The International Conference on Learning Representations (ICLR) 2023 will run from May 1st through 5th in Kigali, Rwanda. Intel Labs’ innovations in model linearization include a three-stage training method that trains a DNN model with significantly fewer rectified linear units (ReLUs) driven by a novel measure of non-linearity layers’ ReLU sensitivity.
-
-
Articles récents
- Optimizing SLMs on Intel® Xeon® Processors: A llama.cpp Performance Study
- Intel® Xeon® 6 Processors: The Smart Total Cost of Ownership Choice
- Next-Gen AI Inference: Intel® Xeon® Processors Power Vision, NLP, and Recommender Workloads
- Document Summarization: Transforming Enterprise Content with Intel® AI for Enterprise RAG
- AutoRound Meets SGLang: Enabling Quantized Model Inference with AutoRound
-
Neural networks news
Intel NN News
- Optimizing SLMs on Intel® Xeon® Processors: A llama.cpp Performance Study
In this post, we'll dicuss how to run responsive, CPU-only applications using a quantized SLM in […]
- Intel® AI for Enterprise Inference as a Deployable Architecture on IBM Cloud
Intel® AI for Enterprise Inference as a Deployable Architecture on IBM CloudAuthored by: Pai […]
- Intel® Xeon® 6 Processors: The Smart Total Cost of Ownership Choice
The latest Intel® Xeon® 6 processors deliver performance advantages across key enterprise […]
- Optimizing SLMs on Intel® Xeon® Processors: A llama.cpp Performance Study
-