But what is this system, that is supposedly as smart as a 4 year old? It’s a program that answers vocabulary and similarity questions as well as a human 4 year old, drawing on MIT’s ConceptNet database.
Whoopie! My calculator can answer arithmetic questions better than I can — does that make it a superintelligence? ;-D ….
A toddler is far more than a question-answering program back-ended on a fixed database, obviously….
This Illinois/MIT program is basically like IBM Watson, but for a different set of knowledge…
ConceptNet is an intriguing resource, and one of the programmers in our Addis Ababa OpenCog lab is currently playing with importing it into OpenCog….
But obviously, this Illinois/MIT software lacks the ability to learn new skills, to play, to experiment, to build, to improvise, to discover, to generalize beyond its experience, etc….. It has basically none of the capabilities of the mind of a 4 year old child.
BUT… one thing is clear … these universities do have excellent PR departments!
The contrast between their system — a question-answering system based on MIT’s ConceptNet knowledge base — and the system OpenCog, Hanson and I are building is both dramatic and instructive.
What we are after with our project is not just a system that passes certain tests as well as a human toddler. We are after a system that can understand and explore the world, and make sense of itself and its surroundings and its goals and desires and feelings and worries, in the rough manner of a human toddler. This is a wholly different thing.
The kind of holistic toddler-like intelligence we’re after, would naturally serve as a platform for building greater and greater levels of general intelligence — moving toward adult-level AGI….
But a question-answering system based on ConceptNet doesn’t particularly build toward anything — it doesn’t learn and grow. It just replies based on the data in its database.
It is unfortunate, but not terribly surprising, that this kind of distinction still needs to be repeated over and over again. General intelligence – the ability to achieve a variety of complex goals in a variety of complex environments, including goals and environments not foreseen in advance by the creators of the intelligent system — is a whole different kettle of fish than engineering a specialized intelligent system for a specific purpose.
The longer I work on AGI, the more convinced I am that an embodied approach will be the best way to fully solve the common sense problem. The AI needs to learn common sense by learning to control a robot that does commonsensical things…. Then the ability to draw analogies and understand words will emerge from the AI’s ability to understand the world and relate different experiences it has had. Whereas, a system that answers questions based on ConceptNet is just manipulating symbols without understanding their meaning, an approach that will never lead to real human-like general intelligence.
The good news is, my OpenCog colleagues and I know how to make a robot that will achieve first toddler-level commonsense knowledge, and then full-scale human-adult level AGI. And then what?
The less exciting news is, it’s going to take a lot of work — though exactly how many years depends on how well funded our project is.
Next Big Future just ran an extensive interview with me on these topics, check it out if you’re curious for more information…
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