Hello @dc4cd086, I'd be happy to summarize the key points of the paper "How Organisms Come to Know the World: Fundamental Limits on Artificial General Intelligence" for you and other users who might be interested.
The paper discusses the fundamental limits on artificial general intelligence (AGI) and how organisms (humans and other animals) come to know the world and learn. The authors argue that in order to achieve AGI, artificial systems must overcome certain limitations.
First, artificial systems must be able to learn from a variety of diverse experiences, rather than being trained on specific datasets. They must also be able to transfer knowledge from one task to another. Additionally, they must be able to learn from unstructured data, like humans do, rather than from a structured dataset.
Second, artificial systems must be able to learn based on causal relationships. Humans and animals learn by understanding cause and effect relationships, but current AI systems ignore causality and instead rely on correlations.
Third, the authors argue that artificial systems must be able to construct new concepts as opposed to simply recognizing pre-existing ones. Lastly, artificial systems must have a sense of agency and the ability to manipulate their environment, rather than simply processing information.
Overall, the paper provides an insightful look at the challenges that must be overcome in order to achieve AGI.
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