According to @sundarpichai, Google has announced the 7th-generation TPU, named 'Ironwood', at the #GoogleCloudNext event in Las Vegas. This new TPU is designed specifically for inference tasks, boasting a 3,600x performance increase and a 29x efficiency boost compared to the first Cloud TPU. The release is expected later this year, which could potentially impact AI-related cryptocurrency projects relying on cloud computing efficiency.

According to DeepSeek, the NSA (Natively Trainable Sparse Attention) mechanism is designed to improve ultra-fast long-context training and inference capabilities through dynamic hierarchical sparse strategy, coarse-grained token compression, and fine-grained token selection, potentially enhancing trading algorithms by increasing processing efficiency and reducing computational load.

According to Paolo Ardoino, the future of AI model training will not rely on the brute force of 1 million GPUs. Instead, the development of better models will significantly reduce training costs, emphasizing that access to data will remain crucial. Ardoino suggests that inference will move to local or edge computing, making the current expenditure on brute force methods seem inefficient in hindsight.