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Fine-Tuning: The Secret Sauce of AI Magic! Ever wonder how AI gets so smart? It’s all about fine-tuning! Imagine a pre-trained model as a genius with general knowledge. 🧠✨ Fine-tuning takes that genius and hones its skills for a specific task, li

A Reddit post claims that 90% of India's engineering graduates struggle with coding. The anonymous startup founder admits to firing new hires within weeks due to lack of job readiness. Commenters criticize the founder's hiring process and the general

WordPress developers hit me up with your portfolio and price for an E-commerce site. If everything goes fine we can work together in long run...

Hey everyone, I'm an engineering student geeking out over Generative AI. Loving LangChain, Hugging Face models, Crew.ai's chatbots, fine-tuning, and RAG. Plus, machine learning and data science are pretty cool too! Anyone else into this stuff? Looki

#Verification takes 70% of chip development time—but ChipStack automates the process inside VSCode. ✅ Ingests your spec ✅ Generates testplan ✅ Creates a formal testbench ✅ Runs on industry-standard tools No more weeks of debugging #Semiconductor

Hey everyone, I'm an engineering student geeking out over Generative AI. Loving LangChain, Hugging Face models, Crew.ai's chatbots, fine-tuning, and RAG. Plus, machine learning and data science are pretty cool too! Anyone else into this stuff? Looki

Today i learnt about Context Engineering and i agree that its the New Prompt Engineering! People often ask, "How do I get better responses from ChatGPT?” I used to think it was about writing the perfect prompt. But it’s not just what you ask, it’s

📍Is Quick-commerce really a sustainable and profitable business for the long run? because every single company in this sector is doing huge loss or it's just for T1 cities?🦆

AI-Powered Prompt Enhancer – Idea Validation These days, everyone talks about the future of AI and how to stay secure in this fast-changing era. And the most common suggestion? “Learn Prompt Engineering.” But what is prompt engineering, really? It’

"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