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BREAKTHROUGH INSIGHT: Most people train AI models. Smart people fine-tune AI models. But the real secret? Learning to dance with AI's existing knowledge. Stop forcing. Start flowing.

India should focus on fine-tuning existing AI models and building applications rather than investing heavily in foundational models or AI chips, says Groq CEO Jonathan Ross. Is this the right strategy for India to lead in AI innovation? Thoughts?

💡 5 Things You Need to Master for learn for integrating AI into your project 1️⃣ Retrieval-Augmented Generation (RAG): Combine search with AI for precise and context-aware outputs. 2️⃣ Vector Databases: Learn how to store and query embeddings for e

Will Al software engineer Devin take our jobs? It's a concern on everyone's mind. But the real question is: Will Devin enhance our jobs? The answer is a resounding YES. Devin autonomously builds complete apps with just a prompt. Devin con learn

🤔 𝐎𝐩𝐞𝐧𝐀𝐈 𝐨𝟏 - 𝐢𝐬 𝐢𝐭 𝐦𝐨𝐫𝐞 𝐛𝐢𝐠𝐠𝐞𝐫 𝐨𝐫 𝐦𝐨𝐫𝐞 𝐟𝐢𝐧𝐞-𝐭𝐮𝐧𝐞𝐝? We're all excited about OpenAI's o1 model and many other such bigger models, but here's what keeps me up at night: Are we witnessing a genuinely larger, more a

So imagine you have need a product that you upload any type of doc and chat with it. People like students, teachers, lawyers….. so on would like and need these tool. What if there’s a tool that performance much better with accuracy? Imagine existing

Top 10 AI Research Papers Since 2015 🧠 1. Attention Is All You Need (Vaswani et al., 2017) Impact: Introduced the Transformer architecture, revolutionizing natural language processing (NLP). Key contribution: Attention mechanism, enabling models

"A Survey on Post-Training of Large Language Models" This paper systematically categorizes post-training into five major paradigms: 1. Fine-Tuning 2. Alignment 3. Reasoning Enhancement 4. Efficiency Optimization 5. Integration & Adaptation 1️⃣ Fin

The Next AI Battleground? Open-Source LLMs Are Gaining Fast GPT-4 may still lead the pack — but the real action is now in open-source LLMs, and the gap is closing *faster than anyone expected In just 3 months: - Mistral’s Mixtral matched GPT-3.5 on