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Hiring AI/ML Engineer 🚀 Join us to shape the future of AI. Work hands-on with LLMs, transformers, and cutting-edge architectures. Drive breakthroughs in model training, fine-tuning, and deployment that directly influence product and research outcom

"Synthetic Data" is used in AI and LLM training !! • cheap • easy to produce • perfectly labelled data ~ derived from the real world data to replicate the properties and characteristics of the rela world data. It's used in training an LLM (LLMs

3B LLM outperforms 405B LLM 🤯 Similarly, a 7B LLM outperforms OpenAI o1 & DeepSeek-R1 🤯 🤯 LLM: llama 3 Datasets: MATH-500 & AIME-2024 This has done on research with compute optimal Test-Time Scaling (TTS). Recently, OpenAI o1 shows that Test-

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

Meta's Llama 3 model scales open language models, boasting improved performance and various sizes. With a focus on addressing fatigue, it utilizes diverse training methods and achieves impressive results, strengthening the open LLM ecosystem

10 Best LLM Tools to Simplify Your Workflow 1️⃣ LangChain LangChain's flexibility suits complex AI and multi-stage processing. 2️⃣ Cohere Cohere offers integration, scalability, and customization. 3️⃣ Falcon Falcon offers cost-effective, high-per

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.

💡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

India’s large language model (LLM) is expected to be ready within the next 10 months, said the Minister of Electronics and IT Ashwini Vaishnaw on Thursday. “We have created the framework, and it is being launched today. Our focus is on building AI m

"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