Cloud Computing | News, how-tos, features, reviews, and videos
In the ramp-up for AI, companies feel pressured to choose cloud or on-premises. Let’s learn from past mistakes and realize the solution is rarely one size fits all.
If you've wondered whether you should invest in cloud certification, or which certifications really make a difference, this article has answers.
Amazon Q Developer works well for completing lines of code, doc strings, and if/for/while/try code blocks, but can’t generate full functions for certain use cases.
At Build, Microsoft described how Azure is supporting large AI workloads today, with an inference accelerator, high-bandwidth connections, and tools for efficiency and reliability.
The Linux packager’s SUSE AI Early Access Program could interest companies wanting to run generative AI on premises.
If your goals are high-velocity software development and frequent delivery of working builds to production, you need continuous integration/continuous delivery (CI/CD). The cloud is the best place for CI/CD. This guide explains the tools.
Rapid cloud adoption has left many enterprises needing help with their technology infrastructure. These simple rules will keep the pain to a minimum.
A brief guide to data visualization, data analytics, and data science platform capabilities and differences, and seven steps to selecting the right data platform for your needs.
Free open-source framework integrates with scads of vector stores, LLMs, and data sources and works for Q&A, structured extraction, chat, semantic search, and agent use cases.
AI as a service (AIaaS) provides customers with cloud-based access for integrating and using AI capabilities in their projects or applications without needing to build and maintain their own AI infrastructure. Here are your options.