fix: typos

learning ai.md

@@ -2,12 +2,12 @@ AI has been a huge word lately; let me try and figure out what it is.
 
 If you see anything wrong (not incomplete, but actually wrong), let me know :).
 ## Large language model (LLM)
-LLM models are tensor networks that get 'activated' with an activation matrix, resulting in an output matrix.
+LLM models are tensor networks that an activation matrix activates, resulting in an output matrix.
 
 There are multiple layers of matrices in most models.
 
-The "open models" available online are still largely closed-source; the matrices are basically binary blocs that describe weights given to each tensor.
+The \"open models\" available online are still largely closed-source; the matrices are basically binary blocks that describe the weights the model assigns to each tensor.
 ## Retrieval-augment generative AI (RAG)
 Basically, before sending the prompt to the LLM, the client does a search to find additional context. There are lots of tools for doing this, but the most popular seem to be from the AI community, and work by converting the user input to a 'vector' of NLP tokens, using a specialized 'vector database' to find other 'chunks' of related inputs, then add those to the message before sending it to the LLM
 ## Tool calling
-A super powerful capability, from what I can tell, it is generally implemented by telling the LLM how to structure its output to make tool calls, then attempting to parse the LLMs output to detect tool calls, run the tools, and append the result to the message going into the LLM.
+A super powerful capability, from what I can tell, developers generally implement this by telling the LLM how to structure its output to make tool calls, then attempting to parse the LLMs output to detect tool calls, run the tools, and append the result to the message going into the LLM.