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A very good read from a respected source!

Google DeepMind. Levels of AGI: Operationalizing Progress on the Path to AGI. 04 NOV.

Meredith Ringel Morris1, Jascha Sohl-dickstein1, Noah Fiedel1, Tris Warkentin1, Allan Dafoe1, Aleksandra Faust1, Clement Farabet1 and Shane Legg1 1Google DeepMind

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.

Keywords: AI, AGI, Artificial General Intelligence, General AI, Human-Level AI, HLAI, ASI, frontier models, benchmarking, metrics, AI safety, AI risk, autonomous systems, Human-AI Interaction

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Defining AGI: Six Principles

Reflecting on these nine example formulations of AGI (or AGI-adjacent concepts), we identify properties and commonalities that we feel contribute to a clear, operationalizable definition of AGI. We argue that any definition of AGI should meet the following six criteria:

  1. Focus on Capabilities, not Processes.
  2. Focus on Generality and Performance.
  3. Focus on Cognitive and Metacognitive Tasks. 
  4. Focus on Potential, not Deployment. 
  5. Focus on Ecological Validity. 
  6. Focus on the Path to AGI, not a Single Endpoint.

FOR EDUCATIONAL AND KNOWLEDGE SHARING PURPOSES ONLY. NOT-FOR-PROFIT. SEE COPYRIGHT DISCLAIMER.