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This chart explains why a handful of unknown chip suppliers could be the real winners of the AI boom (Save this). This table breaks down how much optical networking gear each Nvidia GPU needs, comparing today's systems to the next generation Feynman chips coming down the pipe. Every GPU in a cluster needs to constantly send data to every other GPU, and that requires physical hardware called optical engines, basically tiny devices that convert electrical signals into light so data can move fast enough between chips. In today's system, each GPU only needs 2 of these optical engines, but in the most advanced Feynman setup, that jumps to 70 optical engines per GPU, a 35x increase in hardware needed for the exact same basic job. This is happening because Nvidia is cramming way more GPUs into a single connected cluster, going from 72 GPUs today up to 1,152 GPUs in Feynman systems and all those chips need to talk to each other twice as fast, jumping from 1.6 terabits per second up to 3.2 terabits per second. To handle that much data without needing a mountain of cables, Nvidia is moving toward something called co-packaged optics, or CPO which glues the optical hardware directly onto the chip package instead of plugging it in separately and that one shift alone pushes the total optical hardware per cluster from 144 units today to over 80,000 units in the most advanced setup. Now here is some of the stocks that can benefit from this. Nvidia benefits the most obviously, since it controls this entire roadmap and captures more revenue per system as the hardware gets more complex. Broadcom is one of the only companies that actually makes the specialized chips needed for co-packaged optics, so every step toward CPO adoption means more silicon Broadcom can sell into each rack. Coherent and Lumentum make the actual lasers and light components that go inside these optical engines, and demand for their parts scales directly with that jump from 144 to 80,000 units per cluster. Credo Technology and Marvell supply the chips that clean up and boost these ultra-fast signals, and the table's jump from 100 Gb/s to 200 Gb/s and eventually 400 Gb/s speeds plays right into what they build. Fabrinet builds and assembles optical modules for major networking companies, meaning it captures manufacturing revenue as optical engine volumes scale into the tens of thousands per cluster. Ciena makes optical networking systems and increasingly supplies components used in data center interconnects, positioning it to benefit as bandwidth requirements double. Celestica has become a key manufacturing partner for hyperscalers building custom networking gear, riding the same wave of rack complexity. Bullish on co-packaged optics, make sure to follow @MelvinInvests for more AI infrastructure insights and check out the link below for more details.