Robuta

Face recognition (FR) has been applied to nearly every aspect of daily life, but it is always accompanied by the underlying risk of leaking private...

AI Customer Engineer, Chris Bogdiukiewicz, introduces PyTorch for the IPU. With PopTorch™ - a simple Python wrapper for PyTorch programs, developers can...

Abstract page for arXiv paper 2111.12550: A Worker-Task Specialization Model for Crowdsourcing: Efficient Inference and Fundamental Limits

Learn to build retrieval-augmented generation in 4 steps: data augmentation, inference, workflows, and post-processing. See vector embedding step by step.

Nov 7, 2023 - Large language models (LLMs) offer incredible new capabilities, expanding the frontier of what is possible with AI. However, their large size and unique…

With the advancement of machine learning, a growing number of mobile users rely on machine learning inference for making time-sensitive and safety-critical...

Integrated Assessment Models (IAMs) such as RICE have long provided a foundation for studying the coupled dynamics of the global economy and climate system....

The accurate prediction of the solar Diffuse Fraction (DF), sometimes called the Diffuse Ratio, is an important topic for solar energy research. In the present...

Nov 25, 2025 - Superhuman cut P95 latency by 80% across dozens of custom embedding models in just one week after adopting Baseten Embedding Inference.

NVIDIA Triton Inference Server (Triton) is an open-source inference serving software that maximizes performance and simplifies model deployment at scale

Large language models (LLMs) have demonstrated remarkable capabilities in complex reasoning tasks. However, existing approaches mainly rely on imitation...

Dec 8, 2025 - Flyin’ Like a Lion on Intel Xeon

Hendrik ter Horst, Philipp Cimiano. Proceedings of the Fourth Workshop on Structured Prediction for NLP. 2020.

Learn to build retrieval-augmented generation in 4 steps: data augmentation, inference, workflows, and post-processing. See vector embedding step by step.

Bill MacCartney, Michel Galley, Christopher D. Manning. Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing. 2008.

The popularity of Convolutional Neural Network (CNN) models and the ubiquity of CPUs imply that better performance of CNN model inference on CPUs can deliver...

Abstract page for arXiv paper 2104.12470: Easy and Efficient Transformer : Scalable Inference Solution For large NLP model

Deploy a vLLM model as an inference service,Container Service for Kubernetes:Vectorized Large Language Model (vLLM) is a high-performance large language model...

The U.S. Department of Energy's Office of Scientific and Technical Information

Deploying large language models (LLMs) poses a challenge in optimizing inference efficiency. In particular, cold start delays—where models take significant...

We are often interested in decomposing complex, structured data into simple components that explain the data. The linear version of this problem is...

Deploy a DeepSeek distilled model inference service on ACK,Container Service for Kubernetes:This topic describes how to use KServe to deploy a production-ready...