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Meta's Llama 4 Scout model supports a record-breaking 10 million token context window. While this is impressive for research use cases, production inference at this context depth requires significant GPU memory and specialized hardware.

Tell the model what NOT to do in addition to what you want. For example, 'Explain quantum computing without using analogies or metaphors.' Negative constraints often produce more focused and accurate outputs than positive instructions alone.

""Our current AI systems are not even close to having the common sense of a house cat.""

Ask the LLM to think about its thinking process: 'Before answering, consider what approach would be most effective for this problem and explain your reasoning strategy.'