NVIDIA has introduced the Ising Decoder ColorCode 1 Fast, designed to accelerate and improve the Logical Error Rate (LER) of color code decoders, enabling more than 347.7x better LER and 7.3x faster runtime compared with the state of the art color code decoder Chromobius for d=31 and physical error rate of 0.3%. Color codes, a type of topological code, require more physical qubits for memory than surface codes to achieve the same target logical failure rate but can perform logical gates more efficiently due to their ability to do all Clifford gates transversally and simpler lattice surgery operations. Historically, color codes were shelved due to a lack of fast and accurate decoders. Using the Ising Decoding training pipeline, QPU builders, operators, and decoder developers can train small 3D Convolutional Neural Network (CNN) AI-based pre-decoders designed for triangular Color Codes, which accelerate and improve decoder accuracy by handling localized error syndromes and can scale to arbitrary code distances.