Over the past eight months, I have been developing a conversational symbolic AI architecture.
I believe symbolic AI architectures offer two major advantages worth exploring: computational efficiency and the ability to maintain thousands—or even millions—of lines of reasoning.
Now, imagine if we could extract structured information from the internet using non-neural methods to feed a symbolic model. I view the lack of exploration in this area as a significant gap; such AI models could potentially converse with the same fluency as today’s large models.
Computational intelligence: essentially, computational heuristics. Upon reflection, I realized that computational intelligence—in the context of reasoning—is simply the ability to employ computational heuristics. Try solving 3x² + 2x - 1 = 3 without using the quadratic formula. To do so, you would need to rule out various algebraic paths and instead use the “completing the square” method.
Right now, I’m trying to program my ideas; I’m not good at programming—just a beginner—and I’m open to talking with other developers.