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README.md

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 <li>Connect EvaDB to your SQL and vector database systems with the <a href="https://evadb.readthedocs.io/en/stable/source/reference/databases/postgres.html">`CREATE DATABASE`</a> and <a href="https://evadb.readthedocs.io/en/stable/source/reference/evaql/create.html#create-index">`CREATE INDEX`</a> statements.</li>
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 <li>Connect EvaDB to your SQL and vector database systems with the `CREATE DATABASE` and `CREATE INDEX` statements.</li>
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+<li>Connect EvaDB to your SQL and vector database systems with the <a href="https://evadb.readthedocs.io/en/stable/source/reference/databases/postgres.html">`CREATE DATABASE`</a> and <a href="https://evadb.readthedocs.io/en/stable/source/reference/evaql/create.html#create-index">`CREATE INDEX`</a> statements.</li>
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 <li>Write SQL queries with AI functions to get inference results:</li>
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    <li>Pick a pre-trained AI model from Hugging Face, Open AI, Ultralytics, PyTorch, and built-in AI frameworks for generative AI, NLP, and vision applications;</li>  
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 Follow the [getting started](https://evadb.readthedocs.io/en/stable/source/overview/getting-started.html) guide to get on-boarded as fast as possible.
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 * Get a transcript from a video stored in a table using a Speech Recognition model. Then, ask questions on the extracted transcript using ChatGPT.
 
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 * Store the text returned by a Speech Recognition model on the audio component of a video in a table. Run ChatGPT on the `text` column in a table.
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+* Get a transcript from a video stored in a table using a Speech Recognition model. Then, ask questions on the extracted transcript using ChatGPT.
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 ```sql
 CREATE TABLE text_summary AS
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 * Train a classic ML model for prediction using the <a href="https://ludwig.ai/latest/">Ludwig AI</a> engine.
 
 ```sql
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 EvaDB's AI-centric query optimizer takes a query as input and generates a query plan. The query engine takes the query plan and hits the relevant backends to efficiently process the query:
 1. SQL Database Systems (Structured Data)
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 2. AI Frameworks (Transform Unstructured Data to Structured Data; Unstructured data includes PDFs, text, images, etc. stored locally or on the cloud)
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 2. AI Frameworks (Transform Unstructured Data to Structured Data, Unstructured data includes PDFs, images, podcasts, etc. stored on cloud buckets or local filesystem)
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+2. AI Frameworks (Transform Unstructured Data to Structured Data; Unstructured data includes PDFs, text, images, etc. stored locally or on the cloud)
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 3. Vector Database Systems (Feature Embeddings)
 
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