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kevin deierling

T3 · host / generalist

Kevin Deierling leads NVIDIA's networking business and has been with the company for six years since Jensen Huang acquired his previous networking startup. He presented at COMPUTEX 2026 on extreme co-design across the AI factory stack.

1 call·1 name·100% bull·last heard 3 months ago·NVIDIA
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$NVDANvidiaposition

Nvidia SVP details extreme co-design moat delivering 10x tokens at one-tenth cost

Nvidia's full-stack extreme co-design across energy, chips, infrastructure, models, and applications creates a structural moat: 40% more GPUs per gigawatt via DSX power smoothing, 10x token throughput and 1/10th cost per token via Rubin/Vera/NVLink/Spectrum co-design, and new agentic memory architectures (CMX/STX) unlocking 5x faster inference.

NVIDIA2026-07episode →

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$NVDA
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Nvidia
HIGHkevin deierling·NVIDIA·3 months ago·COMPUTEX 2026 | NVIDIA Keynote | Extreme Co-Design: Building the AI Factory· position
Nvidia SVP details extreme co-design moat delivering 10x tokens at one-tenth cost
Nvidia's full-stack extreme co-design across energy, chips, infrastructure, models, and applications creates a structural moat: 40% more GPUs per gigawatt via DSX power smoothing, 10x token throughput and 1/10th cost per token via Rubin/Vera/NVLink/Spectrum co-design, and new agentic memory architectures (CMX/STX) unlocking 5x faster inference.
"This extreme co-design delivers 10x more tokens and one-tenth the cost per token by optimizing across this stack... As a result of all of this, with the excess, we can deploy 40%…"
2:40
9
AI Infrastructuretailwind
AI factories replace data centers as token revenue generators requiring full-stack co-design
Data centers are being re-architected from cost centers into 'AI factories' that generate tokens as revenue; this requires extreme co-design across energy, chips, infrastructure, models, and applications to maximize tokens per watt and tokens per dollar.
9
AI Hardware & Chip Architecturetailwind
Seven co-designed chips (Rubin, Vera, NVLink, Spectrum, ConnectX, BlueField, CPO) act as one system to beat copper distance limits
Single-chip design is insufficient; Nvidia co-designs seven chips together with cache-coherent links (NVLink 72), scale-out fabric (Spectrum-6), and co-packaged optics (Spectrum CPO) to overcome copper's distance limits, saving tens of megawatts per factory that convert directly to more token revenue.
9
AI Agentstailwind
Agentic loops create exponential token demand, requiring purpose-built CPU (Vera) and storage architectures
Agents close the prompt loop autonomously, generating 100x more internal tokens per output token; this demands CPUs built for planning/tool use (Vera), accelerated libraries (CUDA-X), and new memory hierarchies, making agentic infrastructure a distinct investment vector.
8
Grid & Power Infrastructuretailwind
DSX power smoothing enables 40% more GPU density per gigawatt by flattening training power spikes
AI training creates rainfall-like power spikes that stress grid transformers; Nvidia's DSX system stores excess energy during low-demand phases and releases it during peaks, flattening the curve and unlocking 40% more GPU deployments per gigawatt of delivered power.
8
Networking & Optical Infrastructuretailwind
Co-packaged optics (Spectrum CPO) eliminates PCB signal degradation, saving tens of megawatts per AI factory
Running electrical signals across PCBs to front-panel optics degrades signal integrity; placing optics directly next to the ASIC inside the package preserves signal quality and cuts power dramatically, freeing megawatts for additional GPU compute.
8
Memory & Storagetailwind
New agentic memory tier (CMX for KV cache, STX for vector/object storage) delivers 5x inference throughput
AI agents require short-term KV cache and long-term vector/object memory distinct from traditional DRAM; Nvidia's CMX/STX reference architecture accelerates prefill/decode and tool use, yielding 5x faster token throughput and 5x better efficiency for agentic workloads.