Through 2024 and into mid-2025, the conventional narrative was that Apple was losing the AI race. Siri delays, no proprietary ...

Admittedly it's an oversimplified description, but the economics of AI inference at scale are deceptively simple. The more ...

Berlin Coyotiv and OpenServ Labs published a research paper introducing BRAID (Bounded Reasoning for Autonomous ...

A research team from the Shenyang Institute of Automation, Chinese Academy of Sciences, together with Peking University and collaborating ...

Memori Labs is the creator of the leading SQL-native memory layer for AI applications. Its open-source repository is one of the top-ranked memory systems on GitHub, with rapidly expanding developer ...

End-to-End Hardware-Driven Graph Preprocessing for Enhanced GNN Performance” was published by researchers at KAIST, Panmnesia ...

EnterpriseWeb, a deep-tech software company which offers a no-code platform for contextual automation, is collaborating with ...

Many AI stocks haven't done well so far in 2026.

Shakti P. Singh, Principal Engineer at Intuit and former OCI model inference lead, specializing in scalable AI systems and LLM inference. Generative models are rapidly making inroads into enterprise ...

President Trump’s trade policy, inflation and climbing stock prices shaped business and the economy this year. By Christine Zhang In recent years, macroeconomic tides have ebbed and flowed, but one ...

Not only are GPUs expensive, they are also too often idle. Bursty machine learning (ML) inference requests leave gaps in time. Even when jobs are busy, they may be compute- or memory-bound, leaving ...

Google expects an explosion in demand for AI inference computing capacity. The company's new Ironwood TPUs are designed to be fast and efficient for AI inference workloads. With a decade of AI chip ...