Kog is going deeper to squeeze more inference out of GPUs

A French startup is developing software that optimizes how standard datacenter GPUs perform AI inference, the process of running trained AI models to generate outputs. The startup demonstrated that conventional GPUs already owned by enterprises can achieve significantly faster inference speeds through software improvements, rather than requiring specialized hardware. This matters because inference speed and cost have become critical bottlenecks in AI deployment, and faster inference could unlock value for customers currently delayed by slow processing times. The startup's approach requires deep technical work on each GPU model, which limits how many chips it can support, though it plans to eventually use automated methods to expand compatibility.