Pure AI editors outline when to run LLMs locally vs. in the cloud -- local can lower usage cost, improve reliability, and keep data on-prem, but demands hardware spend, in-house expertise, and accepts model/feature limits; many scenarios benefit from a hybrid approach.
- By Pure AI Editors
- 09/02/2025
How an agent-powered data fabric can give enterprises real-time, self-service access to all their data, without breaking their stack.
Harnessing data the moment it's created can mean the difference between missing an opportunity and seizing it.
Why companies overwhelmingly choose OpenAI for AI work today--and why a shift to competitors like Google, Meta or Anthropic could happen fast, according to AI expert Dr. James McCaffrey.
- By Pure AI Editors
- 08/01/2025
Get ready for the lakehouse evolution into an AI-native platform that thinks, learns and scales alongside data analysts.
With AI-driven, application-centric management across hybrid environments, it's a new era in network security.
A clear, mid-level explainer of the Attention mechanism at the heart of AI models like GPT for technical professionals who want to understand how models process input.
- By Pure AI Editors
- 07/01/2025
Reinforcement learning is key to how LLMs like ChatGPT improve and avoid mistakes -- but it also introduces potential bias. We break down how it works and why understanding it matters for anyone using or building with AI.
- By Pure AI Editors
- 06/02/2025
A factory analogy demystifies how Transformers power AI like GPT -- perfect for non-data scientists seeking to grasp the basics.
- By Pure AI Editors
- 05/01/2025
Your guide to local, global and virtual events that every enterprise should attend to stay ahead of AI trends and technologies.