Sivers and GlobalFoundries Collaborate on Silicon Photonics for AI Datacenters

Jun 2, 2026
Sivers Semiconductors and GlobalFoundries announced a partnership to develop silicon photonics solutions for AI datacenter infrastructure, integrating Sivers' laser arrays into GlobalFoundries' photonics platform and SCALE optical engine.
Sivers and GlobalFoundries Collaborate on Silicon Photonics for AI Datacenters

Sivers Semiconductors and GlobalFoundries have announced a strategic collaboration to develop silicon photonics solutions for AI infrastructure, according to a press release.

Sivers' laser arrays will be integrated into reference designs built on GlobalFoundries' silicon photonics platform. The partnership supports various optical connectivity architectures, including co-packaged optics, linear pluggable optics, and other datacenter interconnect solutions.

The laser arrays will also be available in GlobalFoundries' Silicon Photonics Co-packaged Advanced Light Engine (SCALE) platform, which combines integrated photonic devices, wavelength division multiplexing, and advanced packaging to improve bandwidth density and scalability.

The companies stated that this collaboration targets the growing demand for high bandwidth and energy efficient optical connectivity in AI datacenters, with the pluggable optics market expected to reach 25 billion dollars 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

Enterprise AI Brief

Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.

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.