Taylor Ye

Traditional Data centers vs AI Data centers image

Traditional Data Centers vs AI Data Centers: How Infrastructure Is Evolving to Support AI at Scale

Data centers have always reflected the dominant computing paradigm of their time. For many years, enterprise software, web services, and databases shaped how infrastructure was designed and operated. These workloads emphasized reliability, steady performance, and efficient resource sharing. Artificial intelligence introduces a fundamentally different demand profile. Training and deploying modern
4 min read
Small Language Models vs Large Language Models: Power, Practicality, and the Future of Agentic AI
AI Applications

Small Language Models vs Large Language Models: Power, Practicality, and the Future of Agentic AI

As language models become increasingly central to modern AI applications, particularly within agentic systems, the ongoing pursuit of ever-larger models is prompting a new question: could smaller models provide a smarter and more efficient alternative? While Large Language Models (LLMs) are widely praised for their broad capabilities, growing evidence suggests
5 min read
Stacked NIM blocks above a chip with “Simplify Model Deployment with NIMs on Bitdeer AI” text.
AI Applications

Deploying Foundation Models with a Click: Exploring NVIDIA NIMs on Bitdeer AI

As artificial intelligence transitions from prompt-based tools to autonomous systems, the need for scalable and modular infrastructure becomes essential. NVIDIA Inference Microservices (NIMs) offer a streamlined solution to this challenge, enabling developers and enterprises to deploy powerful open-source foundation models quickly and reliably. Bitdeer AI is an officially licensed partner
3 min read