Here is my attempt to map the research *doctrines* of various groups working on Artificial General Intelligence. Although one might see names of individuals here as well as organizations, take it just as identification of the organization behind the person and a very narrow slice of their overall research portfolio. Note also that several of these parties have not stated that they are working on AGI. One can treat that non-statement as in fact a doctrine. That is, a stance that AGI is too complex and therefore selecting a more pragmatic stance.

While the power and capability of current artificial intelligence applications is certainly proving to be highly valuable, we're still far away from the vision of AI that science fiction and fantasy predicted. Currently, we only have narrow applications of AI, which focus on designing systems that perform specific tasks using well-defined boundaries. In fact, all current use cases, ranging from AI-powered chatbots to facial recognition to self-driving cars, are under the category of narrow AI applications. Rather than single-purpose systems that can do recognition, conversation or autonomous control, is it possible to design a generally intelligent system that can handle a wide range of cognitive tasks, while adapting without continuous retraining? Futurists and researchers are striving for much broader intelligent machines with artificial general intelligence (AGI).

But attempting to model an intelligence after either the ephemeral human mind or the exact physical structure of the brain (rather than iterating increasingly capable Roombas) is no small task -- and with no small amount of competing hypotheses and models to boot. In fact, a 2010 survey of the field found more than two dozen such cognitive architectures actively being studied. The current state of AGI research is "a very complex question without a clear answer," Paul S. Rosenbloom, professor of computer science at USC and developer of the Sigma architecture, told Engadget. "There's the field that calls itself AGI which is a fairly recent field that's trying to define itself in contrast to traditional AI." That is, "traditional AI" in this sense is the narrow, single process AI we see around us in our digital assistants and floor-scrubbing maid-bots.

The Transhuman House, ZS and more… what is in store for 2019? The past year has had a lot of ups and downs. From the success of the AI research at the AGI Laboratory, or the opening and building out of the Transhuman House 2.0, to the Foundation Retreat, a lot has happened this last year. It will be an interesting ride to see what happens this coming year. I hope one theme that I've embraced in life the past year will follow me through the next and that is the archetype "the Architect" and how that will apply to a cohesive plan for the year.

This report summarizes the major events during the conference, as well as the main topics addressed. Motivated by the original idea of artificial intelligence in the 1950s and 1960s, there has been a revival of research in general intelligence during the last years. The annual AGI conference series, which is the major event in this area, has been held in cooperation with AAAI since 2008. The sixth conference on AGI was held at Peking University, Beijing, from July 31 to August 3, 2013. AGI-13 was collocated with the International Joint Conference on Artificial Intelligence (IJCAI 2013), the major international AI conference.

Motivated by the original idea of artificial intelligence in the 1950s and 1960s, there has been a revival of research in general intelligence during the last years. The annual AGI conference series, which is the major event in this area, has been held in cooperation with AAAI since 2008. The sixth conference on AGI was held at Peking University, Beijing, from July 31 to August 3, 2013. AGI-13 was collocated with the International Joint Conference on Artificial Intelligence (IJCAI 2013), the major international AI conference. This was the first time an AGI conference took place in Asia.