How Mixed-Precision Quantization Could Break AI’s Power Addiction

Data originates at the edge, and processing it locally unlocks powerful real-time efficiencies that open very rich product ...
Semiconductor Engineering

Neural Network Model Quantization On Mobile

The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in ...
Business Wire

Elastic Introduces Better Binary Quantization Technique in Elasticsearch

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI Company, announced Better Binary Quantization (BBQ) in Elasticsearch. BBQ is a new quantization approach developed from insights ...
GIGAZINE

Huawei announces 'SINQ,' an open-source quantization method that reduces memory usage of AI models by 60-70% and enables them to run on inexpensive, low-performance hardware

Huawei, a major Chinese technology company, has announced Sinkhorn-Normalized Quantization (SINQ), a quantization technique that enables large-scale language models (LLMs) to run on consumer-grade ...
VentureBeat

Here are 3 critical LLM compression strategies to supercharge AI performance

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More In today’s fast-paced digital landscape, businesses relying on AI face ...
InfoWorld

What is PyTorch? Python machine learning on GPUs

PyTorch 1.10 is production ready, with a rich ecosystem of tools and libraries for deep learning, computer vision, natural language processing, and more. Here's how to get started with PyTorch.
Geeky Gadgets

Local LLMs vs Cloud AI : How Local LLMs Are Changing AI Workflows

What if you could harness the power of innovative artificial intelligence without relying on the cloud? Imagine running a large language model (LLM) locally on your own hardware, delivering ...
The n-Category Café

Second Quantization and the Kepler Problem

The poet Blake wrote that you can see a world in a grain of sand. But even better, you can see a universe in an atom!