Earlier this month reports of a “robot scientist” made their rounds telling of a robotized lab and AI system that generated its own hypothesis, ran experiments to test them and with the process “discovered new functions for a number of genes in Saccharomyces cerevisiae, aka brewer’s yeast.” The robot, called Adam (cute), is being developed by Aberystwyth University and the University of Cambridge in the UK.

Then again this week there are news of what’s essentially a genetic algorithm that extrapolated the law of conservation of momentum, and Newton’s second law of motion from a pendulum’s swing; and without knowledge about physics and geometry.

A good week for the machines! Happy holidays =)

Automatic recommendations:

1. Absolut Adopts Machines & Artificial Creativity
2. Anthropocentric Approaches to Creativity

Not only do we lack understanding of our own creative mechanisms, but the basics of computer programs seem to oppose the idea of achieving unbound originality. Here’s a look at that important, fundamental problem when implementing creativity. In easy digest format, no less.

A Brief Introduction to Creativity

Crucial to what follows is pointing out that creativity is ill-defined and people generally have very different ideas of what it is. This can make it difficult to discuss and debate.

Art is typically strongly tied to creativity, and many scientists are focusing on this. The painting on the side was created by the computer program Aaron, which is one of the more famous creative systems. But while creativity exhibits itself very strongly amongst artists and is easily associated with them, that’s nowhere near the whole story. For example, there’s software like Thaler’s neural networks that have invented new, patentable physical materials. This is another type of creative expression.

And to go even further; in Emergence of Creativity, my chapter in the book Intelligent Complex Adaptive Systems, I explain and define creativity and its origins in a way that accounts for even the actions of primitive organisms — not only human abilities.

But for this article’s purposes, all we have to agree on is that creating something new or being original is an essential part of creativity. Given this agreement, we shouldn’t run into a problem with the following explanations. But even so, keep in mind how extremely multifaceted creativity is and that I’m simplifying the concept (to keep this article from becoming a book).

A problem when creating creative systems

To properly explain the problem, how programming seems to oppose creativity, we must understand what computer programs are: instructions. A set of steps the computer executes. Typically, when we create computer programs we specify a certain problem and in turn devise a set of instructions that addresses this problem.

A program that can add numbers is a very simple example of this: we specify that its input are numbers and operators, how it should apply the operators to the numbers and that the output should be the result of the computation. Note here that before we create a program we need to know what we want it to do and what instructions achieve that purpose.

Computer programs are instructions, even when they become more complex.

An example of a creative system

Consider an intelligent agent model. An agent is a system that perceives its environment (input) and acts upon that environment (output), and broadly speaking, an agent’s input can be anything from keystrokes to streaming video (or a combination).

Our agent is a writer, to stay within a creativity setting most are comfortable with (here’s to hoping you think people like Shakespeare are creative). For this particular case, the input is a human’s demanding to hear a story about a particular subject, like a story about detectives or robots. Our agent composes a story, puts it in a file and then acts upon the environment by displaying it on-screen.

But in order to make our agent write something other than gibberish, he must have a dictionary of words and he must know grammar. He must also have common sense to know how the world works or otherwise we’d be getting stories where a bucket drinks from a detective.

In the real world we would have to take our agent’s architecture quite a bit deeper. We would have had to give him some way of choosing plots, paragraphs and words, for example. But we’re going to look past that and just focus on what we already have at this point.

Instructions are limitations

Note now that when we gave our agent a dictionary, a goal, grammar knowledge and common sense, we effectively restricted him: He’s not a painter. He’s not a musical composer. He’s not a programmer, a witch, a lion or a wardrobe. And when we look at it as a creative writer, we begin to see he’s not that creative at all.

A goal limits the objectives of a system and thereby helps us organize how the system will behave¹: Our agents should write a story — he’s not about to write a groundbreaking paper about artificial creativity. And what about his stories? He has common sense that dictates no man can fly without the help of machines. We killed our creative agent’s Superman right there.

But these restrictions were also necessary for him to do anything at all. To explain this with a familiar analogy, it’s like writing a cooking recipe: To bake a cake we need certain ingredients. When we bake it the ingredients define what kind of cake it becomes. But we’re baking a cake, not bread. And the cake is sweet, not sour. The ingredients are restricted to define a particular outcome of the baking. Similarly, the instructions we devise are what defines a programs behavior and outcome.

Basically, to make it do what we want it to, we impose restrictions — a confined set of rules out of all the possible rules in the world.

What kind of instructions make limitless systems if instructions themselves are limitations?

Now here’s the core of the problem, finally: We agreed in the beginning of this article that an essential part of creativity is originality and creating something new. But like we’ve discussed above we know beforehand how a program should behave before we make it, including what it should produce.

The basics of programming require us to explicitly design mechanisms that produce certain outcomes. By giving these explicit instructions we inadvertently decrease the potential of the program surprising us since clearly it means that we know beforehand how it will behave.

The instructions that define our program (and make it work) are in turn the exact reason it can’t produce surprising, novel and interesting ideas.

But how about a self-organizing program that writes its own code on the fly to overcome its restrictions? Yes, that sounds appealing and is what many scientists working on artificial creativity are trying to do, in one form or the other. And it would be really easy too… if the program wouldn’t have to be creative to write new code!

Edit (Aug. 25th): Due to some comments from readers (thank you) I feel inclined to emphasize what I mentioned in the article: many creative systems have already been made (have a look through the creativity category).

I’ve personally created and worked on systems that present creative behavior. Making them more robust is just a question of time, research and development. The example used here is intentionally simple and raw to flesh out an essential problem that scientists face when developing creative systems—but this is a problem we are overcoming.

Links and References

• Aaron painting retrieved from Wikipedia
• ¹ Stuart Russell and Peter Norvig (2002). Artificial Intelligence: A Modern Approach (2nd edition). Prentice Hall. 60.

Automatic recommendations:

1. Absolut Adopts Machines & Artificial Creativity
2. The 5th International Workshop on Computational Creativity

Automatic recommendations:

1. Emergence of Creativity in Intelligent Complex Adaptive Systems
2. The 5th International Workshop on Computational Creativity

Chapter V, titled Emergence of Creativity: A Simulation Approach, presents my latest research on the emergence of creativity in natural and artificial organisms, a theory of its origins and potential grounds for future artificial implementations. The book is distributed internationally.

Intelligent Complex Adaptive Systems.
ISBN: 978-1-59904-717-1; IGI Publishing.

An official description of the research can be found below, but in short my approach does not exclude creative behavior in animals other than ourselves and explores a possible foundation of creative systems. Using computer simulations for support, the research combines several scientific concepts, techniques and methods of simulation; including evolutionary computation, cellular automata, emergence and self-organization.

Related Wikipedia articles: Emergence, Self organization, Computational creativity, Complex systems.

Emergence of Creativity – Chapter Introduction

The following is an excerpt from the preface to ICAS provided by the editors; Dr. Ang Yang and Dr. Yin Shan.

The third section of this book features four chapters on the use of modern computing techniques to study the emergence of creativity, emergent specialisation, information bottleneck to central processing in adaptive systems and the role of barriers to information flows in the robustness of complex systems.

Creativity has been a difficult concept to define and its exact relationship with intelligence remains to be explained. In the first of the four chapters on computing techniques, Thórisson presents a theory of natural creativity and its relation to certain features of intelligence and cognitive faculties. To test the theory, the author employs simulated worlds of varying complexity that are inhabited by creatures with a genetically evolving mental model. Planmaking strategies are compared between creatures in each world. This shows that creative behaviours are governed by the world’s structural coherence and complexity. The theoretical framework presented in this chapter may serve as a foundation and tool to improve our understanding of natural creativity and to help develop creative artificially intelligent systems.

Interested can look to Amazon in the UK and US, and Barnes & Noble. You can also try finding a local store via the used & new links on Amazon, or Google’s Product Search.

About the Book

The following is the official & compressed introduction to the book’s content and purpose.

As the world currently subsists as a platform for exchange among complex, intelligent systems that are constantly adapting and evolving to suit the surrounding physical, sociological, emotional, and sensory environment, understanding the theory and emergence of complex adaptive systems is of paramount importance.

Intelligent Complex Adaptive Systems explores the foundation, history, and theory of intelligent adaptive systems, providing scholars, researchers, and practitioners with a fundamental resource on topics such as the emergence of intelligent adaptive systems in social sciences, biologically inspired artificial social systems, sensory information processing, as well as the conceptual and methodological issues and approaches to intelligent adaptive systems.

Note these links to a the book detail page at IGI, comprehensive introduction to the table of contents, and an introductory brochure (PDF).

Automatic recommendations:

1. The 5th International Workshop on Computational Creativity

Taking its cues from Google News Alerts on “robotics”, the system analyzes news articles — identifying and extracting relevant lines of text and generating a shorter version of the article. The text is then paraphrased using preset tunings to mimic my writing style. The ultimate result is an article that only needs my one-click administrator approval to be published.

The TOWTAW System (“Toto”)

The system, named The One Who Thinks Artificially & Writes (TOWTAW, pronounced ‘Toto’, as in OZ), is an example of AI systems integration, comprising several software modules that communicate through a central blackboard system.

Relevance ranking of paragraphs and sentences (understanding the text) is accomplished by a custom made module that makes use of the OpenCyc reasoning engine and the Open Mind Common Sense Net (a.k.a. ConceptNet). The excerpted text is paraphrased by another module that again makes use of these two systems, whose combined strength is hundreds of thousands of terms and logical expressions. This entire process is complimented by a third, custom software module that accesses the Wordpress database and tries to find sentences written by me that can be re-used. This is done to further improve writing style similarity.

Finally, the system makes use of Wordpress’ Post-by-email option, simply using my machine to mail in the post to await my admin approval. It’s worth noting that I rarely have to retouch the text.

So Long, and Thanks for All the Fish

With the continued success of the system, and the many great comments on the articles (it has even started debates!) — I’ve decided to leave Think Artificial entirely in the hands of artificial authors. The site, starting next week, will be renamed Think Artificial and Writes. Additionally, I’m opening several new blogs — including one called TOWTAW Row-baw-toh about Western musical adaptations of Asian robot culture.

I thank you very much for your support and compliments on my writings, and will announce at a later date where I plan on start writing online again.

Best regards,
-Hrafn Th.

[[This was April Fools' Day joke for 2008. Read this for the hidden joke]]

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The Absolut Machines

By visiting Absolut Machines you’ll eventually find yourself on a page with two live videofeeds, presented in an old-school, gray window system. One of the machines is placed in Stockholm, Sweden and the other in New York City. The machines at these locations are music-composing AI systems you can interact with to augment the music they generate.

The interaction sessions are recorded and you can get a compressed quicktime video of your visit sent via email or download it from the “Gallery” tab which lists all recent videos.

Think Artificial VIP Access
Dearly devoted Think Artificial readers have been allotted VIP codes that allow cutting to the front of the line to interact with the machines. Leave a comment on this entry and I’ll mail it to the address you enter in the comment form. Alternatively you can contact me directly. Note that there’s a limited supply of codes and they’ll be distributed on a first come first served basis.

Obligatory disclaimer: To participate in this giveaway you must be at least 21 years of age.

Absolut Choir

The Absolut Choir is a system composed of speech synthesizers implemented in the physical form of 10 robotic characters. Each of the machines, or choir members, has a unique voice ranging from women, to tenors and sopranos. A “mother character” virtually conducts by synchronizing and distributing sounds to the other members, each of which contains a Linux box for processing and a speaker.

As the Choir starts singing, the user may input words to the machine. As the machine receives the words, it immediately uses them to generate a musical composition and lyrics. The robotic choir follows the lead of its human partner, and with the help of generative algorithms, the machine engenders a melody, tempo, dynamics, timbre and lyrics inspired by the user-generated input. The composition is also infused with the machine’s current mood and from the most recently analyzed words input by previous users. A lot of short words with many consonants may result in a fast arpeggio-like song, while softer words may result in a slower composition. [Absolut Press Kit]

The sound feed was suffering from some technical difficulties when I tried the choir. But the video worked, and the choir was receiving my lyrics glorifying Think Artificial (I figured I’d attempt to create a themesong for us).

The video compilation I received afterwards was okay. But I discovered that the lyrics were (intentionally) rendered hieroglyphic by the choir, so it sadly doesn’t make the cut as our themesong.

Absolut Quartet

The Quartet is quite different from the Choir. The machines are three; the main one is a marimba which the system plays by shooting rubber balls into the air, aimed at the marimba keys it wants to hit — or multiple balls if the objective is to play a chord. It’s quite fun to look at.

The marimba rubber ball blaster implementation and design.

Overview of the Quartet under construction.

The second machine is a series of glasses which basically replicate the “finger on a wine glass trick”. The glasses are spun, each tuned to a various pitches, and small robotic fingers touch them to produce sounds. The third part of the installation is an automated percussion instrument.

And then there’s the fourth part, us – the users. At the beginning of a session the human user plays notes on a miniature piano. The melody played dictates what kind of music the Quartet will produce, or in other words, your input is the machines inspiration for a following 3 minute song.

The machines are brainchilds of Dan Paluska and Jeff Lieberman. Both of which attend at MIT and have many cool projects in their backpack that combine aesthetics, artificial intelligence, kinetic sculpting and robotics.

Looking Closer at Robotics in the Media

This project is not an academic foray into the realms of creative AI, but rather a project intended to be looked at in terms of aesthetics. That being said: The artificial creativity of the machines is very primitive. If we take for example how the Quartet works; the software takes the melody played by a human user and compares it to a pre-existing collection of songs. Once a similar match has been found the machine mixes the two together producing the ultimate outcome. What interested me more than the software implementation of creativity was the overall aesthetic appeal of the project. In addition to Jeff and Dan’s artwork, the media related to this campaign was superb (partly handled by Noise Marketing, creators of the Appleseed website).

When exploring how we are creating our world; augmenting our environment — it’s intriguing to zoom out of AI context: How we (humans) advertise and perceive products is environmental augmentation. The ultimate sentiment is to be aware of the augmentations. To study them. Be aware of their effect and purpose; and to adapt and further develop whatever it is we want to achieve.

When I saw AI-colored advertisements from a major company (a company that essentially has nothing to do with machines) I immediately wondered whether it gave an indication of the public appeal of robots in Western societies. Certainly, machines in general play a larger role in everyone’s lives than ever before; and the same can be said about robotics even though we’re still in very early stages of that development. When we note that Puma has been sporting robotic-prosthetic cyberpunk campaigns as well, I think we can at least safely venture that robotics are on the rise in terms of public interest.

Automatic recommendations:

1. Robot Uprising 2008-2015, Market to Reach $15B
2. The 5th International Workshop on Computational Creativity

Click through for additional information and the official announcement.

You can download the full call for papers (PDF) from Think Artificial, or visit the workshop’s website for more information such as submission requirements & contact information.

The following is part of the official announcement, describing the objectives and topics of the workshop.

Computational Creativity Workshop Objectives

The aim of the workshop is to facilitate exchange of ideas on the topic of computational creativity. It will bring together people from AI, Cognitive Science and related areas such as Psychology, Philosophy and the Arts who research questions related to the notion of creativity with respect to computers.

The workshop will address issues such as how we assess creativity in computers, how computers can model creative thought, how computers can be used to enhance human creativity, and how we can implement creative software systems. The workshop will include papers on the many and various aspects of computational creativity, and will showcase the applications of computational creativity to the sciences, creative industries and arts.

The workshop will provide a forum for identifying trends and opportunities for research on creativity and promising practices concerning the development of creative systems. In addition, there will be a “show and tell” session, which will be devoted to demonstrations of systems exhibiting behaviour which would be deemed creative in humans.

Computational Creativity Topics

Original contributions are solicited in all areas related to Creative Systems, including but not limited to:

• Computational models of creativity.
• Cognitive models of creativity.
• Metrics, frameworks and formalizations for the evaluation of creativity in computational systems.
• Computational tools for supporting creativity.
• Specific applications to music, language and the arts, to architecture and design, to scientific discovery, to education and to entertainment.
• Philosophical discussions of computational creativity.
• Detailed system descriptions of creative systems, including engineering difficulties faced, example sessions and artefacts produced, and applications of the system.

You can find links to the previous workshops on Think Artificial’s Artificial Creativity page. The page has been updated to include a permament link to IJWCC’08.

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As mentioned in the first post on the Living Article, and on the page itself, this is work in progress that’s gradually improved. But the initial subsections of the External Links are as follows:

• Conferences and Consortiums

Currently contain only the Computational Creativity workshops that’ve been held regularly in recent years.

• Books and literature

Needs some work, but does include what is perhaps the most often recited book on creativity and computers. Future additions will include significant papers and noteworthy books on or related to the subject.

• Labs, Institutes and Companies

Currently contains three links. Should be institutes that fund or otherwise do explicit R&D of artificial creativity.

• Miscellaneous Resources

Various other resources that are not easily categorized or contain assorted information. Such as the Wikipedia entries and the AAAI creativity resource.

Currently missing are Examples of Creative Systems which should be incorporated into the article itself as well as maintained in external links (i.e. additional readings and online examples).

To sum up, this is a bare bones collection of links. But a collection nonetheless. If you have something to add drop me a comment here or via the contact form!

Links and References

• Artificial Creativity on Think Artificial

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Placed in a dark room with one lit button that turns on the lights, and one unlit button that opens the door out, the AIBO is given the goal of getting out of the room. It’s too dark for him to see the unlit Open button, so the idea is that he should learn to turn on the lights first. Watch the video to see what happens.

Did you figure it out before watching? The AIBO is part of a research program at the Rutgers Laboratory for Real-Life Reinforcement Learning, and the video was submitted to the AAAI-07 video competition earlier this year (and won for best short video).

These kinds of surprising solutions are often fun, and not that uncommon. I’ve experienced similar things myself, where creatures in a simulation I was developing found a way to get around a programming fault — effectively using their own intelligence to counter a mistake that human error had left in the fabric of their universe.

Links and References

• Rutgers Laboratory for Real-Life Reinforcement Learning
• Video Collection from the AAAI ‘07 Video Competition
• AIBO on Wikipedia (picture under FDL license)
• Reinforcement Learning on Wikipedia

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It’s an unfortunate fact that there’s no single, online information source that covers machines that can compose music, invent patentable ideas, or make up stories on their own (yes, all of these exist). So, let’s fix that, shall we?

Today I’m introducing something new on Think Artificial: A Living Article. It’s not exactly a blog entry, wiki nor a static page, but an article that I intend to gradually add to and improve upon. The article is an easy-read overview of artificial creativity, or at least the beginning of one. You can always find it through the main menu, and I’ll be posting notifications whenever it’s significantly updated. Moreover, I invite you to help create it!

I thought it’d be cool to try see if we couldn’t put together a bit of an overview of the field, along with examples, a link repository and photo collection of research currently being carried out. As I announced recently, I’m going to be covering a bit more of creativity here and I’ll be using material from those entries to gradually build up the Living Article.

Living Article?

Yeah, so I’m not inventing anything new here. It’s just a webpage that gets updated and built up gradually. But as it’s being made explicitly for continual updating rather than being a typical static webpage, and because it isn’t a Wiki page (only I edit, for now), I thought’d would make sense to label it somehow. Mainly I just wanted a name for it, and I think ‘Living Article’ sounds good. Plus, it allows for an ultra-cool double helix banner

Take Part in the Action!

To make this more exciting and informative, I’d like to ask you to send along questions or comments you might have on the artificial creativity! To give you some ideas and get that gray matter cranking:

• If you make a program that invents, is it really the program that’s inventing rather than the programmer?
• Is a computer that can produce art really creative if it can’t appreciate aesthetics?
• Can computers ever really create anything new, they only do what we tell them to, don’t they?

I can’t promise I’ll be able to answer all of them, but I can promise that I’ll do my best. And, of course, I welcome any suggestions, links and general comments on the page! One more thing, if YOU want to answer something, or discuss something on creativity — drop me a line and we’ll see if we can either integrate it into the Overview or alternatively make it a guest post here.

And then…?

I’m going to see if this is a good idea. See what the response is like. Perhaps I’ll put up more articles like this here if things work out. Maybe we could even donate it eventually to Wikipedia, seeing how the artificial creativity page there is a bit sad to look at. But for now this single page stays up and I look forward to hearing your thoughts on it! Currently, it’s styled like an encyclopaedic article — pretty dry and reciting facts. I’m wondering whether it would serve more purpose that way, or if I should make it more casual.

What do you think? Encyclopaedic or casual? (I’m just talking about the article, not the posts on Think Artificial. They have their own style.)

Links and References

• An Overview of Artificial Creativity
• Artificial Creativity on Wikipedia

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Creativity is a very, very complex subject. If you think creativity only involves art, such as making music, writing, painting, dancing or something similar — you’re wrong. Or rather, you’re underestimating the idea. Surely, creativity exhibits itself very strongly amongst artists and is therefore easily associated with them, but that’s nowhere near the whole story.

When we need to fulfill a goal. Say, we’re at our uncles cabin and we want to go fishing in the lake but we don’t have a fishing rod. What do we do? Someone, somebody creative, might go outside and find a branch. Attach a string to that branch and bend a nail for a hook. Somebody else might take it a step further and decide a lousy branch isn’t enough — he wants the fat fish — and fetch a few blankets to use as a net. The third might jog to the store and simply buy a real rod.

What do each of these persons need to do this? Most will agree that we need intelligence. We need to be able to figure out a solution to our problem. But where do the ideas originally come from? Even mundane things involve creative efforts.

Creativity is invention, it’s creating things. It’s finding solutions to problems. Finding a way to catch underwater creatures involves creating something, and portraying the feeling “anger” on a canvas involves creating something. Even if you don’t have to create something physical, you’re constructing something in you’re mind — creating an idea of what you’re going to do. How are we able to create solutions that we might potentially never have seen or heard of? Moreover, how is this ability to create solutions related to intelligence?

It’s not pure logical deduction. If it were, things would be much simpler (and more boring, I daresay). People often get ideas that seem illogical to pursue, yet continue to think about them. We’re not bound by logic when we imagine. We can imagine quite illogical things. What are these mechanism, why are they here and how do they work?

These are the puzzles I try to decipher every day, in the persuit for a machine that will one day be able to help us invent new things. New machines, new spaceshuttles, computers and medication. The minds of robots, laced with creative abilities, handle unexpected situations on their own initiative.

We’ve already seen AI systems do it to some extent. We keep working on expanding these systems, and they keep getting better at it. I asked earlier whether computers would ever be capable of invention. They are.

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The simulation takes physics into account: each structure is evaluated depending on its joints and external (gravitational) forces. The propagated force of the entire structure is then used to determine whether the load is too much — whether the system needs to add or remove bricks somewhere to avoid collapsing (“dying”).

The Lego brick structures are represented as trees in the simulator, and it’s to this structure that genetic operators are applied: Mutations modify a brick’s size or position and recombinations interchange subtrees of root-bricks.

The system can thus be given a goal, such as building a bridge over a large gap; you can see an animated gif of this process — where they gave it the goal of bridging a gap between two tables in their lab. The end results are quite interesting to the eye, in two words I’d describe them as “naturally messy”.

The crane’s evolved design is noteworthy. To counteract the load posed on the crane-arm itself, the structure evolve a J-shaped crown that extended from its back, as evident on the picture above. Picture (c) shows the intermediate stages of the crane, picture (d) shows the crane in its final stages — where the counter-balancing structure evolved a solid connection with the base. The below diagram shows the design of the crane in three stages (top is first stage, bottom final stage).

It’s interesting how genetic algorithms result in, like I said before, naturally messy constructs. This is actually one of the reasons that genetic algorithms are popular within artificial creativity research. Evolution results in various “unanticipated” or “surprising” constructs which can be perceived as creative. The problem with this approach to creativity presents itself if you want a creative machine that creates less messy structures. You’d invevitably have to add additional constraints which would in turn minimize the surprising factor of the solution — voiding it of “creativity”. Quite an interesting dilemma.

Related Links & References

• EvoCAD Page
• EvoCAD crane (with video)
• Dr. Pablo Funes’ Website

[All photos courtesy of Dr. Pablo Funes]
[tags]artificial creativity, artificial intelligence, simulation, genetic algorithms, EvoCAD[/tags]

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MakeBelieve is one of these creative system. In short, MakeBelieve uses ConceptNet, an open-source common sense database to generate short stories of various sorts. Created in 2002 by Hugo Liu of the MIT Media Lab, the system works interactively: The user initially writes a short sentence and MakeBelieve attempts to write a following story.

Using a common sense knowledgebase the agent (MakeBelieve) makes assumptions about the real world, keeping him from venturing outside a logical framework of a story’s structure. Liu’s site provides some great examples, here’s one from the example file:

Generated Story Example

John became very lazy at work. John lost his job
John decided to get drunk. He started to commit crimes.
John went to prison. He experienced bruises.
John cried.
He looked at himself differently.

John went to prison. He experienced bruises — that line cracks me up. Unfortunately the system is not available for public downloading, so I can’t have it create a story about myself for this post as I had hoped. But how does it work? Basically, the common-sense database contains a series of cause-and-effect sentences like publishing a blog entry means other people can read it, or a consequence of flying is jet-lag. These causes and effects are extracted from the base and used in a kind of if-then manner to link together a story, using synonyms and analogous elements to make the sentence structure look less if-then’ny (and to add a bit of creative spice). Of course, this is an overt oversimplification, making it sound a lot less “magical” — and by magical I mean, of course, intelligent. Check out the links at the bottom of this post for details.

It’s hard to tell from selected examples how well the system generally does, it depends a lot on the size of the knowledge base — which in this case is about 9.000 causality-sentences. We can safely venture that it’s limited at best, as it has no means to construct levels, or phases in the story, nor can it handle more than one character it seems. Nonetheless, it’s interestingly good at short stories.

If you’re interested in trying your hand on artificial creativity in linguistics and story generation, ConceptNet is a fine foundation for building projects on. The latest version is written in Python, but if that’s not your cup of coffee — there’s also an older version written in Java available. In addition to all of that you can interface the Python version with any language through an XML-RPC server.

References

• Hugo Liu’s page (scientific paper included)
• The MakeBelieve project page

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Okay, so the deal is that a bird’s nest is an example of creativity in animals other than humans (it is, although it isn’t Al Yankovic creativity). I needed an picture of that for my latest publication and unfortunately I didn’t have one at hand.

I didn’t dare get one online, as you can never be certain if the licensing declarations are correct — so I had to just go ahead and start flipping through old family albums in hopes of finding one. That didn’t quite work out, so I started making calls. Now, for any other country — a zoo would have been an obvious choice. But Iceland doesn’t have a real zoo. We have a farm-animal zoo. Isn’t that exciting? (Come on, you get to pat the pigs!¹) And of course, all of their bird’s nests are artificial. How ironic. Here I am, an artificial intelligence developer on the hunt for natural creativity, and all I find are artificial constructs. Gargh.

Remarkably, as village-like as Reykjavik might seem to foreign eyes — we sure don’t have a lot of bird’s nests lying around. And not a lot of farm savviness either. Just the other day a girl my age I’m doing a project with reached into her purse and pulled up a shotgun shell. She then stared at me and asked “What is it?“. Somebody had given it to her and she’d been carrying it around for days, banging the purse against all kinds of things. She didn’t dare touch it after I told her what it was.

All went well in the end. My publication is ready. Funny, I didn’t realize until I was halfway through this hunt for a bird’s nest, how far I’d strayed from the stereotypical “Computer Science” activities. It felt a bit like being to artificial intelligence what Indiana Jones is to archaeology.

Now stay tuned for our next event, when I find myself traveling to an old, desolate and booby trapped temple in search of examples of historical creative efforts, and swapping the bag of sand for the Golden Algorithm.

¹Sense the irony.

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Some of you might have noticed that I didn’t mention anything about security last time. Well, that’s because there wasn’t any. Not that I know of, anyway. Iceland is extremely peaceful when it comes to harassing politicians, so during a small gathering like this one nobody’s worrying. Amazing, I’m proud of it.

Last time I left off where I was being led into another room, this was the main ceremonial area — with a podium set up (but oddly, no chairs). We didn’t have to wait, it was shortly announced that the President would now do a speech. I was pleasantly surprised by the humorous remarks during the speech, one of which went something like

“We Icelanders have always been inclined to make discoveries — but have the habit of not telling anyone about them. Leifur Eiriksson discovered America … and then just went home again to take care of the farm.”

The speech was also inspiring, or maybe it was just because it was coming from my countries leader, someone I respect — it’s hard to make a distinction (is it the speech that makes a President, or the President that makes the speech?). Meanwhile, the group were standing around (no chairs, remember) and I was anxiously trying to look normal. Insomnia had been having its go at me the night before, so that was kind of throwing me off balance.

One thing that really struck me as odd during all of this were the reporters. Man, are they rude. One of them was playing around with his phone during the speech, occasionally letting out interrupting beeps and bleeps. Another decided to unwrap some candy with snarkly noises, and yet another had fun taking pictures with his phone with the camera-clicking sound turned on (you know, that fake “cli-click” sound).

Well, to slice off some uninteresting tidbits, let’s skip to the next fun thing. The President and the First Lady stepped back, and the director of the Icelandic Student Innovation Fund introduced all of the nominated projects, and I must say that he did a pretty good job with mine, giving me some extra attention. My project was on my theory of creativity, how it works and where it came from. I created a simulation in which A.I. agents showed creativity — so it almost made me burst out with laughter when the director ended his speech with:

“Quite remarkable, and I must say that, in a way, I hope he doesn’t get much further with his research, otherwise he’ll become like god almighty!”

At that moment I’d sort of realized that since he was making such an effort in describing my project, I probably wouldn’t receive the main award. As was actually to be expected as this award takes practicality and applications to industry greatly into consideration; my project is still in its initial stages and largely theoretical. But since then I’ve been humorously referring to myself as Hrafn Almighty. After this final comparison of me and my god-like future, the President stepped forth with my plaque (I can’t find the word for it, honorary plaque?). I’d been hoping to get a picture of me shaking hands with him before this post, but couldn’t and compensate with this one below. I’m the one on the far left. The President on the far right.

I shook his hand and he congratulated me on my achievements, handing me the framed plaque with his signature, while the (rude) reporters snapped their pictures. The main award went to a project on health sciences and genetics, I had a chance later to look briefly through the report on it and must say that from the looks of it, it deserved to win. Of course it was a bit dissapointing (I’m human, after all), but I’m working on AI because I’m interested in it, enjoy it, and think that I can make a contribution to science. That in itself is very rewarding and this was pure bonus The President added after the ceremony that due to the extreme quality of all the projects, he’d felt more like he was handing out a Nobel Prize.

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