Business Coach • 3h
🔥 Government set to name ~8 Indian teams for foundational model incentives next week – second-round beneficiaries may include BharatGen; GPU access remains tight as only ~17,374 of planned 34,333 GPUs are installed so far. 🤔 Why It Matters – More subsidised compute means faster India‑tuned models, but the GPU crunch could slow training unless procurement accelerates or inference‑efficient approaches are prioritised. 🚀 Action/Example – Founders should prepare grant docs and pivot to efficient training/inference (LoRA, distillation, 4‑bit quant) to ride the incentive window despite supply constraints. 🎯 Who Benefits – AI researchers, Indic LLM builders, and startups focused on low‑cost inference at scale. Tap ❤️ if you like this post.
Hey I am on Medial • 5m
"Just fine-tuned LLaMA 3.2 using Apple's MLX framework and it was a breeze! The speed and simplicity were unmatched. Here's the LoRA command I used to kick off training: ``` python lora.py \ --train \ --model 'mistralai/Mistral-7B-Instruct-v0.2' \ -
See MoreAI Deep Explorer | f... • 4m
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
See MoreLet’s connect and bu... • 3m
Why Grok AI Outperformed ChatGPT & Gemini — Without Spending Billions In 2025, leading AI companies invested heavily in R&D: ChatGPT: $75B Gemini: $80B Meta: $65B Grok AI, developed by Elon Musk's xAI, raised just $10B yet topped global benchmar
See MorePython Developer 💻 ... • 6m
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-
See MoreAI Deep Explorer | f... • 5m
"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
See MoreAI Deep Explorer | f... • 4m
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
See MoreDownload the medial app to read full posts, comements and news.