1.5 Extraordinary Proof? 5
serve as proofs of CogPrime’s power for advanced AGI. We have used some CogPrime ideas in the OpenCog framework to do things like natural language understanding and data mining, and to control virtual dogs in online virtual worlds; and this has been very useful work in multiple senses. It has taught us more about the CogPrime design; it has produced some useful software systems; and it constitutes fractional work building toward a full OpenCog based implemen- tation of CogPrime. However, to date, the things OpenCogPrime has done are all things that could have been done in different ways without the CogPrime architecture (though perhaps not as elegantly nor with as much room for interesting expansion).
The bottom line is that building an AGT is a big job. Software companies like Microsoft spend dozens to hundreds of man-years building software products like word processors and operating systems, so it should be no surprise that creating a digital intelligence is also a relatively large- scale software engineering project. As time advances and software tools improve, the number of man-hours required to develop advanced AGI gradually decreases — but right now, as we write these words, it’s still a rather big job. In the OpenCogPrime project we are making a serious attempt to create a CogPrime based AGI using an open-source development methodology, with the open-source Linux operating system as one of our inspirations. But the open-source methodology doesn’t work magic either, and it remains a large project, currently at an early stage. I emphasize this point so that readers lacking software engineering expertise don’t take the currently fairly limited capabilities of OpenCogPrime as somehow a damning indictment of the potential of the CogPrime design. The design is one thing, the implementation another — and the OpenCogPrime implementation currently encompasses perhaps one third to one half of the key ideas in this book.
So we don’t have extraordinary proof to offer. What we aim to offer instead are clearly- constructed conceptual and technical arguments as to why we think the CogPrime design has dramatic AGI potential.
It is also possible to push back a bit on the common intuition that having a design for human- level AGI is such an “extraordinary claim.” It may be extraordinary relative to contemporary science and culture, but we have a strong feeling that the AGI problem is not difficult in the same ways that most people (including most AI researchers) think it is. We suspect that in hindsight, after human-level AGI has been achieved, people will look back in shock that it took humanity so long to come up with a workable AGI design. As you'll understand once you’ve finished Part 1 of the book, we don’t think general intelligence is nearly as “extraordinary” and mysterious as it’s commonly made out to be. Yes, building a thinking machine is hard — but humanity has done a lot of other hard things before. It may seem difficult to believe that human-level general intelligence could be achieved by something as simple as a collection of algorithms linked together in an appropriate way and used to control an agent. But we suggest that, once the first powerful AGI systems are produced, it will become apparent that engineering human-level minds is not so profoundly different from engineering other complex systems.
All in all, we’ll consider the book successful if a significant percentage of open-minded, appropriately-educated readers come away from it scratching their chins and pondering: “Hmm. You know, that just might work.” and a small percentage come away thinking "Now that’s an initiative I'd really like to help with!".
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