The quiet infrastructure shift powering the next generation of data centers
Updated
January 30, 2026 11:42 AM
Peripheral Component Interconnect Express (PCIe) port on a motherboard, coloured yellow. PHOTO: UNSPLASH
Modern data centers operate on a simple yet fundamental principle: computers require the ability to share data extremely quickly. As AI and cloud systems grow, servers are no longer confined to a single rack. They are spread across many racks, sometimes across entire rooms. When that happens, moving data quickly and cleanly becomes harder.
Montage Technology, a Shanghai-based semiconductor company, builds the chips and connection systems that help servers exchange data without delays. This week, the company announced a new Active Electrical Cable (AEC) solution based on PCIe 6.x and CXL 3.x — two important standards used to connect CPUs, GPUs, network cards and storage inside modern data centers.
In simple terms, Montage’s new AEC product helps different parts of a data center “talk” to each other faster and more reliably, even when those parts are physically far apart.
As data centers grow to support AI and cloud workloads, their architecture is changing. Instead of everything sitting inside one rack, systems now stretch across multiple racks and even multiple rows. This creates a new problem: the longer the distance between machines, the harder it is to keep data signals clean and fast.
This is where Active Electrical Cables come in. Unlike regular copper cables, AECs include small electronic components inside the cable itself. These components strengthen and clean up the data signal as it travels, so information can move farther without getting distorted or delayed.
Montage’s solution uses its own retimer chip based on PCIe 6.x and CXL 3.x. A “retimer” refreshes the data signal so it arrives accurately at the other end. This allows servers, GPUs, storage devices and network cards to stay tightly connected even across longer distances inside large data centers.
The company also uses high-density cable designs and built-in monitoring tools so operators can track performance and fix issues faster. That makes large data centers easier to deploy and maintain.
According to Montage, the solution has already passed interoperability tests with CPUs, xPUs, PCIe switches and network cards. It has also been jointly developed with cable manufacturers in China and validated at the system level.
What makes this development important is not just speed. It is about scale. AI models, cloud services and real-time applications demand massive amounts of data to move continuously between machines. If that movement slows down, everything else slows with it.
By improving how machines connect across racks, Montage’s AEC solution supports the kind of infrastructure that next-generation AI and cloud systems depend on.
Looking ahead, the company plans to expand its high-speed interconnect products further, including work on PCIe 7.0 and Ethernet retimer technologies.
Quietly, in the background of every AI system and cloud service, there is a network of cables and chips doing the hard work of moving data. Montage’s latest launch focuses on making that hidden layer faster, cleaner and ready for the scale that modern computing now demands.
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Where smarter storage meets smarter logistics.
Updated
January 8, 2026 6:32 PM
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Kioxia's flagship building at Yokohama Technology Campus. PHOTO: KIOXIA
E-commerce keeps growing and with it, the number of products moving through warehouses every day. Items vary more than ever — different shapes, seasonal packaging, limited editions and constantly updated designs. At the same time, many logistics centers are dealing with labour shortages and rising pressure to automate.
But today’s image-recognition AI isn’t built for this level of change. Most systems rely on deep-learning models that need to be adjusted or retrained whenever new products appear. Every update — whether it’s a new item or a packaging change — adds extra time, energy use and operational cost. And for warehouses handling huge product catalogs, these retraining cycles can slow everything down.
KIOXIA, a company known for its memory and storage technologies, is working on a different approach. In a new collaboration with Tsubakimoto Chain and EAGLYS, the team has developed an AI-based image recognition system that is designed to adapt more easily as product lines grow and shift. The idea is to help logistics sites automatically identify items moving through their workflows without constantly reworking the core AI model.
At the center of the system is KIOXIA’s AiSAQ software paired with its Memory-Centric AI technology. Instead of retraining the model each time new products appear, the system stores new product data — images, labels and feature information — directly in high-capacity storage. This allows warehouses to add new items quickly without altering the original AI model.
Because storing more data can lead to longer search times, the system also indexes the stored product information and transfers the index into SSD storage. This makes it easier for the AI to retrieve relevant features fast, using a Retrieval-Augmented Generation–style method adapted for image recognition.
The collaboration will be showcased at the 2025 International Robot Exhibition in Tokyo. Visitors will see the system classify items in real time as they move along a conveyor, drawing on stored product features to identify them instantly. The demonstration aims to illustrate how logistics sites can handle continuously changing inventories with greater accuracy and reduced friction.
Overall, as logistics networks become increasingly busy and product lines evolve faster than ever, this memory-driven approach provides a practical way to keep automation adaptable and less fragile.