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Build Agentic RAG without vector database or chunking. PageIndex transforms PDFs into tree structures, preserving the original context, that AI agents can reason through like an intelligent table of contents. 100% free and opensource.

openai dropped a banger guide on building ai agents it's a must read for anyone exploring or building ai agents here's a simple breakdown 🧵

265 pages of everything you need to know about building AI agents. 5 things that stood out to me about this report:

elvis by the time you read all 265 pages agents will be completely different and you’ll have to read a new paper

Google literally published a 69-page prompt engineering masterclass

41 years ago today, I was supposed to be studying for freshman finals. Instead, I started Dell Technologies with $1,000 and a dream. What an amazing journey it’s been thanks to our incredible team, customers, and partners. The next 41 will be even bigger and more fun power by AI and

Dear IAF, PMO, NIA Requesting air strikes on this site which is a confirmed hideout of highly dangerous saboteurs who are helping Pakistan. They were helping China too. This is the office of The Hindu.

1. LLM Course Want to master large language models quickly? This course guides you through training, fine-tuning, and deploying LLMs using HuggingFace Transformers. huggingface.co/learn/llm-cour…

Meanwhile.....

Hello Donald J. Trump Could you please mediate with BBMP to ESCALATE Ejipura flyover works in Bengaluru. We'll name it as MAGA Trump flyover & with BMRCL for Yellow line Metro Trains too in Bangalore

Anthropic 𝗷𝘂𝘀𝘁 𝗿𝗲𝗹𝗲𝗮𝘀𝗲𝗱 𝗮 𝗕𝗶𝗯𝗹𝗲 𝗳𝗼𝗿 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝗜𝘁 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝘀 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗖𝗼𝗱𝗶𝗻𝗴 𝗮𝗻𝗱 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀 📌 𝗛𝗲𝗿𝗲'𝘀 𝗮 𝗾𝘂𝗶𝗰𝗸 𝘀𝘂𝗺𝗺𝗮𝗿𝘆 - 1. 𝗔𝗴𝗲𝗻𝘁

The 5 Levels of AI Agents Lets explore the 5 levels of AI Agents, from simple to complex. Always start with level 1 and add complexity as needed. Level 1: Agent with tools and instructions. When people say agents are just LLM + tool calls in a loop, this is what they mean (this

DeepSeek just dropped the single best end-to-end paper on large model training. It covers — Software (MLA, training in FP8, DeepEP, LogFMT) — Hardware (Multi-Rail Fat Tree, Ethernet RoCE switches) — Mix (IBGDA, 3FS filesystem) DeepSeek's engineering depth is insane. Must read.

Different embedding models have incompatible vector spaces. But they are so similar that you can translate between them. A new paper from Cornell researchers introduces "vec2vec": It’s the first method that can translate embeddings from one vector space to another with NO

Pytest for LLM Apps! DeepEval turns LLM evaluation into a two-line test suite, helping you identify the best models, prompts, and architecture for your AI workflow. Works with any framework, including LlamaIndex, Langchain, CrewAI, and more. 100% open-source, runs locally.

OpenAI, Google, and Anthropic just dropped the guides on: - Prompt Engineering - Building effective Agents - AI in Business - 601 AI use cases and so much more... 9 best guides you don’t want to miss:

Anthropic just dropped Free AI courses on: - Prompt Engineering - Building agents - Best practices for Agentic Coding - Collaborate with AI systems .... and so much more! 9 best guides you don’t want to miss:

Anthropic is killing it with these technical posts. If you're an AI dev, stop what you are doing and go read this. It shows, in great detail, how to implement an effective multi-agent research system. Pay attention to these key parts:

A breakthrough has been achieved by demonstrating quantum entanglement based communication in an experimental setup through DRDO-Industry-Academia Centre of Excellence (DIA-CoE), IIT Delhi. The free-space quantum secure communication using quantum entanglement over a distance of

Man is living in a different Bengaluru…