Soumya Ranjan Das·5d agoThe AI Selloff : A Verdict on Expensive AI ?The headlines say the AI bubble burst. The data says something more consequential. What collapsed was expensive AI: chips, data-center debt…
InGoPenAIbyAditya Inamdar·Oct 16FNet: How Google Replaced Self-Attention with the Fourier Transform and Got 97% of BERT for 80%…The attention-free encoder trains 80 percent faster on GPUs and 70 percent faster on TPUs at 512 tokens in the authors’ benchmarks. It is…A response icon2A response icon2
Sumit Sah·May 22Revolutionizing Real-Time Video Generation: Meet Q-ARVD, The Quantization Breakthrough for…How researchers solved the unique challenges of quantizing autoregressive video diffusion models to make real-time AI video practical.
Ayushi Jain·Apr 21Everything was working perfectly with AI… until someone asked it to draw a dog.When AI came — especially tools like Codex, Claude — where it can access all your code directories, create new files, execute code… you…
Argha Paul·Jan 18Bigger is not always better : The Shift to AI EfficiencyAI efficiency is now taking center stage as the era of simply building bigger models reaches its natural limits. While Large Language…
Haze News·Jan 7Project χθos: A Proof of Concept for a New Paradigm in Efficient AI1. The Premise: Challenging the “Scale or Die” Dogma
InSharing SciencebyMohit Sewak, Ph.D.·Oct 22, 2025Flow Matching (The Next Gen AI Algorithm): From 1000-Steps to a Single-Step Media Generation…How a simulation-free training method is quietly outpacing today’s state-of-the-art diffusion and normalizing flows models.A response icon2A response icon2
Dr. Shouke Wei·Oct 9, 2025Unleashing Large Language Models with oLLM: Power on a BudgetEfficient AI Inference for Everyone, Anywhere
Vamshi nagireddy·Oct 5, 2025Beyond the Algorithms: Hardware Secrets for Faster, More Efficient AIWe’ve pushed algorithms to their limits. Now, the future of artificial intelligence is being forged in silicon.
InArtificial Intelligence in Plain EnglishbyRaahul Krishna Durairaju·Aug 24, 2025Post-Training Quantization vs Quantization-Aware Training: A Hands-On Comparison with a Small LLaMA…Introduction
