Dirty Secrets of BookCorpus, a Key Dataset in Machine Learning | by Jack Bandy | Towards Data Science

AI/ML
Chatbots with RAG: LangChain Full Walkthrough
In this video, we work through building a chatbot using Retrieval Augmented Generation (RAG) from start to finish. We use OpenAI's gpt-3.5-turbo Large Language Model (LLM) as the "engine", we implement it with LangChain's ChatOpenAI class, use OpenAI's text-embedding-ada-002 for embedding, and the Pinecone vector database as our knowledge base.
📌 Code:
https://github.com/pinecone-io/examples/blob/master/learn/generation/langchain/rag-chatbot.ipynb
🌲 Subscribe for Latest Articles and Videos:
https://www.pinecone.io/newsletter-signup/
👋🏼 AI Consulting:
https://aurelio.ai
👾 Discord:
https://discord.gg/c5QtDB9RAP
Twitter: https://twitter.com/jamescalam
LinkedIn: https://www.linkedin.com/in/jamescalam/
00:00 Chatbots with RAG
00:59 RAG Pipeline
02:35 Hallucinations in LLMs
04:08 LangChain ChatOpenAI Chatbot
09:11 Reducing LLM Hallucinations
13:37 Adding Context to Prompts
17:47 Building the Vector Database
25:14 Adding RAG to Chatbot
28:52 Testing the RAG Chatbot
32:56 Important Notes when using RAG
#artificialintelligence #nlp #ai #langchain #openai #vectordb
GitHub - freedmand/textra: A command-line application to convert images, PDFs, and audio files to text using Apple's APIs
A command-line application to convert images, PDFs, and audio files to text using Apple's APIs - GitHub - freedmand/textra: A command-line application to convert images, PDFs, and audio fil...
A look at Apple’s new Transformer-powered predictive text model
I found some details about Apple’s new predictive text model, coming soon in iOS 17 and macOS Sonoma.
Centaurs and Cyborgs on the Jagged Frontier
turboderp/exllamav2: A fast inference library for running LLMs locally on modern consumer-class GPUs
llm-applications/notebooks/rag.ipynb at main · ray-project/llm-applications
A Comprehensive Guide for Building RAG-based LLM Applications
Onboard AI
Navigate unfamiliar codebases using AI. Step 1: Clone a GitHub repository Step 2: Ask questions to find your way around
Pivot to AI: Pay no attention to the man behind the curtain – Amy Castor
Machine Learning Mastery Series: Part 1 - Introduction to Machine Learning
Welcome to the Machine Learning Mastery Series, a comprehensive journey into the exciting world of machine learning. In this first installment, we’ll lay the foundation by exploring the fundamentals of machine learning, its types, and the essential concepts that underpin this transformative field.
What is Machine Learning? Machine learning is a subfield of artificial intelligence (AI) that focuses on developing algorithms and models that enable computers to learn from and make predictions or decisions based on data.
Fine-tune your own Llama 2 to replace GPT-3.5/4 | Hacker News
LLMs, Intuition, and Working With Computers - Jim Nielsen’s Blog
An AI capitalism primer
How to benchmark Llama2 Uncensored vs. GPT-3.5 on your own inputs | promptfoo
LLM Benchmarks
Why Nvidia’s AI Supremacy is Only Temporary « Pete Warden's blog
Advanced NLP with SpaCy | Hacker News
Buzzy AI Startup for Generating 3D Models Used Cheap Human Labor
Kaedim's founder was recently in a Forbes 30 Under 30 list for the company's 2D to 3D image conversion. In some cases artists produced the work wholecloth, one source said.
Perplexity: Interactive language modeling visualization
I built this little tool to help me understand what it's like to be an autoregressive language model. For any given passage of text, it augments the original text with highlights and annotations that tell me how
amaiya/onprem: A tool for running on-premises large language models with non-public data
AI now impacting the recruitment CV’s – RadOncNotes
Khoj: An Open-Source AI Copilot for your Second Brain
Teach your LLM to always answer with facts not fiction | MyScale | Blog
USA Today's publisher had to update all of the sports posts its AI reporter botched | Engadget
A week after "pausing" its AI high scool sports reporter, Gannett publishing has has had to recheck and update every post the machine had written..
SettingUpML | Macs in Chemistry
Apple M2 Studio Learns Nuke Machine Learning - fxguide
Seeking Advice on Optimal Computer Configuration for Machine/Deep Learning : r/nvidia
The build-a-deep-learning-machine from vineetk1 - Giter Club
Prebuilt vs Building your own Deep Learning Machine vs GPU Cloud (AWS) | BIZON Custom Workstation Computers, Servers. Best Workstation PCs and GPU servers for AI/ML, deep learning, HPC, video editing, 3D rendering, CAD.
Build a super fast deep learning machine for under $1,000 – O’Reilly