Add video link on how LLMs work (#9287)

* Add video link on how LLMs work

Added a video link explaining how large language models work.

* Update src/data/roadmaps/prompt-engineering/content/llms-and-how-they-work@74JxgfJ_1qmVNZ_QRp9Ne.md

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

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Co-authored-by: Javier Canales <56018501+jcanalesluna@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

src/data/roadmaps/prompt-engineering/content/llms-and-how-they-work@74JxgfJ_1qmVNZ_QRp9Ne.md

@@ -1,3 +1,5 @@
 # LLMs and How They Work
 
-LLMs function as sophisticated prediction engines that process text sequentially, predicting the next token based on relationships between previous tokens and patterns from training data. They don't predict single tokens directly but generate probability distributions over possible next tokens, which are then sampled using parameters like temperature and top-K. The model repeatedly adds predicted tokens to the sequence, building responses iteratively. This token-by-token prediction process, combined with massive training datasets, enables LLMs to generate coherent, contextually relevant text across diverse applications and domains.
+LLMs function as sophisticated prediction engines that process text sequentially, predicting the next token based on relationships between previous tokens and patterns from training data. They don't predict single tokens directly but generate probability distributions over possible next tokens, which are then sampled using parameters like temperature and top-K. The model repeatedly adds predicted tokens to the sequence, building responses iteratively. This token-by-token prediction process, combined with massive training datasets, enables LLMs to generate coherent, contextually relevant text across diverse applications and domains.
+
+- [@video@How Large Language Models Work](https://youtu.be/5sLYAQS9sWQ)