It’s still frothy in AI, but memory chips are now the bottleneck

Fei-Fei Li also just raised a billion dollars for her World Labs, though it’s much further along with its physical AI models ...

Why T-shaped knowledge is becoming more important than ever in the age of AI

AI tools are fundamentally changing software development. Investing in foundational knowledge and deep expertise secures your career long-term.

Azul 2026 State of Java Survey & Report: 62% of Enterprises Now Leverage Java to Power AI Functionality, 41% Rely on High-Performance Java Platforms to Reduce Cloud Compute Costs

Azul, the only company 100% focused on Java, today announced the results of its 2026 State of Java Survey & Report. The annual study, based on responses from more than 2,000 Java professionals ...
IEEE

DeepTM: Efficient Tensor Management in Heterogeneous Memory for DNN Training

Abstract: Deep Neural Networks (DNNs) have gained widespread adoption in diverse fields, including image classification, object detection, and natural language processing. However, training ...
CNBC

Memory chip shortage to last through 2027, semiconductor boss says

Memory chips are a key component of artificial intelligence data centers. The boom in AI data center construction has caused a shortage of semiconductors, which are also crucial for electronics like ...
CNBC

AI memory is sold out, causing an unprecedented surge in prices

This year, there won't be enough memory to meet worldwide demand because powerful AI chips made by the likes of Nvidia, AMD and Google need so much of it. Prices for computer memory, or RAM, are ...
Hacker

Reading 1 Million+ Row Excel Files in Java Without Killing Your Memory: Meet Sjxlsx

Healthcare Architect. Develop applications in C#.Net. Java , Python ,Typescript & SQL in both cloud native and on Prem servers. Healthcare Architect. Develop applications in C#.Net. Java , Python ...
IEEE

Efficient KV Cache Spillover Management on Memory-Constrained GPU for LLM Inference

Abstract: The rapid growth of model parameters presents a significant challenge when deploying large generative models on GPU. Existing LLM runtime memory management solutions tend to maximize batch ...