Indian IT services firm Tata Consultancy Services (TCS) has secured a $1 billion investment from private‑equity firm TPG as part of a multi‑year, $2 billion plan to build a network of gigawatt‑scale AI data centers across India. Dubbed “HyperVault,” the project will use liquid‑cooled, high‑density designs to meet the soaring demand for AI compute power. The initiative arrives amid a stark supply‑demand gap in the country, where data generation is high but data‑center capacity remains low. TCS aims to partner with hyperscalers and AI firms to develop the infrastructure needed for advanced AI workloads. Read more →

The surge in AI workloads is driving rapid expansion of data centers that rely heavily on GPUs, which consume far more power and generate far more heat than traditional CPUs. This growth is straining electricity supplies and dramatically increasing water use for cooling. Industry leaders are exploring liquid‑cooling, micro‑fluidic chips, free‑cooling, and geothermal options, while experts call for greater transparency, smarter hardware design, and more efficient model use to curb the environmental impact. Read more →

Google introduced its seventh‑generation Tensor Processing Unit, dubbed Ironwood, at a recent Hot Chips event. The dual‑die chip delivers 4,614 TFLOPs of FP8 performance and pairs each die with eight stacks of HBM3e, providing 192 GB of memory per chip. When scaled to a 9,216‑chip pod, the system reaches 1.77 PB of directly addressable memory—the largest shared‑memory configuration ever recorded for a supercomputer. The architecture includes advanced reliability features, liquid‑cooling infrastructure, and AI‑assisted design optimizations, and is already being deployed in Google Cloud data centers for large‑scale inference workloads. Read more →

Google introduced its seventh‑generation Tensor Processing Unit, dubbed Ironwood, at a recent Hot Chips event. The dual‑die chip delivers 4,614 TFLOPs of FP8 performance and pairs each die with eight stacks of HBM3e, providing 192 GB of memory per chip. When scaled to a 9,216‑chip pod, the system reaches 1.77 PB of directly addressable memory—the largest shared‑memory configuration ever recorded for a supercomputer. The architecture includes advanced reliability features, liquid‑cooling infrastructure, and AI‑assisted design optimizations, and is already being deployed in Google Cloud data centers for large‑scale inference workloads. Read more →

Google introduced its seventh‑generation Tensor Processing Unit, dubbed Ironwood, at a recent Hot Chips event. The dual‑die chip delivers 4,614 TFLOPs of FP8 performance and pairs each die with eight stacks of HBM3e, providing 192 GB of memory per chip. When scaled to a 9,216‑chip pod, the system reaches 1.77 PB of directly addressable memory—the largest shared‑memory configuration ever recorded for a supercomputer. The architecture includes advanced reliability features, liquid‑cooling infrastructure, and AI‑assisted design optimizations, and is already being deployed in Google Cloud data centers for large‑scale inference workloads. Read more →

Google introduced its seventh‑generation Tensor Processing Unit, dubbed Ironwood, at a recent Hot Chips event. The dual‑die chip delivers 4,614 TFLOPs of FP8 performance and pairs each die with eight stacks of HBM3e, providing 192 GB of memory per chip. When scaled to a 9,216‑chip pod, the system reaches 1.77 PB of directly addressable memory—the largest shared‑memory configuration ever recorded for a supercomputer. The architecture includes advanced reliability features, liquid‑cooling infrastructure, and AI‑assisted design optimizations, and is already being deployed in Google Cloud data centers for large‑scale inference workloads. Read more →

Google introduced its seventh‑generation Tensor Processing Unit, dubbed Ironwood, at a recent Hot Chips event. The dual‑die chip delivers 4,614 TFLOPs of FP8 performance and pairs each die with eight stacks of HBM3e, providing 192 GB of memory per chip. When scaled to a 9,216‑chip pod, the system reaches 1.77 PB of directly addressable memory—the largest shared‑memory configuration ever recorded for a supercomputer. The architecture includes advanced reliability features, liquid‑cooling infrastructure, and AI‑assisted design optimizations, and is already being deployed in Google Cloud data centers for large‑scale inference workloads. Read more →