RAG vs. Fine Tuning

LLaMA3.2 has released a new set of compact models designed for on-device use cases, such as locally running assistants. Here, we show how LangGraph can enable these types of local assistant by building a multi-step RAG agent – this combines ideas from 3 advanced RAG papers (Adaptive RAG, Corrective RAG, and Self-RAG) into a single…

This is the 5th video in a series on using large language models (LLMs) in practice. Here, I discuss how to fine-tune an existing LLM for a particular use case and walk through a concrete example with Python code.

For more information about Stanford’s Artificial Intelligence programs visit: https://stanford.io/ai https://www.youtube.com/watch?v=Bl4Feh_Mjvo To follow along with the course, visit:https://cs229.stanford.edu/syllabus-s… Tengyu MaAssistant Professor of Computer Sciencehttps://ai.stanford.edu/~tengyuma/ Christopher RéAssociate Professor of Computer Sciencehttps://cs.stanford.edu/~chrismre/

How does AI learn? Is AI conscious & sentient? Can AI break encryption? How does GPT & image generation work? What’s a neural network? #ai #agi #qstar #singularity #gpt #imagegeneration #stablediffusion #humanoid #neuralnetworks #deeplearning

Dec 3, 2024One-day workshop on topics in Generative AI IISc-IBM AI Day is being jointly organized by the Centre for Networked Intelligence (with support from Cisco CSR) and IBM-IISc Hybrid Cloud Lab, in collaboration with IBM India Research Lab. The goal of this workshop would be to apprise the audience of Generative AI, a set…

Ready to launch your vector search game? 🚀 Ditch your traditional keywords and discover the power of vector search! This video will help you discover ways users can make search smarter, and generate creative text along the way. Get hands-on with vector search on Vertex AI! Jump directly to the topics you want to learn:00:00…