Huiyu Technology upgrades AI-dedicated network equipment, Siemens Energy becomes a new customer.

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Hewlett Packard Enterprise (HPE) is betting on accelerating demand for AI infrastructure, launching a dedicated switch for inference workloads, and announcing that Siemens Energy will adopt its private cloud solution co-developed with NVIDIA.

CEO Antonio Neri stated this week that networking is the core foundation for enterprise AI implementation. HPE’s earnings outlook released earlier this month exceeded Wall Street expectations, precisely because AI demand for servers and networking products has increased significantly.

Siemens Energy will deploy HPE and NVIDIA’s AI portfolio to run simulation programs and manage engineering tasks in a private cloud environment.

Analysts believe such enterprise-class AI deployment cases directly reflect traditional enterprise clients accelerating their embrace of AI, and validate HPE’s network-centric strategy for entering the AI market.

HPE’s stock closed down 0.91% on Tuesday, but has risen 47% over the past month.

Dedicated inference switches, targeting the scale-up market

At its annual conference, HPE released the HPE Juniper QFX series switches, designed specifically for AI inference workloads. This product targets "scale-up" networking scenarios—where computing power or capacity is increased within a single system, rather than through connecting more machines to boost performance.

In such architectures, users need to interconnect multiple AI chips at high speeds and rapidly transmit data between them to ensure responsive AI model inference. The QFX series is designed to meet this demand.

This product line is built upon the networking technology that HPE acquired by purchasing Juniper Networks last year for around $13 billion, marking the latest integration of Juniper assets with AI requirements by HPE.

Deepening NVIDIA collaboration, building the AI agent ecosystem

HPE is simultaneously expanding its partnership with NVIDIA, adding more integration support for NVIDIA’s AI models, agent tools, and chips. NVIDIA’s GPUs currently handle the vast majority of AI model training and inference tasks worldwide and have become an indispensable core partner in the AI infrastructure sector.

Antonio Neri said in an interview:

"Our conviction is that the core foundation lies in networking. If the right infrastructure, suitable computing power, and corresponding workloads and data cannot be connected, enterprises won’t truly realize AI agent transformation."

He pointed out that enterprise customers are accelerating their adoption of AI, increasingly relying on AI agents to autonomously handle programming, customer service, and financial tasks. Siemens Energy’s case is a specific example of this trend.

Competitive landscape: Cisco and Broadcom in the arena

In the networking equipment market, HPE faces direct competition from Cisco, while Broadcom acts as both a competitor and a partner, depending on the product and service category. Both companies are increasing investment and updating their networking product lines to compete for AI business.

It is worth noting that NVIDIA also maintains close cooperation with Cisco, which adds complexity to the competitive landscape. Whether HPE can leverage Juniper’s technical foundation and its deepened cooperation with NVIDIA to gain a larger share in the AI networking market remains to be seen.

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