Core AI to Partner with CSPM Resources on AI Data Centers in Malaysia

Feb 8, 2026
Core AI Holdings, Inc. has signed a memorandum of understanding with CSPM Resources SDN BHD to pursue AI-ready data center projects in Malaysia, aiming to retrofit existing facilities into Tier 3 or Tier 4 AI-capable sites within 12 months.

Core AI Holdings, Inc. has entered into a memorandum of understanding with CSPM Resources SDN BHD to develop AI-ready data centers in Malaysia, announced in a press release.

The collaboration aims to identify and upgrade existing edge computing facilities into Tier 3 or Tier 4 AI-capable centers. By leveraging current infrastructure for power and connectivity, the companies expect to shorten development timelines, targeting operational readiness in about 12 months.

Once upgraded, the facilities will be positioned as co-location assets or for sale to hyperscalers seeking AI-optimized infrastructure. The partnership follows growing hyperscaler investment in Malaysia from companies such as Amazon Web Services, Oracle, Google, TikTok, and Microsoft.

CSPM brings long-standing experience in Malaysia’s data center industry, including integration expertise and established connections with government and utility stakeholders. Core AI said the partnership provides a strategic entry into Malaysia’s expanding AI infrastructure market, which is projected to grow significantly by 2030.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Silicon Brief, Enterprise AI Brief or Daily AI Brief.

Also, consider following us on social media:

AI Chips & Datacenters Enterprise AI AI Brief AI Brief (X)
Free newsletter

Silicon Brief

Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.