Nvidia Is Moving Beyond LLMs to Superlearners, the Possible Precursor to AGI. What That Means for NVDA Stock.

Large language models (LLMs) have dominated much of the AI debate over the last few years. Scaling token prediction and LLM training were considered reliable metrics to measure progress, irrespective of the cost. This factor played right into the hands of Jensen Huang, who makes the best GPUs in the world, a fundamental requirement for training these AI models.

As intelligent as these systems were, they were still dumb in the sense that they had to be fed data in order to become better at predicting the next token. These static datasets could only make the AI so intelligent, giving rise to the need for superlearners: AI systems that continuously learn from experience rather than static datasets.