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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-

🚀 Key takeaway from IndiaAI Mission CEO Abhishek Singh: Indian LLM startups can’t lean on government help for too long — they need to think GLOBAL to stand against players like OpenAI. "Govt can give a push at the start, but long-term success need

Food for thought. Instead of building AI models/agents/RAGs, why not build for AI. There is a dearth of auxiliary products and services for AI development such as benchmarking, training environments, data cleaning, synthetic data generation etc. But

🚨 Open AI is an Wrapper👀🤯 Hot take, but let’s break it down logically: OpenAI is not a full-stack AI company — it’s a high-level wrapper over Azure and NVIDIA. Here’s why that matters 👇 🔹 1. Infra Backbone = Microsoft Azure Almost 90%+ of Op

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

OpenAI spent millions if not billions developing and training LLMs. Same is for Google, Microsoft and Meta.. the only difference being they are releasing their LLMs now after the craze of AI is at its peak. But I don't understand how companies like K

Innovation idea, improvement, Scalability of product or service? The innovation behind Sunraise Solar lies in its unique ecosystem approach that merges clean energy solutions with education and entrepreneurship. By offering online solar training, it

🚨 OpenAI Erased Its $6.5 Billion Deal With Jony Ive From the Internet -What Are They Hiding? One month after a flashy reveal, all traces of the groundbreaking partnership vanished. A trademark dispute is just the surface… Read: https://orcus4ai.com/

NVIDIA isn’t just a chipmaker—it’s the brain behind the AI revolution. From powering gaming graphics to training ChatGPT-like models, NVIDIA mastered one thing: timing. While others saw GPUs as gaming tools, NVIDIA saw them as the future of computing