The latest release, the sixth-generation Trillium TPU, was announced in October and offers substantial performance boosts in AI training and inference throughput compared to its predecessor. These chips also support larger language models and a broader range of model architectures. Producing in-house AI chips allows Google to reduce its reliance on Nvidia, which currently dominates the AI chip market. TPUs are used in Google’s data centers for scalable machine-learning tasks and are available in a compact version for edge computing, bringing AI capabilities to devices like smartphones and IoT applications.
Key takeaways:
- Google is reportedly partnering with MediaTek for the production of next-generation tensor processing units (TPUs).
- MediaTek may handle input/output modules for the new TPUs, while Google continues its relationship with Broadcom for current TPU production.
- Google's TPUs are specialized for machine learning tasks, offering significant performance and energy efficiency improvements over traditional processors.
- The latest Trillium TPU offers substantial performance boosts and supports larger language models, providing an alternative to Nvidia's GPUs.