Embedded Computing Design

Transistors are the lifeblood of modern technology, fueling data transmission and storage worldwide. Experts have continuously refined these mechanisms, and they are essential components in various industries, including aerospace, defense and transportation.

Recent studies demonstrate how engineers might be entering a new age of transistors with memory-retention capabilities.

Natural language processing (NLP) is a powerful artificial intelligence (AI) application. It supports next-generation chatbots like ChatGPT, making advanced machine-learning capabilities accessible to the general public. However, training NLP models can be challenging.

Large language models (LLMs) are some of today’s most impactful technologies. They’re what make advanced chatbots and generative AI possible, but as their functionality grows, so too do their costs and complexity. A new framework from Stanford researchers could change that.