Edge-AI Hardware for Extended Reality


New technical paper titled "Memory-Oriented Design-Space Exploration of Edge-AI Hardware for XR Applications" from researchers at Indian Institute of Technology Delhi and Reality Labs Research, Meta. Abstract "Low-Power Edge-AI capabilities are essential for on-device extended reality (XR) applications to support the vision of Metaverse. In this work, we investigate two representative XR w... » read more

Using AI To Speed Up Edge Computing


AI is being designed into a growing number of chips and systems at the edge, where it is being used to speed up the processing of massive amounts of data, and to reduce power by partitioning and prioritization. That, in turn, allows systems to act upon that data more rapidly. Processing data at the edge rather than in the cloud provides a number of well-documented benefits. Because the physi... » read more

MIPI In Next Generation Of AI IoT Devices At The Edge


The history of data processing begins in the 1960’s with centralized on-site mainframes that later evolved into distributed client servers. In the beginning of this century, centralized cloud computing became attractive and began to gain momentum becoming one of the most popular computing tools today. In recent years however, we have seen an increase in the demand for processing... » read more

“All-in-One” 8×8 Array of Low-Power & Bio-inspired Crypto Engines w/IoT Edge Sensors Based on 2D Memtransistors


New technical paper titled "All-in-one, bio-inspired, and low-power crypto engines for near-sensor security based on two-dimensional memtransistors" from researchers at Penn State University. Abstract: "In the emerging era of the internet of things (IoT), ubiquitous sensors continuously collect, consume, store, and communicate a huge volume of information which is becoming increasingly vuln... » read more

The Role Of AI And Endpoint Real-Time Data Analytics


The Internet of Things (IoT) has the capability of amassing large amounts of data which it does with the help of dispersed intelligent sensors. The organization and distribution of this enormous amount of data is posing a challenge. While conventional methods of data analysis have facilitated the operations in IoT, artificial intelligence (AI) has proven that it can do it with greater precision... » read more

MIT: Stackable AI Chip With Lego-style Design


New technical paper titled "Reconfigurable heterogeneous integration using stackable chips with embedded artificial intelligence" from researchers at MIT, along with Harvard University, Tsinghua University, Zhejiang University, and others. Partial Abstract: "Here we report stackable hetero-integrated chips that use optoelectronic device arrays for chip-to-chip communication and neuromorphic... » read more

Chip Substitutions Raising Security Concerns


Substituting chips is becoming more common in the electronics industry as shortages drag on, allowing systems vendors to continue selling everything from cars to manufacturing equipment and printer cartridges without waiting for a commoditized part. But substitutions aren't always an even swap, and they increase security risks in ways that may take years to show up or fully understand. So fa... » read more

There Is Plenty Of Room At The Top: Imagining Miniaturized Electro-Mechanical Switches In Low-Power Computing Applications


The first computers were built using electro-mechanical components, unlike today’s modern electronic systems. Alan Turing’s cryptanalysis multiplier and Konrad Zuse’s Z2 were invented and built in the first half of the 20th century, and were among the first computers ever constructed. Electro-mechanical switches and relays performed logic operations in these machines. Even after computers... » read more

Analog Edge Inference with ReRAM


Abstract "As the demands of big data applications and deep learning continue to rise, the industry is increasingly looking to artificial intelligence (AI) accelerators. Analog in-memory computing (AiMC) with emerging nonvolatile devices enable good hardware solutions, due to its high energy efficiency in accelerating the multiply-and-accumulation (MAC) operation. Herein, an Applied Materials... » read more

HD Map (EdgeMap) Crowdsources Data From Connected Vehicles in Auto Edge Computing


New research paper from University of Nebraska-Lincoln, Xidian University and University of North Carolina at Charlotte. Abstract "High definition (HD) map needs to be updated frequently to capture road changes, which is constrained by limited specialized collection vehicles. To maintain an up-to-date map, we explore crowdsourcing data from connected vehicles. Updating the map collaborati... » read more

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