This is a five minute video in which I was asked to make some predictions for the next decade about the Semantic Web, search and artificial intelligence. It was done at the NextWeb conference and was a fun interview.
Learning from the Future with Nova Spivack from Maarten on Vimeo.
Earlier this month I had the opportunity to visit, and speak at, the Digital Enterprise Research Institute (DERI), located in Galway, Ireland. My hosts were Stefan Decker, the director of the lab, and John Breslin who is heading the SIOC project.
DERI has become the world's premier research institute for the Semantic Web. Everyone working in the field should know about them, and if you can, you should visit the lab to see what's happening there.
Part of the National University of Ireland, Galway. With over 100 researchers focused solely on the Semantic Web, and very significant financial backing, DERI has, to my knowledge, the highest concentration of Semantic Web expertise on the planet today. Needless to say, I was very impressed with what I saw there. Here is a brief synopsis of some of the projects that I was introduced to:
In summary, my visit to DERI was really eye-opening and impressive. I recommend that major organizations that want to really see the potential of the Semantic Web, and get involved on a research and development level, should consider a relationship with DERI -- they are clearly the leader in the space.
This is a video of me giving commentary on my "Understanding the Semantic Web" talk and how it relates to Twine, to a group of French business school students who made a visit to our office last month.
Nova Spivack - Semantic Web Talk from Nicolas Cynober on Vimeo.
I've been thinking lately about whether or not it is possible to formulate a scale of universal cognitive capabilities, such that any intelligent system -- whether naturally occurring or synthetic -- can be classified according to its cognitive capacity. Such a system would provide us with a normalized scientific basis by which to quantify and compare the relative cognitive capabilities of artificially intelligent systems, various species of intelligent life on Earth, and perhaps even intelligent lifeforms encountered on other planets.
One approach to such evaluation is to use a standardized test, such as an IQ test. However, this test is far too primitive and biased towards human intelligence. A dolphin would do poorly on our standardized IQ test, but that doesn't mean much, because the test itself is geared towards humans. What is needed is a way to evaluate and compare intelligence across different species -- one that is much more granular and basic.
What we need is a system that focuses on basic building blocks of intelligence, starting by measuring the presence or ability to work with fundamental cognitive constructs (such as the notion of object constancy, quantities, basic arithmetic constructs, self-constructs, etc.) and moving up towards higher-level abstractions and procedural capabilities (self-awareness, time, space, spatial and temporal reasoning, metaphors, sets, language, induction, logical reasoning, etc.).
What I am asking is whether we can develop a more "universal" way to rate and compare intelligences? Such a system would provide a way to formally evaluate and rate any kind of intelligent system -- whether insect, animal, human, software, or alien -- in a normalized manner.
Beyond the inherent utility of having such a rating scale, there is an additional benefit to trying to formulate this system: It will lead us to really question and explore the nature of cognition itself. I believe we are moving into an age of intelligence -- an age where humanity will explore the brain and the mind (the true "final frontier"). In order to explore this frontier, we need a map -- and the rating scale I am calling for would provide us with one, for it maps the range of possible capabilities that intelligent systems are capable of.
I'm not as concerned with measuring the degree to which any system is more or less capable of some particular cognitive capability within the space of possible capabilities we map (such as how fast it can do algebra for example, or how well it can recall memories, etc.) -- but that is a useful second step. The first step, however, is to simply provide a comprehensive map of all the possible fundamental cognitive behaviors there are -- and to make this map as minimal and elegant as we can. Ideally we should be seeking the simplest set of cognitive building blocks from which all cognitive behavior, and therefore all minds, are comprised.
So the question is: Are there in fact "cognitive universals" or universal cognitive capabilities that we can generalize across all possible intelligent systems? This is a fascinating question -- although we are human, can we not only imagine, but even prove, that there is a set of basic universal cognitive capabilities that applies everywhere in the universe, or even in other possible universes? This is an exploration that leads into the region where science, pure math, philosophy, and perhaps even spirituality all converge. Ultimately, this map must cover the full range of cognitive capabilities from the most mundane, to what might be (from our perspective) paranormal, or even in the realm of science fiction. Ordinary cognition as well as forms of altered or unhealthy cognition, as well as highly advanced or even what might be said to be enlightened cognition, all have to fit into this model.
Can we develop a system that would apply not just to any form of intelligence on Earth, but even to far-flung intelligent organisms that might exist on other worlds, and that perhaps might exist in dramatically different environments than humans? And how might we develop and test this model?
I would propose that such a system could be developed and tuned by testing it across the range of forms of intelligent life we find on Earth -- including social insects (termite colonies, bee hives, etc.), a wide range of other animal species (dogs, birds, chimpanzees, dolphins, whales, etc.), human individuals, and human social organizations (teams, communities, enterprises). Since there are very few examples of artificial intelligence today it would be hard to find suitable systems to test it on, but perhaps there may be a few candidates in the next decade. We should also attempt to imagine forms of intelligence on other planets that might have extremely different sensory capabilities, totally different bodies, and perhaps that exist on very different timescales or spatial scales as well -- what would such exotic, alien intelligences be like, and can our model encompass the basic building blocks of their cognition as well?
It will take decades to develop and tune a system such as this, and as we learn more about the brain and the mind, we will continue to add subtlety to the model. But when humanity finally establishes open dialog with an extraterrestrial civilization, perhaps via SETI or some other means of more direct contact, we will reap important rewards. A system such as what I am proposing will provide us with a valuable map for understanding alien cognition, and that may prove to be the key to enabling humanity to engage in successful interactions and relations with alien civilizations as we may inevitably encounter as humanity spreads throughout the galaxy. While some skeptics may claim that we will never encounter intelligent life on other planets, the odds would indicate otherwise. It may take a long time, but eventually it is inevitable that we will cross paths -- if they exist at all. Not to be prepared would be irresponsible.
There has been a lot of hype about artificial intelligence over the years. And recently it seems there has been a resurgence in interest in this topic in the media. But artificial intelligence scares me. And frankly, I don't need it. My human intelligence is quite good, thank you very much. And as far as trusting computers to make intelligent decisions on my behalf, I'm skeptical to say the least. I don't need or want artificial intelligence.
No, what I really need is artificial stupidity.
I need software that will automate all the stupid things I presently have to waste far too much of my valuable time on. I need something to do all the stupid tasks -- like organizing email, filing documents, organizing folders, remembering things, coordinating schedules, finding things that are of interest, filtering out things that are not of interest, responding to routine messages, re-organizing things, linking things, tracking things, researching prices and deals, and the many other rote information tasks I deal with every day.
The human brain is the result of millions of years of evolution. It's already the most intelligent thing on this planet. Why are we wasting so much of our brainpower on tasks that don't require intelligence? The next revolution in software and the Web is not going to be artificial intelligence, it's going to be creating artificial stupidity: systems that can do a really good job at the stupid stuff, so we have more time to use our intelligence for higher level thinking.
The next wave of software and the Web will be about making software and the Web smarter. But when we say "smarter" we don't mean smart like a human is smart, we mean "smarter at doing the stupid things that humans aren't good at." In fact humans are really bad at doing relatively simple, "stupid" things -- tasks that don't require much intelligence at all.
For example, organizing. We are terrible organizers. We are lazy, messy, inconsistent, and we make all kinds of errors by accident. We are terrible at tagging and linking as well, it turns out. We are terrible at coordinating or tracking multiple things at once because we are easily overloaded and we can really only do one thing well at a time. These kinds of tasks are just not what our brains are good at. That's what computers are for - or should be for at least.
Humans are really good at higher level cognition: complex thinking, decisionmaking, learning, teaching, inventing, expressing, exploring, planning, reasoning, sensemaking, and problem solving -- but we are just terrible at managing email, or making sense of the Web. Let's play to our strengths and use computers to compensate for our weaknesses.
I think it's time we stop talking about artificial intelligence -- which nobody really needs, and fewer will ever trust. Instead we should be working on artificial stupidity. Sometimes the less lofty goals are the ones that turn out to be most useful in the end.
Scoble came over and filmed a full conversation and video demo of Twine. You can watch the long version (1 hour) or the short version (10 mins) on his site. Here's the link.
This is written in response to a post by Anne Zelenka.
I've been talking about the coming "semantic graph" for quite some time now, and it seems the meme has suddenly caught on thanks to a recent article by Tim Berners-Lee in which he speaks of an emerging "Giant Global Graph" or "GGG." But if the GGG emerges it may or may not be semantic. For example social networks are NOT semantic today, even though they contain various kinds of links between people and other things.
So what makes a graph "semantic?" How is the semantic graph different from social networks like Facebook for example?
Many people think that the difference between a social graph and a semantic graph is that a semantic graph contains more types of nodes and links. That's potentially true, but not always the case. In fact, you can make a semantic social graph or a non-semantic social graph. The concept of whether a graph is semantic is orthogonal to whether it is social.
A graph is "semantic" if the meaning of the graph is defined and exposed in an open and machine-understandable fashion. In other words, a graph is semantic if the semantics of the graph are part of the graph or at least connected from the graph. This can be accomplished by representing a social graph using RDF and OWL, the languages of the Semantic Web.
Continue reading "Defining the Semantic Graph -- What is it Really?" »
The New Scientist just posted a quick video preview of Twine to YouTube. It only shows a tiny bit of the functionality, but it's a sneak peak.
We've been letting early beta testers into Twine and we're learning a lot from all the great feedback, and also starting to see some cool new uses of Twine. There are around 20,000 people on the wait-list already, and more joining every day. We're letting testers in slowly, focusing mainly on people who can really help us beta test the software at this early stage, as we go through iterations on the app. We're getting some very helpful user feedback to make Twine better before we open it up the world.
For now, here's a quick video preview:
Jason just blogged his take on an official definition of "Web 3.0" -- in his case he defines it as better content, built using Web 2.0 technologies. There have been numerous responses already, but since I am one of the primary co-authors of the Wikipedia page on the term Web 3.0, I thought I should throw my hat in the ring here.
Web 3.0, in my opinion is best defined as the third-decade of the Web (2010 - 2020), during which time several key technologies will become widely used. Chief among them will be RDF and the technologies of the emerging Semantic Web. While Web 3.0 is not synonymous with the Semantic Web (there will be several other important technology shifts in that period), it will be largely characterized by semantics in general.
Web 3.0 is an era in which we will upgrade the back-end of the Web, after a decade of focus on the front-end (Web 2.0 has mainly been about AJAX, tagging, and other front-end user-experience innovations.) Web 3.0 is already starting to emerge in startups such as my own Radar Networks, but will really become mainstream around 2010.
Why is defining Web 3.0 as a decade better than just about any other possible definition of the term? Well for one thing, it can't easily be co-opted by any company or individual for their own commercial ends. It's also a completely unambiguous definition -- it refers to a particular time period and everything that happens in Web technology during that period. This would end the debate about what the term means and move it to something more useful to discuss: What technologies and trends will actually become important in the coming decade of the Web?
It's time to once again pull out my well-known graph of Web 3.0 to illustrate what I mean...
(Click the thumbnail for a larger, reusable version)
I've written fairly extensively on the subjects of defining Web 3.0 and the Semantic Web. Here are some links to get you started if you want to dig deeper:
The Semantic Web: From Hypertext to Hyperdata
The Meaning and Future of the Semantic Web
How the WebOS Evolves
Web 3.0 Roundup
Gartner is Wrong About Web 3.0
Beyond Keyword (And Natural Language) Search
Enriching the Connections of the Web: Making the Web Smarter
Next Step for the Web
Doing for Data What HTML Did for Documents
I've been looking around for open-source libraries (preferably in Java, but not required) for extracting data and metadata from common file formats and Web formats. One project that looks very promising is Aperture. Do you know of any others that are ready or almost ready for prime-time use? Please let me know in the comments! Thanks.
Give me a tip!
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