Abstract: In the context of the big data era, the extensive penetration of the Internet and the rapid development of database technology have led to an explosive growth in the amount of data generated ...

Mecum's Kissimmee 2026 auction saw more than a dozen Hemi-equipped Mopars go under the hammer. The most anticipated car, a 1971 Plymouth Hemi Cuda Convertible, just changed hands for a whopping $3.3 ...

AMD is hoping to win over artificial intelligence (AI) developers in Asia-Pacific with its open software ecosystem and help the region compete on a global stage without relying on proprietary AI ...

Nov 25 (Reuters) - Meta Platforms (META.O), opens new tab is in talks with Google to spend billions of dollars on the Alphabet (GOOGL.O), opens new tab-owned company's chips for use in its data ...

The golden-era muscle cars are primarily famous for their powerful engines. But some of them stand out through other features as well. The Mopars, for instance, were available in a few flashy colors ...

If you've been around the automotive side of the internet for any length of time, you've likely heard rumors that Chrysler (now Stellantis) is going to revive the Plymouth Barracuda, which ended ...

Hello! I am the CUDA Python tech lead and I'm filing this RFC to improve the interoperability between Python GPU libraries. For existing Python projects such as PyTorch, transitioning to cuda.core may ...

Dawning Information Industry Co. (Sugon) has partnered with more than 20 Chinese firms across AI chips, large models, and system integration to roll out a new open AI computing architecture. The ...

Reproducibility is the backbone of credible AI development. Without it, scientific claims or production ML models cannot be verified, audited, or reliably transferred between environments. AI/ML ...

For many years, CuPy has been the one-stop shop for using NVIDIA CUDA GPUs in Python. It provides many functionalities, way beyond what’s publicly known (“NumPy/SciPy for GPUs”), for example Python ...

NVIDIA introduces cuda.cccl, bridging the gap for Python developers by providing essential building blocks for CUDA kernel fusion, enhancing performance across GPU architectures. NVIDIA has unveiled a ...

Why it matters: Nvidia introduced CUDA in 2006 as a proprietary API and software layer that eventually became the key to unlocking the immense parallel computing power of GPUs. CUDA plays a major role ...