The Road to Autonomous Intelligence with Andrej Karpathy
No Priors: Artificial Intelligence | Technology | Startups
Training on Reasoning Trajectories
Current advancements in large language models (LLMs) rely on the refactoring of internet data to capture the intricate thought processes akin to human problem-solving. Internet data, while abundant, does not provide the depth of insight needed for optimal performance; instead, it serves as a valuable resource due to its embedded reasoning traces and knowledge. The true potential for achieving artificial general intelligence (AGI) lies in accessing extensive inner thought trajectories akin to human cognition. By focusing on transforming datasets into formats that reflect this inner monologue, significant progress toward AGI can be realized.
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