ABSTRACT: The golden age of digital chips seems to be coming to an end. For decades, we have relied on making transistors smaller and increasing clock speeds to improve performance. However, when chip ...

Abstract: Model compression is widely adopted for edge inference of neural networks (NNs) to minimize both costly DRAM accesses and memory footprints. Recently, XOR-based model compression has ...

Skoltech scientists have devised a mathematical model of memory. By analyzing its new model, the team came to surprising conclusions that could prove useful for robot design, artificial intelligence, ...

I want to show you guys the basic stick figure I use to pose all my figures so that I can draw from memory without having to use any reference. It is really easy and simple to do and this is the first ...

In this updated tutorial, I walk you through the progress and new ideas behind my handmade photo journal. From binding techniques to decorative layouts, I share tips on how I’ve refined the design, ...

Model Context Protocol, or MCP, is arguably the most powerful innovation in AI integration to date, but sadly, its purpose and potential are largely misunderstood. So what's the best way to really ...

Summary: A new memory model called Input-Driven Plasticity (IDP) offers a more human-like explanation for how external stimuli help us retrieve memories, building on the foundations of the classic ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Transformer-based models have significantly advanced natural language processing (NLP), excelling in various tasks. However, they struggle with reasoning over long contexts, multi-step inference, and ...