Back

X updates its developer agreement to ban third parties from using the X API or X Content for training or fine-tuning foundation or frontier AI models.

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?

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 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

OpenAI researchers have discovered hidden features within AI models that correspond to misaligned "personas," revealing that fine-tuning models on incorrect information in one area can trigger broader unethical behaviors through what they call "emerg

Working on a cool AI project, that involves vector db and LLM fine-tuning

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.

LLM Post-Training: A Deep Dive into Reasoning LLMs This survey paper provides an in-depth examination of post-training methodologies in Large Language Models (LLMs) focusing on improving reasoning capabilities. While LLMs achieve strong performance

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

💡An Idea to Change the Game for AI Startups: Making AI Processing Faster, Cheaper, and Effortless Running AI models like ChatGPT, DALL·E, or AlphaCode is a computing monster—they need massive power to function, which makes them expensive to operate