Optimizing AI Efficiency from Silicon to Model

We are entering an inference age, driven by the growing role of agentic AI, test-time compute, and post-training, making compute efficiency increasingly critical. Furiosa’s Tensor Contraction Processor (TCP) architecture and co-designed hardware-software stack maximize utilization across layers, from transformer-based models to multimodal inference, enabling large-scale LLMs and generative AI workloads to run with greater efficiency and performance.