AGI: The Coming AGI Wars: Players and Positioning

AGI (artificial general intelligence) is getting closer to near-term reality. We examine three classes of potential players: those based on LLMs (large language models), using transformer-based architectures, typically with reinforcement learning with human feedback (RLHF) to refine capabilities, Yann LeCun's reinforcement learning-based approach (being developed by Meta), and Karl Friston's notion of active inference (being developed by Verses.ai). We show how CORTECONs (COntent-Retentive, TEmporally-CONnected neural networks) can play a role, both as a model within active inference (where the model itself can come to a free energy minimum), as well as a means to connect signal-to-symbolic processing in LLM (signal-based) AIs. We identify funding for the major players, both in terms of recent investments as well as market caps.


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