Resources From X/Twitter Audio Space on LLMs & AI - 2025-02-02
Curated Links & Insights from the X/Twitter Space on LLMs, RAG, and AI Tools
Table of Contents
This blogpost was published on my X/Twitter account on February 2nd, 2025 .
Here are the resources that were shared and discussed during the Space on February 2nd, 2025. I’ve also included a few additional resources that I believe will enhance the collection. Space recording (in Arabic) can be found here.
Educational Resources
AI, ML, and Neural Networks Visualization
- @3eid10 shared a great YouTube channel
- Transformers (how LLMs work) explained visually by 3Blue1Brown: Watch here
LangChain and Node.js Tutorials
- Embarking on the AI Adventure: Introduction to LangChain and Node.js: Read more
- Shared by @AhmedHemaz
AI in Global Context
AI adoption in the Middle East
Three Takeaways From DeepSeek’s Big Week
- This article explores DeepSeek’s latest advancements and their impact on the AI landscape. It discusses their model’s cost efficiency, the competitive environment, and potential legal concerns. (Read more )
- @OsMo999 references their discussion
Six Takeaways From a Monumental Week for AI
- The article discusses significant events in the AI industry, highlighting DeepSeek’s emergence with cost-effective AI models, the impact on Nvidia’s stock due to concerns over reduced demand for expensive chips, and debates about the legality and ethics of DeepSeek’s model distillation approach. It also mentions OpenAI’s substantial backing from SoftBank, valuing the company at about $300 billion. (Read on WSJ )
Books
Shared by @Mishtar
Generative AI in Action
- The book Generative AI in Action by Amit Bahree, with a foreword by Eric Boyd, is published by Manning. It explores the applications and practical aspects of generative AI. The cover features an illustration of a person in historical attire holding a gift box. (More details )
AI Agents in Action
- The book AI Agents in Action by Micheal Lanham, published by Manning, provides insights into building AI agents and their real-world applications. (More details )
Retrieval-Augmented Generation (RAG) Benchmarks
MTEB Leaderboard - Ranking Embedding Models
- The Massive Text Embedding Benchmark (MTEB) leaderboard hosted by Hugging Face ranks text embedding models based on their performance across diverse NLP tasks. It provides insights into the latest advancements and comparisons in embedding models. (View leaderboard )
- Shared by @TheAhmadOsman
Tools Highlighted
Hugging Face’s cost-effective deployment
Postgres with pgvector as a Vector DB for AI applications
RAG (Retrieval-Augmented Generation) and AI Automation
- Embedding, reranking, segmentation: Jina AI
- Full RAG pipeline: Weaviate Verba
- N8N for AI workflow automation
- Shared by 3eid10
AI Search & Retrieval (RAG) Services
Voyage AI - Enhancing Search & Retrieval
- Voyage AI specializes in enhancing search and retrieval for unstructured data using advanced embedding models and rerankers. Their solutions aim to improve retrieval-augmented generation (RAG) systems by providing high-accuracy, low-latency, and cost-efficient models tailored for various domains, including general-purpose, domain-specific, and company-specific applications. (Learn more )
- Shared by @TheAhmadOsman
Jina AI - Powering Search & Indexing
- Jina AI offers a suite of products designed to improve search capabilities, including Reader for converting URLs to Markdown, Embeddings for multimodal and multilingual data, Reranker for enhancing search relevancy, Classifier for zero-shot and few-shot classification, and Segmenter for text chunking and tokenization. Their models form the foundation for high-quality enterprise search and retrieval-augmented generation (RAG) systems. (Explore Jina AI )
- Shared by 3eid10
If you missed the session, check the recorded discussion !