I built an app for question-answering over the full history of Lex Fridman podcasts. It uses Whisper for audio-to-text followed by Langchain for dataset processing and embedding. It uses Pinecone to store embeddings and Langchain vectorDB search to find relevant podcast clips given a user question. It uses UI elements inspired by Mckay Wrigley’s work. Code is here. (View Highlight)
I built an app for question-answering over the full history of Lex Fridman podcasts. It uses Whisper for audio-to-text followed by Langchain for dataset processing and embedding. It uses Pinecone to store embeddings and Langchain vectorDB search to find relevant podcast clips given a user question. It uses UI elements inspired by Mckay Wrigley’s work. Code is here. (View Highlight)
I built an app for question-answering over the full history of Lex Fridman podcasts. It uses Whisper for audio-to-text followed by Langchain for dataset processing and embedding. It uses Pinecone to store embeddings and Langchain vectorDB search to find relevant podcast clips given a user question. It uses UI elements inspired by Mckay Wrigley’s work. Code is here. (View Highlight)
I built an app for question-answering over the full history of Lex Fridman podcasts. It uses Whisper for audio-to-text followed by Langchain for dataset processing and embedding. It uses Pinecone to store embeddings and Langchain vectorDB search to find relevant podcast clips given a user question. It uses UI elements inspired by Mckay Wrigley’s work. Code is here. (View Highlight)
built an app for question-answering over the full history of Lex Fridman podcasts. It uses Whisper for audio-to-text followed by Langchain for dataset processing and embedding. It uses Pinecone to store embeddings and Langchain vectorDB search to find relevant podcast clips given a user question. It uses UI elements inspired by Mckay Wrigley’s work. Code is here. (View Highlight)
built an app for question-answering over the full history of Lex Fridman podcasts. It uses Whisper for audio-to-text followed by Langchain for dataset processing and embedding. It uses Pinecone to store embeddings and Langchain vectorDB search to find relevant podcast clips given a user question. It uses UI elements inspired by Mckay Wrigley’s work. Code is her (View Highlight)
built an app for question-answering over the full history of Lex Fridman podcasts. It uses Whisper for audio-to-text followed by Langchai (View Highlight)
Split size has a strong influence on performance. To quantify this, I take the Karpathy podcast episode and use Langchain QAGenerationChain to generate an eval set. (View Highlight)
Split size has a strong influence on performance. To quantify this, I take the Karpathy podcast episode and use Langchain QAGenerationChain to generate an eval set. (View Highlight)
Split size has a strong influence on performance. To quantify this, I take the Karpathy podcast episode and use Langchain QAGenerationChain to generate an eval set. (View Highlight)
