A decade into development, the world’s top container orchestrator is more extensible than ever. But usability is still ...

However, the focus is shifting toward optimizing the resources required for inference, which is when a pre-trained AI model makes predictions or decisions based on new, unseen data (rather than ...

TL;DR: DeepSeek's R1 model is utilizing Huawei's Ascend 910C AI chips for inference, highlighting China's advancements in AI despite US export restrictions. Initially trained on NVIDIA H800 GPUs ...

The new AI Connect suite from Verizon comes as McKinsey estimates 60% to 70% of AI workloads will be for inference by 2030 It’s been a busy two weeks in the world of AI. OpenAI and partners announced ...

McKinsey predicts 60-70% of AI workloads will transition to real-time inference by 2030. McKinsey also outlines that there is an urgent need for low-latency connectivity, computing and security.

This is why IDC predicts that by 2028, in response to the growth of GenAI inferencing workloads, 60% of the Global 2000 will supersize edge IT by doubling spend on remote compute, storage ...

Learn More Inference-time scaling is one of the big themes of artificial intelligence in 2025, and AI labs are attacking it from different angles. In its latest research paper, Google DeepMind ...

The technique, called SwiftKV, is an optimization technique for large language models developed by Snowflake AI Research and released to open source that improves the efficiency of the inference ...

Triton Inference Server is an open source inference serving software that streamlines AI inferencing. Triton enables teams to deploy any AI model from multiple deep learning and machine learning ...

Embedded Vision and Inferencing are two critical technologies for many modern devices such as drones, autonomous cars, industrial robots, etc. Embedded vision uses computer vision to process images, ...