Who makes fpgas for AI data centers

FPGAs are reconfigurable logic chips that pick up work a fixed-function accelerator design doesn't fit well: certain inference workloads, custom networking functions that sit near the NIC and DPU layer (NICs / SuperNICs, DPUs), and test and bring-up tasks used across the semiconductor supply chain (Semiconductor test & burn-in) as new AI silicon comes online. They're a smaller, more specialized category than the GPU and ASIC accelerators that dominate the layer, and one where volume is driven by breadth of use case rather than by cluster-wide compute scaling. Investor exposure is concentrated in a small number of vendors, and the category's growth is tied less to overall AI buildout volume than to how many distinct niches — inference offload, networking, test — continue to favor reconfigurable logic over a purpose-built ASIC. That makes it a steadier, lower-beta way to have AI exposure within compute silicon than the accelerator vendors themselves, at the cost of a smaller addressable opportunity.