The quantum many body problem has been at the heart of much of theoretical and experimental physics over the past few decades ...

Abstract: We propose an efficient quantum subroutine for matrix multiplication that computes a state vector encoding the entries of the product of two matrices in superposition. The subroutine ...

India’s evolving AI landscape still relies largely on GPUs, though the rise of TPU could unfold a huge opportunity for Indian ...

Google’s in-house Tensor chips from the beginning have faced criticism for not offering solid performance. While they are excellent for everyday tasks, the performance gap is pretty significant when ...

This week at the AI Infra Summit, the RISC-V chip designer revealed its second generation of Intelligence cores, including ...

Google’s in-house Tensor chips have steadily improved over the years to become a reliable daily driver with solid battery efficiency. Still, performance has often been a sticking point. While previous ...

NotImplementedError: Cannot copy out of meta tensor; no data! Please use torch.nn.Module.to_empty() instead of torch.nn.Module.to() when moving module from meta to a different device.

Abstract: Since 2017, NVIDIA GPUs have been equipped with specialized units known as Tensor Cores, which demonstrate remarkable efficiency in processing matrix multiplications (GEMMs). Beyond GEMMs, ...

Qiskit addons are a collection of modular tools for building utility-scale workloads powered by Qiskit. This addon enables a Qiskit user to perform approximate quantum compilation using tensor ...

Google’s Tensor reboot of the Pixel lineup has never been about adding more power, but rather about creating an experience tailored to what Google wants your phone to be. With the Pixel 10, Tensor G5 ...