ONLINE CAPSTONE PROJECT (CS_467_400_W2024)

Blog Post #3 – Feb 26, 2024

My biggest success during the course is that I learned how to import JSON files for reading and starting up an instance of Weaviate for vectorizing and embedding of the JSON files with OpenAI API. And, I created the schema that house our data and wrote a query to extract the vector for questions. And currently, I just started working on searching for relevant answers using vector search to match founders and founders. Those I learned really matter since it is very important these days to know how we can use the OpenAI embeddings API to easily create vectors and perform vector search on text data using Weaviate an open-source vector database for our new jobs. Also, when we’re talking about vectors in the context of AI these days with ChatGPT and generative AI, they are used to represent unstructured data such as images or text. Now, I understood basic of how we can use vectors for ML tasks such as classification which is awesome result from this class.

Blog Post #2 – Feb 5, 2024

The favorite technology from my project is Open AI and Weaviate. Why? because those provide vector databases which are to provide fast and accurate similarity search or nearest neighbor search capabilities. The integration of AI techniques in vector databases enhances their capabilities, improves search accuracy, optimizes performance, and enables more intelligent and efficient management of high-dimensional data. I am really interested in this foundational technology — which is already being used in industries like ecommerce, social media, and more. I am learning lots of things from foundational concepts around AI-first vector databases to hands-on coding labs for question answering using LLMs.