Huawei Proposes Next Generation OTN for AI Data Center Networks
Huawei proposed in an announcement a Next Generation optical transport network system for networks centered on AI data centers. The company presented the system at NetworkX 2026 in Vienna.
For data center interconnection, the system provides capacity from 800G to 2T and an OTN capacity pool that can reserve capacity across multiple directions. Huawei said this design reduces the resources needed for advance capacity deployment.
For data center access, the system includes end to end optical cross connects, millisecond level wavelength switched optical networking, and fgOTN bandwidth from 10 Mbps to 1 Gbps. It also includes quantum key distribution for encryption, plus hardware and software changes intended to prevent service outages.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Enterprise AI Brief, Silicon Brief or Daily AI Brief.
Also, consider following us on social media:
More from Enterprise
Oct 15 Legora and Laurel Partner on Automatic Legal Time Capture Oct 15 Anthropic Licenses OPAQUE Technology and Hires Team Members Oct 15 EU survey finds 42% of smaller companies use AI or automated management Oct 15 Zenzap Raises $44 Million for AI Workplace Messaging App Oct 15 EQT AI Infrastructure Fund Reaches $11.5 Billion in NAVMore from Data Centers
Oct 15 Senators Question Meta Tax Credits for AI Data Centers Oct 15 Ukrainian Strikes Disrupt Yandex Services Across Central Asia Oct 15 Sachin Katti to Leave OpenAI Infrastructure Role Oct 15 Ricursive Intelligence Details AI System for Chip Design Oct 15 ALPS Names Brian Turnbow to Lead AI Data Center ExpansionEnterprise AI Brief
Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.
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 moreYou may also like
Huawei NG WAN Reaches Commercial Use at Over 60 Carriers
Huawei Outlines AI Native Core Network for Agent Services
Cisco and NVIDIA Plan Open 400G Optics Specification
Huawei Upgrades Stellar AI Network for AI Computing
Airoha Details 50G PON AI Gateway Processor
Daily AI Brief: the AI news that matters, in your inbox.