Google 用 Gemini 4 Argon 加速图挖掘与 TPU 内核开发
Google 图挖掘团队借 Gemini 4 Argon 与 Antigravity 的 Teamwork agent，把数月 RDMA 网络和 TPU 内核工作压缩到数小时，FarArray 提速最高 180 倍。
Today, we shared how Google’s Graph Mining and Graph Learning teams used Gemini 4 Argon with Teamwork agent in @GoogleAntigravity to solve a different class of internal engineering bottleneck: compressing months of low-level RDMA networking and custom TPU kernel development into hours. Specifically, improvements include accelerated graph algorithms with FarArray (up to 180x faster, 22x less RAM) and custom TPU kernels for Graph Neural Networks that run 8–15x faster than native JAX with massive HBM savings. For me, this update is a full-circle experience: Graph Mining contributed deeply to Gemini Data via deduping and data curation over time, and now Gemini is giving back by scaling and improving Graph Mining library! This is also a close collaboration amongst our Graph Mining and Teamwork teams, together with the Antigravity and Gemini teams. Congratulations! Read the full blog: https://antigravity.google/blog/gemini-4-argon-trillion-edge-graphs-and-tpu-kernels