3 min read

In a paper, published last week, a member from the US Air Force talks about a model for artificial general intelligence (AGI). The author of the paper, A Model for General Intelligence, is Paul Yaworsky, Information Directorate of the US Air Force Research Laboratory. There have been many efforts in the past to model intelligence in machines, but with little progress in terms of real cognitive intelligence like those of humans.

What is artificial general intelligence?

Currently, the way AI systems work is not understood completely. Also, AI systems are good at performing narrow tasks but not complex cognitive problems. Artificial general intelligence aims to covers the gap between lower level and higher level work in AI—to try and make sense of the abstract general nature of intelligence. Three basic aspects of artificial intelligence need to be understood to bridge this gap.

  1. To realize the general order and the nature of intelligence at a high level.
  2. Understand what these realizations mean with respect to the overall intelligence process.
  3. Describe these realizations as clearly as possible.

The paper proposes a hierarchical model to help capture and exploit the order within intelligence. The underlying order contains patterns of signals that become organized, stored and then activated in space and time.

The hierarchical model

The paper portrays intelligence as an orderly, organized process using a simple hierarchy as shown:


Source: A Model for General Intelligence

The real world has order and organization. The human brain understands this and forms an internal model based on that understanding. This model enables learning, which further gives way to decision making, movement, and communication. The flow of input signals and learning within the shown model is bottom-up which is in contrast to the top-down of learned signal representations.

The paper says that external order and organization can be modeled internally in the brain in the form of various hierarchies. The hierarchies discussed are temporal, spatial, and general.

Impact and concerns

When computers continue to improve and cooperation increases between humans and computers, people themselves will become more productive in information processing. A point to remember as the paper states is that computers work for humans.

Yaworsky also talks about concerns with AI and it taking over the world. Problems like those are heard today due to sketchy predictions involving intelligence he says. It is difficult to make good scientific predictions in itself but when the predictions have to be done in intelligence it is almost impossible to get them right.

This is because a proper understanding of intelligence itself is not good enough to be able to make accurate predictions.

Do you buy this explanation or fear the US Air Force working on killer drones that may one day go rampant like in Terminator 2?!

Either way, the conclusion is that intelligence involves multiple levels of abstraction. Human intelligence has high processing levels—abstract, general, etc. Majority of the work done in AI currently is at lower levels of abstraction. There is a lot needed for the current AI to become real AI. A high-level hierarchical model for artificial intelligence as explored in the paper addresses this.

For more details, you can read the research paper.

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