As AI systems push relentlessly toward higher bandwidth, denser packaging, and tighter power and signal margins, the weakest link is no longer just silicon—it’s validation at scale. At DesignCon 2026, Keysight Technologies (NYSE: KEYS) is positioning itself squarely at that inflection point, unveiling a full-stack portfolio aimed at one goal: making sure AI hardware actually works when it leaves the lab.
From February 24–26 at the Santa Clara Convention Center, Keysight will use its booth (No. 1039) to demonstrate how engineers can design, validate, and scale AI systems across the entire signal chain. The showcase spans advanced packaging, chiplets, memory, PCIe®, USB4, and emerging 1.6T AI fabrics, culminating in live interconnect benchmarking that reflects real-world system loads—not idealized simulations.
In an era where AI infrastructure failures can cost millions in downtime and redesigns, Keysight’s message is blunt: validate earlier, validate deeper, and validate at system scale.
From Chiplets to Systems: Why End-to-End Validation Matters Now
AI hardware design has become a game of compounding complexity. Chiplets replace monolithic dies. Advanced 3D packaging introduces new thermal and signal integrity risks. Memory subsystems strain under AI workloads. Interconnects race toward terabit-class speeds.
What used to be discrete validation problems now collide at the system level.
Keysight’s DesignCon presence reflects that shift. Rather than focusing on individual components, the company is demonstrating continuous workflows—from early interconnect design through compliance, debug, and large-scale benchmarking.
That approach mirrors broader industry trends. Hyperscalers and AI infrastructure vendors are increasingly demanding system-level confidence, not just standards compliance. Passing a spec test is table stakes; proving performance under AI traffic is the real differentiator.
Accelerating Chiplet and 3D IC Design
One of the first stops in Keysight’s demo lineup tackles a foundational challenge in modern AI silicon: multi-die integration.
The Chiplet 3D Interconnect Designer showcases a workflow for accelerating chiplet and 3D IC interconnect development. As AI accelerators grow more modular, engineers must manage complex interactions across dies, substrates, and vertical interconnects—often before physical prototypes exist.
Keysight’s approach emphasizes early visibility into signal integrity, power delivery, and packaging constraints, helping teams avoid costly late-stage redesigns. For AI and HPC devices, where time-to-market pressure is extreme, that early de-risking can be the difference between shipping on schedule or slipping quarters.
Signal Integrity at 3.2T: Living at the Physical Limits
As interconnect speeds approach multi-terabit territory, signal integrity stops being an abstract concern and becomes a hard physical ceiling.
Keysight’s Signal Integrity at 3.2T Speeds demo pairs the PLTS2026 Physical Layer Test System with the NA5307A Frequency Extender, pushing measurements out to 250 GHz. The setup highlights the bandwidth and accuracy required to validate next-generation infrastructure—where even minor distortions can collapse link margins.
This is less about headline speeds and more about confidence. AI infrastructure vendors increasingly need proof that their designs will behave predictably across temperature, process variation, and deployment environments. Keysight is betting that ultra-high-frequency measurement will move from niche research labs into mainstream validation pipelines.
Memory Validation for AI Workloads, Not Just Specs
Memory is one of the quiet bottlenecks in AI systems. Bandwidth, latency, and signal integrity directly affect model training and inference throughput, yet validation often lags real-world usage.
Keysight’s Next Generation Memory Validation demos focus on closing that gap. The lineup includes:
- A live DDR5 system for mainstream electrical validation
- A GDDR7 PAM3 signal integrity setup, using a new SNDR and jitter measurement suite
The emphasis here is on debug and compliance under AI-relevant conditions, not just theoretical limits. As AI accelerators increasingly rely on high-speed graphics and HBM-adjacent memory technologies, these measurement capabilities become critical for avoiding subtle errors that only appear under sustained load.
PCIe® 7.0 and the PAM4 Reality Check
PCIe® remains the backbone of AI system connectivity, and with PCIe 7.0, the margin for error shrinks even further.
Keysight’s Reliable PCIe PAM4 Performance demo showcases its next-generation PCIe test solutions across both the PHY and protocol layers. Using the UXR-Series oscilloscope, M8050A BERT platform, and PCIe test software, the demo illustrates how engineers can:
- Accelerate debug cycles
- Improve margin analysis
- Enhance long-term link reliability
This matters because PCIe failures don’t always announce themselves loudly. Intermittent errors can degrade AI workloads silently, undermining performance guarantees. Keysight’s pitch is clear: visibility across layers is no longer optional.
448 Gbps Pathfinding: Exploring the Modulation Frontier
As signaling speeds climb, the industry is experimenting beyond PAM4. Keysight’s 448 Gbps Pathfinding demo leans into that uncertainty.
By combining the M8199B arbitrary waveform generator with the N1046A electrical channel module, Keysight enables researchers to generate and analyze PAM4, PAM6, and PAM8 signals. The goal isn’t to crown a winner, but to give engineers tools to evaluate trade-offs between complexity, power, and resilience.
For next-generation AI interconnects, these decisions will shape architectures years before standards solidify. Keysight is positioning itself as the experimentation platform where those decisions get tested, not guessed.
1.6T Interconnects: Where AI Networks Are Headed
The climax of Keysight’s DesignCon story is 1.6T interconnect benchmarking—a speed class that’s quickly moving from roadmap to requirement in AI data centers.
The INPT-1600GE benchtop test system demo shows how engineers can:
- Validate bit error rate (BER) and FEC
- Measure end-to-end link quality
- Benchmark AI workloads over emerging fabrics
This is where compliance meets reality. At these speeds, lab conditions rarely resemble production deployments. Keysight’s focus on workload-aware benchmarking reflects a growing industry demand: proof that AI networks won’t crumble under real traffic.
UALink and Scale-Up Ethernet: Governing AI Fabrics
Beyond raw speed, AI infrastructure needs repeatable validation and automation. Keysight’s demos around UALink and Scale-Up Ethernet highlight automated test workflows for 1.6T-class electrical interfaces, including expanded measurement coverage and streamlined calibration.
As AI clusters scale, manual validation becomes a liability. Automation, observability, and policy-driven testing are increasingly essential—not just for hyperscalers, but for enterprises building private AI infrastructure.
Education as a Strategy, Not an Afterthought
Keysight isn’t limiting its presence to the show floor. The company will participate in 16 paper, panel, and tutorial presentations, plus nine talks via the Keysight Educational Forum on February 25 in the Great America K Ballroom.
That level of engagement underscores a broader strategy: shaping how the industry understands—and approaches—the physical realities of AI system design.
The Bigger Picture
DesignCon 2026 arrives at a moment when AI ambition is colliding with physical constraints. Faster silicon alone won’t carry the next wave of AI innovation. Validation, measurement, and system-level confidence will.
Keysight’s message is subtle but firm: the future of AI hardware won’t be won by who builds the fastest component, but by who can prove—early and often—that everything works together at scale.
For engineers racing toward terabit-class AI systems, that may be the most important demo of all.
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