AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Qualcomm confirmed a $3.92 billion all-stock deal to buy AI software startup Modular, paired with a Meta Platforms CPU ...

Every Python developer knows some or all of these libraries, because they’re stable, reliable, and excellent at what they do.

For three years the AI boom ran on capability claims and vibes. This year it runs on invoices. An inference platform most ...

Abstract: Algorithmic text summarization task in natural language processing aims to represent a given text in a shorter and suitable form for a human reader by locating sentences of interest while ...

Wiki-CS is a Wikipedia-based dataset for benchmarking Graph Neural Networks. This repository contains the dataset files, the data pipeline used to create it as well as experiments performed to ...

Abstract: Graph Neural Networks (GNNs) enable effective machine learning on graph-structured data, but their performance and scalability are often limited by the irregular structure and large size of ...

Generative AI and Recurrent Networks run on Q.ANT's Second-Generation Photonic Processor Complexity Model Graph Climbing the complexity ladder of AI Models Second Generation NPU Q.ANT Native ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...