Baby AGI and Developmental Cognitive Science

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The only planet we live on - the Earth - is vulnerable to cosmic events (near-earth objects? near-earth supernova?) which can, quite literally, freeze or fry human life. This calls for a need to colonize beyond Earth, and research and development into space exploration and habitation.

But there is another parallel direction for research. Our biological bodies are ill-suited for living beyond Earth, especially for interplanetary travel. But while artificial limbs are important elements for overcoming our biology bodies, there is yet another component that is as crucial if not more… our minds. I'm interested in the creation of an artificial mind.

A separate motivation for this also stems from mere curiosity. Sitting behind those darting eyes lies one of the most mysterious systems in the universe – 100 billion neurons, each connected to almost 10 thousand others – all made of the same carbon we obtain when we burn sugar on a stove. How can something as nonliving as a piece of rock be made of the same basic elements that make up something as lively as you or me? Perhaps, along with the mysteries of the cosmos, mysteries of our minds will continue to be amongst the longest unsolved puzzles of humankind.

Of course, once Artificial General Intelligence is attained, speculation has it that it will soon explode into a singularity, for better or worse. Hopefully, it proves helpful in finding solutions to cancer, physics, inequity, and sustainable progress, amongst other things. (Or, maybe, the Covid19 pandemic taught us some form of equity already?)

But where does one begin taking a crack at AGI? Maybe one way is to look inward at the only example we have of sufficiently general intelligence – ourselves. But clearly, no direct intervention puts our minds into their adult forms. Plus, studying the adult mind is like studying the artifacts left behind by the sociocultural environment the individual grew up in. Doesn't seem like a great way to understand where nature ended and nurture began.

At the AGI 2021 conference, I was pleasantly surprised to be affirmed by this primitive conclusion. Bootstrapping was an important theme throughout the conference: We should not aim to create Artificial General Intelligence. We should aim at creating a (minimal) system that could give rise to Artificial General Intelligence. One may argue that this itself is sufficiently general intelligence.

Clearly, such a system already exists: the human child. If the reader is a younger me, pondering over what intelligence is, how our brain-minds do what they do, then know that Childhood Cognitive Development and Bootstrapping could be a valuable perspective to consider. I was pleased to hear that Michael Tomasello, one of the leading figures in First Language Acquisition, also pointed towards studying Phylogeny and Ontogeny to understand human cognition better in his Rumelhart Prize Presentation at the CogSci 2022 Conference.

Learning Resources

Following are some resources that may be useful for starting out with Artificial General Intelligence.

The AGI Conferences are listed here, with AGI 2021 available here and its schedule here. The proceedings are also available for reading and viewing! Many excellent resources for self-education in AGI and prerequisites have been collected here. In terms of keywords, "bootstrapping agi" might yield more relevant results than "bootstrapping" alone.

When it comes to childhood cognition, Wiley-Blackwell's Handbook of Childhood Cognitive Development can be a good place to start. However, while there have been calls for Unified Theories of Cognition since the 1990s, I am yet to come across a call for a Unified Theory of Developmental Cognition. There has been significant progress in mainstream AI over the last 30 years which can be used for such a unified theory. Still, certain important elements remain: particular ones, I am interested in include (i) discovering causal models from high dimensional data (ii) augmenting machine learning via shared attention and theory of mind.

All is not well in the field of AGI either. In particular, as this paper points out, most AGI research leans towards being Proof of Concept rather than digging deeper. Good AGI research is relatively rare. Pei Wang's Non-Axiomatic Reasoning System is an research direction I have found promising.

Pei Wang has put together an excellent AGI curriculum. Here is an alternative suggestion based on my experiences so far:

  • School Education (expected 2 dedicated years):
    • Prerequisites: English, understanding of a 10/14 year old
  • Computer Science (expected 2 dedicated years): teachyourselfcs.com
    • Prerequisites: English, Mathematics from the above resource, understanding of a 16/18 year old

Something more directly relevant to the discussions above includes:

Other readings:

  • all of Pylyshyn's writings
  • all of Dreyfus' writings
  • all of Pei Wang's writings
  • all of Judea Pearl's writings

*When I say "dedicated", it assumes you will be working full-time on the topic.

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