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🚀 Breaking News: Meta Unleashes Its Biggest Open-Source AI Model Yet – Llama 3.1 with 405 Billion Parameters!Meta has taken a giant leap forward in AI development by releasing Llama 3.1, their most powerful open-source AI model to date, boasting an

Meta has introduced the Llama 3.1 series of large language models (LLMs), featuring a top-tier model with 405 billion parameters, as well as smaller variants with 70 billion and 8 billion parameters. Meta claims that Llama 3.1 matches the performance

30 AI Buzzwords Explained for Entrepreneurs 1) Large Language Model (LLM) LLMs are like super-smart computer programs that can understand and do almost anything you ask them using regular language. Think of tools like ChatGPT or Gemini – they're a

SEO isn’t dead. It’s evolving LLM + SEO = LEO (LLM Engine Optimization). This is how brands are now getting traffic from ChatGPT, Claude, Perplexity, and other AI platforms. While most marketers still chase Google rankings, LEO is about relevance

I fine-tuned 3 models this week to understand why people fail. Used LLaMA-2-7B, Mistral-7B, and Phi-2. Different datasets. Different methods (full tuning vs LoRA vs QLoRA). Here's what I learned that nobody talks about: 1. Data quality > Data quan

𝗧𝗵𝗶𝘀 𝗺𝗮𝗻 𝘄𝗼𝗿𝗸𝗲𝗱 𝗮𝘁 𝗯𝗼𝘁𝗵 𝗢𝗽𝗲𝗻𝗔𝗜 & 𝗚𝗼𝗼𝗴𝗹𝗲 𝗗𝗲𝗲𝗽𝗠𝗶𝗻𝗱. Now, he's building a $9B AI search engine that's challenging Google. And in a mind-blowing interview with YC last week… Aravind Srinivas revealed how he turne

2 ways AI systems today generate smarter answers. I’ve explained both in simple steps below. 𝗥𝗔𝗚 (𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹-𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻) (𝘴𝘵𝘦𝘱-𝘣𝘺-𝘴𝘵𝘦𝘱) RAG lets AI fetch and use real-time external information to ge

What exactly is Context Engineering in AI? A quick 2-minute simple breakdown for you. 𝗙𝗶𝗿𝘀𝘁, 𝗵𝗼𝘄 𝗶𝘀 𝗶𝘁 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝗳𝗿𝗼𝗺 𝗣𝗿𝗼𝗺𝗽𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴? • 𝗣𝗿𝗼𝗺𝗽𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 = crafting a single clever inp