systems that know and understand and think and learn
Deep learning can produce some impressive chatbots, but they are hardly intelligent. In fact, they are precisely ignorant in that they do not think or know anything.
More intelligent dialog with an artificially intelligent agent involves both knowledge and thinking. In this article, we educate an intelligent agent that reasons to answer questions.
Going on 5 years ago, I wrote part 1. Now, finally, it’s time for the rest of the story.
Continue reading “Confessions of a production rule vendor (part 2)”
Orin Etzioni is a marvelous choice to lead the Allen Institute for AI (aka AI2). The NL/ML path is the right path for scaling up the deep knowledge that Paul Allen’s vision of a Digital Aristotle requires. You can read more about it below and here’s more background on the change in the direction and on some evidence that the path holds great promise.
As I discussed in Over $100m in 12 months backs natural language for the semantic web, Radar Networks’ Twine is one of the more interesting semantic web startups. Their founder, Nova Spivak, is funded by Vulcan and others to provide “interest-driven [social] networking”. I’ve been participating in the beta program at modest bandwidth for a while. Generally, Nova’s statements about where they are and where they are going are fully supported by what I have experienced. There are obvious weaknesses that they are improving. Overall, the strategy of gradually bootstrapping functionality and content by controlling the ramp up in users from a clearly alpha stage implementation to what is still not quite beta (in my view) seems perfect.
Recently, Nova recorded a few minute video in which he makes three short-term predictions: Continue reading “The Semantic Arms Race: Facebook vs. Google”