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Friday, June 06, 2025

10 Possible "AI-Era Ciscos" (Infra Giants in the Making)

 


Here’s a list of 10 possible “Ciscos” for the emerging AI era — companies that are (or could be) to AI infrastructure what Cisco was to the Internet: the backbone builders, the connective tissue, the enablers of scale.

🧠 10 Possible "AI-Era Ciscos" (Infra Giants in the Making)

  1. NVIDIA
    Why: Already the GPU kingpin. But it's now expanding into networking (e.g., Mellanox), AI cloud infra, and full-stack AI systems. Becoming the "hardware+software fabric" of the AI age.

  2. TSMC
    Why: The invisible foundation of AI — fabs that make the chips. If NVIDIA is the architect, TSMC is the builder. As AI demand grows, TSMC becomes more geopolitically and economically critical.

  3. AMD
    Why: Rising challenger to NVIDIA, with competitive AI and data center chips (like MI300). May power alternative AI infrastructure providers looking to avoid Nvidia lock-in.

  4. Broadcom
    Why: Quietly dominates custom silicon, networking chips, and infrastructure software. Their tech powers AI data centers even if they’re not front-and-center.

  5. Arista Networks
    Why: Modern data center networking, low-latency fabrics, and AI cluster connectivity. Like Cisco in the 90s — building the roads for AI traffic.

  6. Lambda Labs
    Why: The "DIY NVIDIA stack" for startups and mid-size orgs. Affordable AI servers, cloud GPU access, and full-stack ML infra. Positioning itself as the dev-friendly infra layer.

  7. CoreWeave
    Why: Ex-GPU crypto miner turned AI cloud. One of the fastest-scaling alternatives to AWS for AI workloads. Building infra-as-a-service for inference and training at scale.

  8. Graphcore (or another chip startup)
    Why: Betting on novel compute paradigms. If they crack the "post-GPU" architecture (e.g., IPUs, TPUs), they could be the dark horse Cisco of new AI hardware.

  9. Celestial AI / Lightmatter / Ayar Labs
    Why: Optical and photonic interconnects — essential for scaling AI clusters beyond today's thermal/electrical limits. Could power the next-generation AI data highways.

  10. Anthropic / OpenAI Infra Division
    Why: Building internal, vertically integrated superclusters (custom racks, interconnects, scheduling). Their infra efforts may birth the AWS of AGI — or be spun out into infra-first giants.

🚀 Bonus Mentions

  • Amazon / Microsoft / Google (Infra Arms) – They’re still the cloud backbones, increasingly offering custom AI infra (e.g., Trainium, Azure Maia, Google TPUv5).

  • SiFive / RISC-V startups – Open hardware standards may drive new AI infra designed from the ground up.



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