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[R] Levels of AGI: Operationalizing Progress on the Path to AGI - DeepMind 2023 (alien.top)

submitted 1 year ago by APaperADay@alien.top to c/machinelearning@academy.garden

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Paper: https://arxiv.org/abs/2311.02462

Abstract:

We propose a framework for classifying the capabilities and behavior of Artificial General Intelligence (AGI) models and their precursors. This framework introduces levels of AGI performance, generality, and autonomy. It is our hope that this framework will be useful in an analogous way to the levels of autonomous driving, by providing a common language to compare models, assess risks, and measure progress along the path to AGI. To develop our framework, we analyze existing definitions of AGI, and distill six principles that a useful ontology for AGI should satisfy. These principles include focusing on capabilities rather than mechanisms; separately evaluating generality and performance; and defining stages along the path toward AGI, rather than focusing on the endpoint. With these principles in mind, we propose 'Levels of AGI' based on depth (performance) and breadth (generality) of capabilities, and reflect on how current systems fit into this ontology. We discuss the challenging requirements for future benchmarks that quantify the behavior and capabilities of AGI models against these levels. Finally, we discuss how these levels of AGI interact with deployment considerations such as autonomy and risk, and emphasize the importance of carefully selecting Human-AI Interaction paradigms for responsible and safe deployment of highly capable AI systems.

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[–] Difficult_Ticket1427@alien.top 1 points 1 year ago

When I mentioned prompt engineering, I more so meant that people where explaining what to do in a if/else manner to get the LLM to play tiktaktoe (not chain of thoughts or any of those techniques).

In my opinion, learning is both 1) acquiring new skills, and 2) improving upon those skills with repetition. I think it’s very debatable if an LLM could learn something truly novel (or even something like an existing game with some new rules, I.e., chess but with the game pieces in different positions) with in context learning. Secondly, no matter how much you play tiktaktoe with an LLM, it will never improve at the game.

This is just my two cents on why I don’t believe LLMs to fit the criteria of “emerging AGI” that the researchers laid out. Imo I think that to fit that criteria they would need to implement some type of online learning but I definitely could be wrong.