A renewed wave of institutional interest is building around Chinese e-commerce giant Alibaba. While geopolitical tensions ...

Discover why Alibaba's AI-driven Cloud Intelligence Group drives strong growth and upside potential. Click here to read my ...

By participating in ISV Catalyst, software vendors gain access to Akamai's expansive cloud and edge computing infrastructure, positioning them to capture new demand as enterprises increasingly rely on ...

Bairong Inc. (the "Company", "we" , "us" or "our" ; HKEX: 6608), a leading cloud-based AI turnkey service provider, today unveiled its enterprise AI Agent strategy where it introduced its Results as a ...

Government agencies worldwide are rapidly transforming digital strategies with the adoption of government cloud solutions, driven by a heightened focus on security, compliance, an ...

Data centers consume substantial amounts of power, much of which is dedicated to cooling the computers inside since they generate substantial amounts of heat as a byproduct of their operation.

What will the year ahead bring for cloud computing? We predict it will center around two major races: the hyperscaler race to build AI-native cloud infrastructure and, similarly, the enterprise race ...

The way clusters of differently sized water droplet populations are distributed within clouds affects larger-scale cloud properties, such as how light is scattered and how quickly precipitation forms.

After signing agreements to use computing power from Nvidia, AMD and Oracle, OpenAI is teaming up with the world’s largest cloud computing company. By Cade Metz Reporting from San Francisco After ...

Anthropic announced that it would expand its use of Google Cloud’s tensor processing unit (TPU) chips, in order to provide the company with access to the computing power and resources required for the ...

Abstract: The advancement of Large Language Models (LLMs) with vision capabilities in recent years has elevated video analytics applications to new heights. To address the limited computing and ...

Abstract: Deep neural network (DNN) model partitioning and pruning have proven to be effective methods for enhancing resource efficiency and reducing inference delay by strategically allocating DNN ...