Going on 5 years ago, I wrote part 1. Now, finally, it’s time for the rest of the story.
Deep natural language understanding (NLU) is different than deep learning, as is deep reasoning. Deep learning facilities deep NLP and will facilitate deeper reasoning, but it’s deep NLP for knowledge acquisition and question answering that seems most critical for general AI. If that’s the case, we might call such general AI, “natural intelligence”.
Deep learning on its own delivers only the most shallow reasoning and embarrasses itself due to its lack of “common sense” (or any knowledge at all, for that matter!). DARPA, the Allen Institute, and deep learning experts have come to their senses about the limits of deep learning with regard to general AI.
General artificial intelligence requires all of it: deep natural language understanding, deep learning, and deep reasoning. The deep aspects are critical but no more so than knowledge (including “common sense”). Continue reading “Natural Intelligence”
A decade or so ago, we were debating how to educate Paul Allen’s artificial intelligence in a meeting at Vulcan headquarters in Seattle with researchers from IBM, Cycorp, SRI, and other places.
We were talking about how to “engineer knowledge” from textbooks into formal systems like Cyc or Vulcan’s SILK inference engine (which we were developing at the time). Although some progress had been made in prior years, the onus of acquiring knowledge using SRI’s Aura remained too high and the reasoning capabilities that resulted from Aura, which targeted University of Texas’ Knowledge Machine, were too limited to achieve Paul’s objective of a Digital Aristotle. Unfortunately, this failure ultimately led to the end of Project Halo and the beginning of the Aristo project under Oren Etzioni’s leadership at the Allen Institute for Artificial Intelligence.
At that meeting, I brought up the idea of simply translating English into logic, as my former product called “Authorete” did. (We renamed it before Haley Systems was acquired by Oracle, prior to the meeting.)
It’s a bit too far towards the singularity/general AI end of the spectrum for me, but nicely done and fun for many not in the field, perhaps:
Enterra is an interesting company,too, FYI. They are in cognitive computing with a bunch of people formerly of Inference Corporation where I was Chief Scientist. Doug Lenat of Cycorp was one of our scientific advisors. Interestingly enough, Enterra uses Cyc!