Tech Times on MSN

LLM quantization without calibration data matches SmoothQuant: DualQuant targets FP4 hardware

LLM quantization without calibration data: DualQuant from AI inference startup d-Matrix eliminates the dataset requirement ...

A Record of Learning About Quantization and Deployment Techniques for LLMs in Edge AI

I am compiling this memorandum based on related materials to document what I have learned about quantization and deployment ...
BIOENGINEER

New Co-Design Framework Speeds Up LLM Inference on Mixed Hardware by Taming Memory Bottlenecks

CoOpt, an algorithm-hardware co-design framework that boosts large language model inference throughput by up to 13.43 percent ...
InfoWorld

What is model quantization? Smaller, faster LLMs

Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...
XDA Developers on MSN

MoE models changed what fits on my GPU means, and most hardware advice hasn't caught up

My 10-year-old GPU runs 26B LLMs now, and MoE models changed everything about LLM-hosting advice ...
Geeky Gadgets

How Unsloth Makes Fine-Tuning LLMs a Breeze to Boost AI Performance

Fine-tuning large language models (LLMs) might sound like a task reserved for tech wizards with endless resources, but the reality is far more approachable—and surprisingly exciting. If you’ve ever ...
VentureBeat

Here are 3 critical LLM compression strategies to supercharge AI performance

In today’s fast-paced digital landscape, businesses relying on AI face new challenges: latency, memory usage and compute power costs to run an AI model. As AI advances rapidly, the models powering ...

The Rise of Small Specialized Models: Practical AI Execution on General Devices

Practical AI Execution on General DevicesIn recent years, large language models (LLMs) with hundreds of billions of ...
BIOENGINEER

PharmAI: Small Language Models Master Pharmaceutical QA on a 6 GB GPU

The distinction between small language models and their larger counterparts is more than a matter of parameter counts. Models ...

Qualcomm CEO Says Smartphones Will Run 100B AI Models by 2028

Qualcomm CEO Cristiano Amon believes smartphones will be able to continuously run AI models with 100 billion parameters by 2028, despite major challenges ...