For more than three decades, modern CPUs have relied on speculative execution to keep pipelines full. When it emerged in the 1990s, speculation was hailed as a breakthrough — just as pipelining and ...

High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...

A cycle-accurate alternative to speculation — unifying scalar, vector and matrix compute In dynamic execution, processors speculate about future instructions, dispatch work out of order and roll back ...

import torch @torch.compile(backend="inductor") def fn(src, index, base_tensor): src = src + 10 torch.use_deterministic_algorithms(True) base_tensor.scatter_(0, index ...

Differential privacy (DP) stands as the gold standard for protecting user information in large-scale machine learning and data analytics. A critical task within DP is partition selection—the process ...

Eggplant seed vigor is a crucial indicator of its germination rate and seedling growth quality. In response to the need for efficient and nondestructive assessment methods, this study explores the use ...

Google’s DeepMind research division claims its newest AI agent marks a significant step toward using the technology to tackle big problems in math and science. The system, known as AlphaEvolve, is ...