Semiconductor Engineering

Enhancing Silicon Reliability With In-System Test And SLM Data

A convergence of DFT techniques and the proliferation of in-silicon monitors can flag potential failures before they occur.
InfoQ

Pinterest Reduces Spark OOM Failures by 96% Through Auto Memory Retries

Pinterest Engineering cut Apache Spark out-of-memory failures by 96% using improved observability, configuration tuning, and ...
Security Boulevard

Everything I Learned About Harness Engineering and AI Factories in San Francisco (April 2026)

I spent the last week of March 2026 in San Francisco talking to CTOs, CPOs, and engineering leaders from companies of every ...
VentureBeat

Google PM open-sources Always On Memory Agent, ditching vector databases for LLM-driven persistent memory

Google senior AI product manager Shubham Saboo has turned one of the thorniest problems in agent design into an open-source engineering exercise: persistent memory. This week, he published an ...
sei.cmu

Temporal Memory Safety in C and C++: An AI-Enhanced Pointer Ownership Model

This podcast explores updates to the Pointer Ownership Model for C, a modeling framework designed to improve the ability of developers to statically analyze C programs for errors involving temporal ...
SDxCentral

The 5 unlikely winners of the memory chip shortage

The intensifying memory shortage already has its winners. SK Hynix has raised its prices by as much as 70% compared to the final quarter of 2025. Micron has moved away from the consumer sector to ...
CIO Dive

Best performance and fastest memory with the new Amazon EC2 R8i and R8i-flex instances

Today, we’re announcing general availability of the new eighth generation, memory optimized Amazon Elastic Compute Cloud (Amazon EC2) R8i and R8i-flex instances powered by custom Intel Xeon 6 ...
blockchain

ChatGPT Memory Architecture: Four-Layer Context System Prioritizes Speed Over RAG and Vector Databases

According to @godofprompt, after reverse-engineering ChatGPT's memory architecture, it was revealed that the platform does not use sophisticated RAG (Retrieval-Augmented Generation) systems or vector ...
InfoWorld

AI memory is really a database problem

If we want to avoid making AI agents a huge new attack surface, we’ve got to treat agent memory the way we treat databases: with firewalls, audits, and access privileges. The pace at which large ...
Hacker

Vector Databases Aren’t Enough: Why AI Needs Multi-Modal Memory Architectures

Cloud Architect at Amazon Web Services (AWS) specializing in cloud-native development, AI/ML, serverless compute, and event-driven architecture. Cloud Architect at Amazon Web Services (AWS) ...
IEEE

PimBeam: Efficient Regular Path Queries Over Graph Database Using Processing-in-Memory

Abstract: Regular path queries (RPQs) in graph databases are bottlenecked by the memory wall. Emerging processing-in-memory (PIM) technologies offer a promising solution to dispatch and execute path ...
marktechpost

A Coding Implementation to Build Neural Memory Agents with Differentiable Memory, Meta-Learning, and Experience Replay for Continual Adaptation in Dynamic Environments

In this tutorial, we explore how neural memory agents can learn continuously without forgetting past experiences. We design a memory-augmented neural network that integrates a Differentiable Neural ...