Why Search Your Data When You Can Ask It? Vector Databases and Embeddings to Level Up Your Corpus.

AemonAlgiz · Intermediate ·🧠 Large Language Models ·3y ago

About this lesson

GitHub repo: https://github.com/pashpashpash/vault-ai In today's video, we're exploring how to leverage your content and search with large language models like Ada and GPT-4! We're moving beyond traditional keyword searches and diving into natural question-asking to enhance your search experience. We'll be using the Pinecone database and Ada embeddings to empower our content for search, and demonstrate how easy it is to set up a powerful search engine for your corpus. By working with the PubMed public dataset, you'll see how quickly you can generate relevant results and contextual answers. Discover the advantages of large language models for research and how they can help you stay current in rapidly evolving fields. Say goodbye to updating control vocabularies and hello to more efficient searching! Don't forget to like, subscribe, and stay tuned for our next video tomorrow, where we'll discuss fine-tuning your large language model, including Vicuna, LLaMa, and OpenAI! #LargeLanguageModels #Ada #GPT4 #ContentSearch #NLP

Original Description

GitHub repo: https://github.com/pashpashpash/vault-ai In today's video, we're exploring how to leverage your content and search with large language models like Ada and GPT-4! We're moving beyond traditional keyword searches and diving into natural question-asking to enhance your search experience. We'll be using the Pinecone database and Ada embeddings to empower our content for search, and demonstrate how easy it is to set up a powerful search engine for your corpus. By working with the PubMed public dataset, you'll see how quickly you can generate relevant results and contextual answers. Discover the advantages of large language models for research and how they can help you stay current in rapidly evolving fields. Say goodbye to updating control vocabularies and hello to more efficient searching! Don't forget to like, subscribe, and stay tuned for our next video tomorrow, where we'll discuss fine-tuning your large language model, including Vicuna, LLaMa, and OpenAI! #LargeLanguageModels #Ada #GPT4 #ContentSearch #NLP
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
Changes to LLM pricing: Novita and StreamLake
Learn about the pricing changes for Novita and StreamLake LLMs and how they impact your projects
Dev.to AI
 📰
The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix
Enterprises face an AI context gap, where retrieval-augmented generation lacks trust due to missing or inconsistent context, and a governed semantic layer is needed to fix this issue
VentureBeat AI
 📰
The LLM Was the Easy Part: Building a Hybrid RAG API
Learn to build a hybrid RAG API by combining LLMs with retrieval mechanisms for more accurate and informative responses
Dev.to · Abu Hurayra Niloy
 📰
NVIDIA NeMo Guardrails: Building Safer, More Controllable LLM Applications
Learn to build safer LLM applications with NVIDIA NeMo Guardrails, a framework for adding programmable safety features to your apps
Medium · LLM
Up next
5 Levels of AI Agents - From Simple LLM Calls to Multi-Agent Systems
Dave Ebbelaar (LLM Eng)
Watch →