fix broken references in docs

website/docs/genai/llm.md

@@ -10,7 +10,7 @@ import GPT1 from './llm-gpt-1.png';
 
 ## Embeddings
 
-An Autoencoder is a type of [DNN](intro-ai#) that does not require classification labels but rather, performs unsupervised learning by asking the DNN to classify the the inputs of the network as the outputs. For example, when classifying the image of a cat, the pixels of that cat would be the input and the classificatio label would also be all the pixels of the cat.
+An Autoencoder is a type of [DNN](dnn.md) that does not require classification labels but rather, performs unsupervised learning by asking the DNN to classify the the inputs of the network as the outputs. For example, when classifying the image of a cat, the pixels of that cat would be the input and the classificatio label would also be all the pixels of the cat.
 
 <center><a href="https://towardsdatascience.com/applied-deep-learning-part-3-autoencoders-1c083af4d798"><img src={Autoencoder} style={{width: 500}} /></a></center>
 

website/docs/intro.md

@@ -4,17 +4,17 @@ sidebar_position: 1
 
 # Intro
 
-**What is Hal9?** Hal9 is a Python library to help you write your own versions of ChatGPT -- We reffer to those applications as Generative Apps since they use GenAI.
+**What is Hal9?** Hal9 is a Python library to help you write your own versions of ChatGPT -- We refer to those applications as Generative Apps since they use GenAI.
 
 ### Generative AI
 
 Generative Artificial Intelligence (**GenAI**), a version of Artificial Intelligence (**AI**) that is good at generating content: text, images, sounds, videos, code, etc.
 
-The previous version of GenAI, reffered to as AI, was based on Deep Neural Networks (**DNN**), which are brain-inspired math equations optimized useful for content classificaiton. For example, it enabled computers to identify if pixels in an image represent a cat, or understand if text is written in Spanish.
+The previous version of GenAI, refered to as AI, was based on Deep Neural Networks (**DNN**), which are brain-inspired math equations optimized useful for content classificaiton. For example, it enabled computers to identify if pixels in an image represent a cat, or understand if text is written in Spanish.
 
 GenAI uses AI in the opposite way -- not to classify, but to generate content on its own. For example, generate pixels for a cat image, or generate text in Spanish.
 
-Read next the [Intro to AI](genai/intro-ai) section to learn the foundations that lead us to Generative AI.
+Head next to the [Deep Neural Networks](genai/dnn) section to learn the foundations that lead us to Generative AI.
 
 ### Generative Apps