Главная
Study mode:
on
1
Intro
2
Pinecone
3
History of NLP
4
Transformers
5
NLP
6
Screenshots
7
Problems with Large Language Models
8
Growth of Large Language Models
9
LangChain
10
LangChain Overview
11
Modular Components
12
Chains
13
Prompt Templates
14
Agents
15
Memory
16
Building with Language Models
17
Deep Dive
18
The Problem
19
Retrievable Augmentation
20
Indexing
21
Vector Database
22
LangChain Components
23
LangChain Variants
24
Process Overview
25
Training Models on Proprietary Data
26
Python Text Splitter
27
Embedding Tools
Description:
Explore the future of AI development in this comprehensive workshop featuring Harrison Chase, creator of LangChain, and James Briggs from Pinecone. Dive into the world of Large Language Models (LLMs), vector databases, and the LangChain library to understand how these tools are revolutionizing AI-powered applications. Learn about the history of NLP, transformers, and the challenges faced by large language models. Discover the key components of LangChain, including chains, prompt templates, agents, and memory. Gain insights into building with language models, focusing on retrievable augmentation, indexing, and vector databases. Explore practical applications through Python text splitters and embedding tools. Access accompanying slides and a notebook to enhance your learning experience and start creating cutting-edge AI applications.

Building the Future with LLMs, LangChain, & Pinecone

Pinecone
Add to list
0:00 / 0:00