IEEE

A Developer’s Guide to Compressing Pre-Trained Transformer Neural Networks Across Different Domains

Abstract: Transformer neural networks have become the benchmark across a variety of domains in part thanks to their competence in comprehending the importance and dependencies between large input ...
Tech Times

Compile Once, Run Offline: New AI Method Matches 32B Models With a 23MB File

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2 ...

Waterloo's PAW compiles task specs into 23MB LoRA adapters a 600M-parameter model runs entirely offline.

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2 ...
IEEE

IHUD-BERT: A Large-Scale Network Traffic Classification Method Based on Pre-training Transformers and Knowledge Distillation

Abstract: Accurate and efficient classification of large-scale network traffic is fundamental to ensuring network Quality of Service (QoS) and security. However, existing methodologies face critical ...
SiliconANGLE

Google open-sources speedy DiffusionGemma text diffusion model

Google LLC today released DiffusionGemma, a large language model based on an emerging machine learning approach known as text diffusion. The company says the algorithm can generate text four times ...
VentureBeat

Researchers say they trained a foundation model from scratch for about $1,500

Training a foundation LLM from scratch costs millions and requires internet-scale data — which is why most enterprises don't bother. Sapient thinks it has a cheaper path. To overcome this brute-force ...