terms possible — people need to stop feeling threatened by big words and abstract concepts they cannot grasp. There also needs to be increased opportunities for interaction with research — Science in the City is the perfect example. Finally, I think MCST needs to start playing a larger role — it must work closer to University and take a more coordinated role at a national level. Only then can we begin to explain what us researchers do.
Producing Food products, pharmaceuticals, and fine chemicals leads to hazardous waste and poses environmental and health risks. For over 20 years, green chemists have been attempting to transform the chemical industries by designing inherently safer and cleaner processes. Continue reading
There are over 100 billion galaxies in our universe. Each galaxy has billions of stars. Each star could have a planet. Planets can breathe life. Alessio Magrowrites about his experience hunting for E.T. Illustrations by Sonya Hallett
In 1982, 4 years before I was born, the world fell in love with Spielberg’s E.T. the Extra-Terrestrial. Fifteen years later, the movie Contact, an adaptation of Carl Sagan’s novel, hit the big screen. Although at the time I was too young to appreciate the scientific, political, and religious themes I was captivated and it fired my thoughts. I questioned whether we are alone in this vast space. What would happen if E.T. does call? Are we even listening? If so, how? And, is it all a waste of time and precious money? Instead of deflating me, these questions inspired me to start a journey that led me to my collaboration with SETI, the Search for Extra Terrestrial Intelligence. I participated in ongoing efforts to try and find intelligent civilisations on other worlds.
The debate on whether we are alone started ages ago. It was first debated in Thales, Ancient Greece. Only recently has advanced technology allowed us to try and open up communication channels with any existing advanced extraterrestrial civilisations. If we do not try we will never answer this question.
For the past fifty years we have been scanning the skies using large radio telescopes and listening for signals which cannot be generated naturally. The main assumption is that any advanced civilisation will follow a similar technological path as we did. For example, they will stumble upon radio communication as one of the first wireless technologies.
SETI searches are usually in the radio band. Large telescopes continuously scan and monitor vast patches of the sky. Radio emissions from natural sources are generally broadband, encompassing a vast stretch of the electromagnetic spectrum — waves from visible light to microwaves and X-rays — whilst virtually all human radio communication has a very narrow bandwidth, making it easy to distinguish between natural and artificial signals. Most SETI searches therefore focus on searching for narrow band signals of extraterrestrial origin.
Narrow bands are locked down by analysing a telescope’s observing band — the frequency range it can detect. This frequency range is broken down into millions or billions of narrow frequency channels. Every channel is searched at the same time. SETI searches for sharp peaks in these small channels. This requires a large amount of computational resources, such as supercomputing clusters, specialised hardware systems, or through millions of desktop computers. The infamous SETI@home screen-saver extracted computer power from desktops signed up to the programme, which started as the millennium turned.
E.T. civilisations might also transmit signals in powerful broadband pulses. This means that SETI could search for wider signal frequencies. However, they are more difficult to tease apart from natural emissions, so they require more thorough analysis. The problem is that as broadband signals — natural or otherwise — travel through interstellar space they get dispersed, resulting in higher frequencies arriving at the telescope before lower ones, even though they both were emitted at the same time. The amount of dispersion, the dispersion gradient, depends on the distance between the transmitter and receiver. The signal can only be searched after this effect is accounted for by a process called dedispersion. To detect E.T. signs, thousands of gradients have to be processed to try out all possible distances. This process is nearly identical to that used to search for pulsars, which are very dense, rapidly rotating stars emitting a highly energetic beam at its magnetic poles. Pulsars appear like lighthouses on telescopes, with a regular pulse across the entire observation band.
For the past four years I have been developing a specialised system which can perform all this processing in real-time, meaning that any interesting signals will be detected immediately. Researchers now do not need to wait for vast computers to process the data. This reduces the amount of disk space needed to store it all. It also allows observations to be made instantaneously, hence reducing the risk of losing any non-periodic, short duration signals. To tackle the large computational requirements I used Graphics Processing Units (GPUs) — typically unleashed to work on video game graphic simulations — because a single device can perform tasks of at least 10 laptops. This system can be used to study pulsars, search for big explosions across the universe, search for gravitational waves, and for stalking E.T..
The Electromagnetic Spectrum. Higher frequencies mean higher energies but shorter wavelengths. X-rays and Gamma rays are on the higher end of the spectrum making them so dangerous.
E.T. we love you
Hunting for planets orbiting other stars, known as exoplanets, has recently become a major scientific endeavour. Over 3,500 planet-candidates were found by the Kepler telescope that circles our planet, about 961 are confirmed. Finding so many planets is now leading scientists to believe that the galaxy is chock-full of them. The current estimate: 100 billion in our galaxy, with at least one planet per star. For us E.T. stalkers, this is music to our ears.
Life could be considered inevitable. However, not all planets can harbour life, or at least life as we know it. Humans need liquid water and a protective atmosphere, amongst other things. Life-supporting planets need to be approximately Earth-sized and orbit within its parent star’s habitable zone. This Goldilocks zone is not too far away from the sun, freezing the planet, or too close to it, frying it. These exoplanets are targeted by SETI searches, which perform long duration observations of exoplanets similar to Earth.
“The big question is: where do we look for E.T.? I would prefer rephrasing to: at which frequency do we listen for E.T.?”
By focusing on these planets, SETI is gambling. They are missing huge portions of the sky to focus on areas that could yield empty blanks. SETI could instead perform wide-field surveys which search large chunks of the sky for any interesting signals. Recent development in radio telescope technology allows for the instantaneous observation of the entire sky, making 24/7 SETI monitoring systems possible. Wide-field surveys lack the resolution needed to figure out where a signal would come from, so follow-up observations are required. Anyhow, a one-off signal would never be convincing.
For radio SETI searches, the big question is: where do we look for E.T.? I would prefer rephrasing to: at which frequency do we listen for E.T.? Imagine being stuck in trafficand you are searching for a good radio station without having a specific one in mind. Now imagine having trillions of channels to choose from and only one having good reception. One would probably give up, or go insane. Narrowing down the range of frequencies at which to search is one of the biggest challenges for SETI researchers.
The Universe is full of background noise from naturally occurring phenomena, much like the hiss between radio stations. Searching for artificial signals is like looking for a drop of oil in the Pacific Ocean. Fortunately, there exists a ‘window’ in the radio spectrum with a sharp noise drop, affectionately called the ‘water hole’. SETI researchers search here, reasoning that E.T. would know about this and deliberately broadcast there. Obviously, this is just guesswork and some searches use a much wider frequency range.
Two years ago we decided to perform a SETI survey. Using the Green Bank Telescope in West Virginia (USA), the world’s largest fully steerable radio dish, we scanned the same area the Kepler telescope was observing whilst searching for exoplanets. This area was partitioned into about 90 chunks, each of which was observed for some time. In these areas, we also targeted 86 star systems with Earth-sized planets. We then processed around 3,000 DVDs worth of data to try and find signs of intelligent life. We developed the system ourselves at the University of Malta, but we came out empty handed.
A camera shy E.T.
Should we give up? Is it the right investment in energy and resources? These questions have plagued SETI from the start. Till now there is no sign of E.T., but we have made some amazing discoveries while trying to find out.
Radio waves were discovered and entered into mainstream use in the late 19th century. We would be invisible to other civilisations unless they are up to 100 light years away. Light (such as radio) travels just under 9.5 trillion kilometres per year. Signals from Earth have only travelled 100 light years, broadcasts would take 75,000 years to reach the other side of our galaxy. To compound the problem, technology advances might soon make most radio signals obsolete. Taking our own example, aliens would have a very small time window to detect earthlings. The same reasoning works the other way, E.T. might be using technologies which are too advanced for us to detect. As the author Arthur C. Clarke stated, ‘any sufficiently advanced technology is indistinguishable from magic’.
The Wow! signal is a brief, strong radio burst of unknown origin detected by the Big Ear Telescope, SETI search, 1977. If it originated from deep space, it could either be a new astrophysical phenomena or an alien signal.
At the end of the day, it is all a probability game, and it is a tough one to play. Frank Drake and Carl Sagan both tried. They came up with a number of factors that influence the chance of two civilisations communicating. One is that we live in a very old universe, over 13 billion years old, and for communication between civilisations their time windows need to overlap. Another factor is, if we try to detect other technological signatures they might also be obsolete for advanced alien life. Add to these parts, the assumed number of planets in the Universe and the probability of an intelligent species evolving. For each factor, several estimates have been calculated. New astrophysical, planetary, and biological discoveries keep fiddling with the numbers that range from pessimistic to a universe teeming with life.
The problem with a life-bloated galaxy is that we have not found it. Aliens have not contacted us, despite what conspiracy theorists say. There is a fatalistic opinion that intelligent life is destined to destroy itself, while a simpler solution could be that we are just too damned far apart. The Universe is a massive place. Some human tribes have only been discovered in the last century, and by SETI standards they have been living next door the whole time. The Earth is a grain of sand in the cosmic ocean, and we have not even fully explored it yet.
“Signals from Earth have only travelled 100 light years, broadcasts would take 75,000 years to reach the other side of our galaxy”
Still, the lack of alien chatter is troubling. Theorists have come up with countless ideas to explain the lack of evidence for intelligent alien existence. The only way to solve the problem is to keep searching with an open mind. Future radio telescopes, such as the Square Kilometre Array (SKA), will allow us to scan the entire sky continuously. They require advanced systems to tackle the data deluge. I am part of a team working on the SKA and I will do my best to make this array possible. We will be stalking E.T. using our most advanced cameras, and hopefully we will catch him on tape.
Wi-fi is ubiquitous. The technology can be an easy back door for hackers to access a computer through online tools that anyone can learn to use. The global cybercrime bill now tops €700bn and will keep rising. To find out the security of Maltese Wi-Fi networks Kurt Mahoney (supervised by Prof. Ing. Victor Buttigieg) mapped out around 70% of the island’s built-up areas.
Mahoney first carried out in-house testing on Wi-Fi security protocols. He then formulated security categories depending on ease and speed of access to a private network. For example, the WEP (Wired Equivalent Privacy) security standard could be cracked in less than one minute (irrelevant of password complexity). On the other hand, the WPA2 (Wi-Fi Protected Access II) security standard with AES (Advanced Encryption Standard) grade encryption and a twelve-character random alphanumeric password was virtually impossible to crack using brute force techniques.
Kurt Mahoney
Setting up a car with several Wi-Fi antennas, he then travelled a preplanned route through all the Maltese villages, apart from Mdina. Private security protocols were noted from automatic Wi-Fi transmissions, however he avoided conducting cracking or penetration testing. Mahoney then created a security map for the Maltese Islands from 64,317 observed private networks. Forty percent of private Wi-Fi networks in Malta were very vulnerable to hacking that increased to 90% if using more sophisticated attacks.
Wi-Fi security was poor all over the Island, with Western and South Eastern districts having marginally lower security. Malta needs a nationwide awareness campaign to increase the security levels of Wi-Fi networks. Top-notch security can be setup in a few minutes. All modern routers support military grade AES encryption standards, and together with a proper password policy one would render a Wi-Fi network almost invulnerable to direct attack.
This research was presented at the fourth Workshop in Information and Communication Technology (WICT). It was performed as part of a B.Sc. (Hons) in ICT at the Faculty of ICT and part sponsored by the Malta Communications Authority. It was shortlisted for the Chamber of Engineers’ Best ICT Student’s Project Award.
Made infamous by Sigmund Freud, the idea is that we spend one third of our lives dreaming about what we would like to do. Our rational brain suppresses these feelings.
On the other extreme, our brain is just as active in certain sleep stages. These neural firings express themselves in dreams. There are no deep hidden emotions behind them.
Somewhere in between lie recent studies that show that dreams are important in memory, learning and emotions. If you sleep without dreaming these qualities will suffer. For example, rat studies in 2001 showed how while dreaming they replayed solutions to mazes to commit them to their long-term memory.
Send your questions to think@um.edu.mt and we’ll find out if it’s the truth or just a fib!
In 2011 an IBM computer called Watson made the headlines after it won an American primetime television quiz called Jeopardy. Over three episodes the computer trounced two human contestants and won a million dollars.
Jeopardy taps into general world knowledge, with contestants being presented with ‘answers’ to which they have to find the right questions. For instance, one of the answers, in the category “Dialling for Dialects”, was: While Maltese borrows many words from Italian, it developed from a dialect of this Semitic language. To which Watson correctly replied with: What is Arabic?
Watson is a good example of state of the art technology that can perform intelligent data mining, sifting through huge databases of information to identify relevant nuggets. It manages to do so very efficiently by exploiting a grid architecture, which is a design that allows it to harness the power of several computer processors working in tandem.
“Maltese has been described as a language in danger of ‘digital extinction’”
This ability alone would not have been enough for it to win an American TV show watched by millions. Watson was so appealing because it used English as an American would.
Consider what it takes for a machine to understand the above query about Maltese. The TV presenter’s voice would cause the air to vibrate and hit the machine’s microphones. If Watson were human, the vibrations would jiggle the hairs inside his ear so that the brain would then chop up the component sounds and analyse them into words extremely rapidly. The problem for a computer is that there is more to language than just sounds and words. A human listener would need to do much more. For example, to figure out that ‘it’ in the question probably refers to ‘Maltese’ (rather than, say, ‘Italian’, which is possible though unlikely in this context). They would also need to figure out that ‘borrow’ is being used differently than when one says borrowing one’s sister’s car. After all, Maltese did not borrow words from Italian on a short-term basis. Clearly the correct interpretation of ‘borrow’ depends on the listener having identified the intended meaning of ‘Maltese’, namely, that it is a language. Watson was equipped with Automatic Speech Recognition technology to do exactly that.
To understand language any listener needs to go beyond mere sound. There are meanings and structures throughout all language levels. A human listener needs to go through them all before saying that they understood the message.
Watson was not just good at understanding; he was pretty good at speaking too. His answers were formulated in a crisp male voice that sounded quite natural, an excellent example of Text-to-Speech synthesis technology. In a fully-fledged human or machine communicating system, going from text to speech requires formulating the text of the message. The process could be thought of as the reverse of understanding, involving much the same levels of linguistic processing.
Machine: say ‘hello’ to Human
The above processes are all classified as Human Language Technology, which can be found in many devices. Human Language Technology can be found everywhere from Siri or Google Now in smart phones to a word processing program that can spell, check grammar, or translate.
Human-machine interaction relies on language to become seamless. The challenge for companies and universities is that, unlike artificial languages (such as those used to program computers or those developed by mathematicians), human languages are riddled with ambiguity. Many words and sentences have multiple meanings and the intended sense often depends on context and on our knowledge of the world. A second problem is that we do not all speak the same language.
Breaking through Maltese
Maltese has been described as a language in danger of ‘digital extinction’. This was the conclusion of a report by META-NET, a European consortium of research centres focusing on language technology. The main problem is a lack of Human Language Technology — resources like word processing programs that can correctly recognise Maltese.
Designing an intelligent computer system with a language ability is far easier in some languages than it is in others. English was the main language in which most of these technologies were developed. Since researchers can combine these ready-made software components instead of developing them themselves, it allows them to focus on larger challenges, such as winning a million dollars on a TV program. In the case of smaller languages, like Maltese, the basic building blocks are still being assembled.
Perhaps the most fundamental building block for any language system is linguistic data in a form that can be processed automatically by a machine. In Human Language Technology, the first step is usually to acquire a corpus, a large repository of text or speech, in the form of books, articles, recordings, or anything else that happens to be available in the correct form. Such repositories are exploited using machine-learning techniques, to help systems grasp how the language is typically used. To return to the Jeopardy example, there are now programs that can resolve pronouns such as ‘it’ to identify their antecedents, the element to which they refer. The program should identify that ‘it’ refers to Maltese.
For the Maltese language, researchers have developed a large text/speech repository, electronic lexicons (language’s inventory of its basic units of meaning), and related tools to analyse the language (available for free). Automatic tools exist to annotate this text with basic grammatical and structural information. These tools require a lot of manual work however, once in place, they allow for the development of sophisticated programs. The rest of this article will analyse some of the on-going research using these basic building blocks.
From Legalese to Pets
Many professions benefit from automating tasks using computers. Lawyers and notaries are the next professionals that might benefit from an ongoing project at the University of Malta. These experts draft contracts on a daily basis. For them, machine support is still largely limited to word processing, spell checking, and email services, with no support for a deeper analysis of the contracts they write and the identification of their potential legal consequences, partly through their interaction with other laws.
Contracts suffer from the same challenges when developing Human Language Technology resources. A saving grace is that they are written in ‘legalese’ that lessens some problems. Technology has advanced enough to allow the development of tools that analyse a text to enable extraction of information about the basic elements of contracts, leaving the professional free to analyse the deeper meaning of these contracts.
Deeper analysis is another big challenge in contract analysis. It is not restricted to just identifying the core ‘meaning’ or message, but needs to account the underlying reasoning behind legal norms. Such reasoning is different from traditional logic, since it talks about how things should be as opposed to how they are. Formal logical reasoning has a long history, but researchers are still trying to identify how one can think precisely about norms which affect definitions. Misunderstood definitions can land a person in jail.
Consider the following problem. What if a country legislates that: ‘Every year, every person must hand in Form A on 1st January, and Form B on 2nd January, unless stopped by officials.’ Exactly at midnight between the 1st and 2nd of January the police arrest John for not having handed in Form A. He is kept under arrest until the following day, when his case is heard in court. The prosecuting lawyer argues that John should be found guilty because, by not handing in Form A on 1st January he has violated the law. The defendant’s lawyer argues that, since John was under arrest throughout the 2nd of January he was being stopped by officials from handing in Form B, absolving him of part of his legal obligation. Hence, he is innocent. Who is right? If we were to analyse the text of the law logically, which version should be adopted? The logical reasoning behind legal documents can be complicated, which is precisely why tools are needed to support lawyers and notaries who draft such texts.
Figuring out legal documents might seem very different to what Watson was coping with. But there is an important link: both involve understanding natural language (normal every day language) for something, be it computer, robot, or software, to do something specific. Analysing contracts is different because the knowledge required involves reasoning. So we are trying to wed recent advances in Human Language Technology with advances in formal logical reasoning.
Illustration by Sonya Hallett
Contract drafting can be supported in many ways, from a simple cross-referencing facility, enabling an author to identify links between a contract and existing laws, to identifying conflicts within the legal text. Since contracts are written in a natural language, linguistic analysis is vital to properly analyse a text. For example in a rent contract when making a clause about keeping dogs there would need to be a cross-reference to legislation about pet ownership.
We (the authors) are developing tools that integrate with word processors to help lawyers or notaries draft contracts. Results are presented as recommendations rather than automated changes, keeping the lawyer or notary in control.
Robots ’R’ Us
So far we have only discussed how language is analysed and produced. Of course, humans are not simply language-producing engines; a large amount of human communication involves body language. We use gestures to enhance communication — for example, to point to things or mime actions as we speak — and facial expressions to show emotions. Watson may be very clever indeed, but is still a disembodied voice. Imagine taking it home to meet the parents.
“Robby the Robot from the 1956 film Forbidden Planet, refused to obey a human’s orders”
Robotics is forging strong links with Human Language Technology. Robots can provide bodies for disembodied sounds allowing them to communicate in a more human-like manner.
Robots have captured the public imagination since the beginning of science fiction. For example, Robby the Robot from the 1956 film Forbidden Planet, refused to obey a human’s orders, a key plot element. He disobeyed because they conflicted with ‘the three laws of robotics’, as laid down by Isaac Asimov in 1942. These imaginary robots look somewhat human-shaped and are not only anthropomorphic, but they think and even make value judgements.
Actual robots tend to be more mundane. Industry uses them to cut costs and improve reliability. For example, the Unimate Puma, which was designed in 1963, is a robotic arm used by General Motors to assemble cars.
The Unimate Puma 200
The Puma became popular because of its programmable memory, which allowed quick and cheap reconfiguration to handle different tasks. But the basic design was inflexible to unanticipated changes inevitably ending in failure. Current research is closing the gap between Robby and Puma.
Opinions may be divided on the exact nature of robots, but three main qualities define a robot: one, a physical body; two, capable of complex, autonomous actions; and three, able to communicate. Very roughly, advances in robotics push along these three highly intertwined axes.
At the UoM we are working on research that pushes forward all three, though it might take some time before we construct a Robby 2. We are developing languages for communicating with robots that are natural for humans to use, but are not as complex as natural languages like Maltese. Naturalness is a hard notion to pin down. But we can judge that one thing is more or less natural than another. For example, the language of logic is highly unnatural, while using a restricted form of Maltese would be more natural. It could be restricted in its vocabulary and grammar to make it easier for a robot to handle.
Take the language of a Lego EV3 Mindstorms robot and imagine a three-instruction program. The first would be to start its motors, the second to wait until light intensity drops to a specific amount, the third to stop. The reference to light intensity is not a natural way to communicate information to a robot. When we talk to people we are not expected to understand how the way we put our spoken words relates to their hardware. The program is telling the robot to: move forward until you reach a black line. Unlike the literal translation, this more natural version employs concepts at a much higher level and hence is accessible to anybody with a grasp of English.
The first step is to develop programs that translate commands spoken by people into underlying machine instructions understood by robots. These commands will typically describe complex physical actions that are carried out in physical space. Robots need to be equipped with the linguistic abilities necessary to understand these commands, so that we can tell a robot something like ‘when you reach the door near the table go through it’.
To develop a robot that can understand this command a team with a diverse skillset is needed. Language, translation, the robot’s design and movement, ability to move and AI (Artificial Intelligence) all need to work together. The robot must turn language into action. It must know that it needs to go through the door, not through the table, and that it should first perceive the door and then move through it. A problem arises if the door is closed so the robot must know what a door is used for, how to open and close it, and what the consequences are. For this it needs reasoning ability and the necessary physical coordination. Opening a door might seem simple, but it involves complex hand movements and just the right grip. Robots need to achieve complex behaviours and movements to operate in the real world.
The point is that a robot that can understand these commands is very different to the Puma. To build it we must first solve the problem of understanding the part of natural language dealing with spatially located tasks. In so doing the robot becomes a little bit more human.
A longer-term aim is to engage the robot in two-way conversation and have it report on its observations — as Princess Leia did with RT-D2 in Star Wars, if RT-D2 could speak.
Lego Mindstorms EV3 brick
Language for the World
Human Language Technologies are already changing the world. From automated announcements at airports, to smartphones that can speak back to us, to automatic translation on demand. Human Language Technologies help humans interact with machines and with each other. But the revolution has only just begun. We are beginning to see programs that link language with reasoning, and as robots become mentally and physically more adept the need to talk with them as partners will become ever more urgent. There are still a lot of hurdles to overcome.
To make the right advances, language experts will need to work with engineers and ICT experts. Then having won another million bucks on a TV show, a future Watson will get up, shake the host’s hand, and maybe give a cheeky wink to the camera.
Richard Feynman is my new idol. He’s hallucinated, he’s chatted up call girls, and he’s won a Nobel Prize. Realistically, I’ll probably only manage one of those achievements.
Surely you’re joking Mr Feynman!: Adventures of a Curious Character is as amazing a book as was Dick himself. He died of cancer in 1989, three years after the book was published.
The book is a great read and insight into his mind. It is compiled from a series of taped conversation that Feynman had with drumming partner Ralph Leighton. It haphazardly goes through his life from young radio mechanic to Professor at Caltech where he achieved most of his discoveries.
Throughout the book he randomly switches from girls, mathematics, academic life, to his adventures. This nicely sums up his life.
Take Brazil. He travelled there from Caltech during a sabbatical. There he learnt to play Samba music choosing the frigiderisa — a metal stick banged on a toy metal frying pan. ‘I practiced all the time. I’d walk along the beach […] practicing, practicing, practicing. I kept working on it, but I always felt inferior.‘ Insecurity that culminated in him walking down Brazil’s main streets, cars diverted, while his samba band made the streets dance.
“Once Feynman overcame his social awkwardness, he became a famous womaniser”
Feynman didn’t hold back his punches; if he didn’t agree with something he said it. He heavily criticised the Brazilian education system. ‘I tried to show them (students) how to solve problems by trial and error. […] I could never get them to ask […] questions.’ When surrounded by Brazil’s big shots, he said: ‘no science is being taught in Brazil. […] It’s amazing you don’t find many physicists in Brazil. Why is that?’ Magically, government listened.
Once Feynman overcame his social awkwardness, he became a famous womaniser. Girls crop up throughout most of the book. And he’s good. They would even buy him champagne and sandwiches. As most things in his life, he did it for fun and loved the game.
He writes a lot more about experiences with other women than with his three wives. His first wife’s death touched him deeply, however. ‘I didn’t cry until a couple of months later […] walking past a department store with dresses in the window.’ His other wives aren’t mentioned much.
Feynman also dabbled in drugs. He took ketamine, smoked marijuana, and might have taken LSD — denied in this book but suggested elsewhere.
He also had a short art career and managed to sell his paintings, though he lost his drive to paint by having a solo exhibition too early in his art career.
Another highlight of the book is Feynman’s colourful descriptions of the Manhattan Project that made the first atomic bomb, including how he lock-picked the project’s secrets. He also mentions his great discoveries but is incredibly humble and dismissive about his Nobel Prize — too much hassle. He beautifully describes how he came to his findings and his nervousness when meeting Einstein and Pauli.
Feynman’s genius and eccentricity is clear throughout the book. It will have you in fits. He went on all fours to sniff the world to see how much better dogs can sniff than us — apparently, not much. Life was his game, and boy did he play well.
Being in the second year of my banking, finance and management studies, innovation in these sectors is a key part of my curriculum. In banking one can easily see developments with the introduction of banking by telephone, internet and mobile. Similarly with management, recent growth has allowed the sector to grow and develop expertise in management of projects, accounting and supply chains.
Research — that would be the simplest way to answer the question above. Really and truly this answer would only apply to a small niche of individuals throughout the world.
Take the language of a 
