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performance drops in the middle, use selective retrieval, repeat the heading, or add a short
navigational summary, rather than uploading a larger document with no plan.

Heavy summarizing has a cost. When a system turns ten pages into ten bullet points, it may
drop the exceptions, the negations, and the footnotes. You should therefore state what may

not be removed, such as conditions, figures, dates, and differences between versions. In
research or regulation, keep the original text as the source, and do not let the summary
become the only layer of truth.

✕ Common misconception Correction

A large context window means a perfect Sending everything may increase noise and

memory and equal understanding of every cost and make verification harder. Choose
line. the context; do not merely accumulate it.

● Remember: Section summary

• Key idea: Variation is the product of probabilistic generation, a multi-layered system,
and a changing context.
• Practical decision: Record the settings, repeat the test, and organize the context.
• Mistake to avoid: Reading every difference as direct evidence that one model is more
intelligent.

Video: [1hr Talk] Intro to Large Language

Models
A general explanation of next-token

prediction, training, and the move from a
language model to an assistant, together with
the limits of the approach.

Duration: about 60 minutes | Level: Beginner
to Intermediate
Learning objective: Build an integrated mental

picture of how a language model is built and
behaves.
Source: Andrej Karpathy [23].

https://www.youtube.com/watch?v=zjkBMFh
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Verified: June 6, 2026

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