xcvvxcfgsdfg How does the process of creating word embeddings in Excel, as demonstrated in the excerpt, compare to the methods used by large language models developed by companies like Google? What are the limitations and potential inaccuracies introduced by using Excel for natural language processing tasks, and how might these limitations affect the results? Considering the complexity of sentence transformers and attention mechanisms, what are the key simplifications and trade-offs made in this Excel-based implementation, and how do these affect the model's performance and applicability? And but since it's live, you'll see me making mistakes throughout and uh, so and then is just then, uh, to all can learn from my mistake as well. All right, so the first step i'd like to be able to do is to, to tell you what embedding means.