Roadmap for AI HW Development, With The Role of Photonic Chips In Supporting Future LLMs (CUHK, NUS, UIUC, Berkeley)


A new technical paper titled "What Is Next for LLMs? Next-Generation AI Computing Hardware Using Photonic Chips" was published by researchers at The Chinese University of Hong Kong, National University of Singapore, University of Illinois Urbana-Champaign and UC Berkeley. Abstract "Large language models (LLMs) are rapidly pushing the limits of contemporary computing hardware. For example, t... » read more

2D materials–based homogeneous transistor-memory architecture for neuromorphic hardware


Abstract "In neuromorphic hardware, peripheral circuits and memories based on heterogeneous devices are generally physically separated. Thus exploring homogeneous devices for these components is an important issue for improving module integration and resistance matching. Inspired by ferroelectric proximity effect on two-dimensional materials, we present a tungsten diselenide-on-LiNbO3 cascaded... » read more