AI Model Optimization

LoRA is a go-to for efficient fine-tuning, but it has a hidden flaw. We break down why it struggles to learn new facts and how a simple fix, RS-LoRA, can solve the problem.

Researchers from MIT, NVIDIA, and Zhejiang University have developed TriAttention, a new method that dramatically speeds up large language models without sacrificing accuracy. It solves the massive memory problem that slows down complex reasoning.

In a world of giant AI models, Liquid AI just dropped something different: a tiny 350M parameter model that was trained on a mind-boggling 28 trillion tokens. Here's why this small but mighty AI could change how we think about intelligence on our devices.

Ever wonder why running LLMs at scale eats up so much GPU memory? The culprit is often a wasteful process called KV caching. Discover how Paged Attention, a clever trick inspired by your computer's own memory management, fixes this and dramatically boosts performance.

Ever heard of an AI model that gets more powerful by shedding a third of its size? Meet Yuan 3.0 Ultra, a new model that's rewriting the rules on AI efficiency and performance. Let's break down how it works.

Google just dropped Gemini 3.1 Flash-Lite, a super-fast, low-cost AI model. But the real story is its new 'Thinking Levels' feature, which lets you control its brainpower on the fly. Let's break down why this is a huge deal for developers.

Running large language models is a memory nightmare, mostly due to the massive KV cache. NVIDIA just dropped a new technique called KVTC that compresses this cache by 20x with almost no accuracy loss. Here's how it works and why it matters.

A wild new paper from ByteDance suggests we've been teaching AI to reason all wrong. Instead of imitating keywords, true long-term thinking is held together by "molecular bonds," just like in chemistry. Here's what that means and why it's a huge deal.

For years, we thought longer AI answers were better. New research from Google proves the opposite is often true, and introduces a new metric that boosts accuracy while cutting inference costs by nearly 50%.

Ever wondered how to make a large language model less... weird? This guide breaks down how to align an LLM with human preferences using DPO and QLoRA, all on a single GPU.

Remember when AI needed a massive data center? Liquid AI just dropped a 1.2 billion parameter reasoning model that fits in under 1GB on your phone. It's not a chatbot—it's a planner that thinks out loud.

Tired of giant, cloud-only AI models? Zhipu AI just dropped GLM-4.7-Flash, a powerful 30B model designed for developers who want top-tier coding performance without the massive overhead. Let's see if it's the local powerhouse we've been waiting for.