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The datasets used to train frontier large language models are massive, often consisting of trillions of tokens. For example, the dataset for Llama 3 was over 15 trillion tokens, sourced from a vast collection of publicly available text and code from the internet.

Emergent abilities are phenomena where AI models suddenly demonstrate new, unpredictable skills once they reach a certain scale (i.e., more parameters and training data). These abilities are not explicitly programmed but emerge from the model's complexity, such as performing arithmetic or answering logic puzzles.

When building with AI, consider potential biases in training data, fairness of outcomes, transparency of decision-making, and the societal impact of your application.

If you plan to fine-tune an LLM, the quality of your training data is paramount. Even a small dataset of high-quality, relevant examples can be more effective than a large, noisy one.