MCU Changes At The Edge


Microcontrollers are becoming a key platform for processing machine learning at the edge due to two significant changes. First, they now can include multiple cores, including some for high performance and others for low power, as well as other specialized processing elements such as neural network accelerators. Second, machine learning algorithms have been pruned to the point where inferencing ... » read more

Research Bits: May 28


Nanofluidic memristive neural networks Engineers from EPFL developed a functional nanofluidic memristive device that relies on ions, rather than electrons and holes, to compute and store data. “Memristors have already been used to build electronic neural networks, but our goal is to build a nanofluidic neural network that takes advantage of changes in ion concentrations, similar to living... » read more

High-Level Synthesis Propels Next-Gen AI Accelerators


Everything around you is getting smarter. Artificial intelligence is not just a data center application but will be deployed in all kinds of embedded systems that we interact with daily. We expect to talk to and gesture at them. We expect them to recognize and understand us. And we expect them to operate with just a little bit of common sense. This intelligence is making these systems not just ... » read more

Fundamental Issues In Computer Vision Still Unresolved


Given computer vision’s place as the cornerstone of an increasing number of applications from ADAS to medical diagnosis and robotics, it is critical that its weak points be mitigated, such as the ability to identify corner cases or if algorithms are trained on shallow datasets. While well-known bloopers are often the result of human decisions, there are also fundamental technical issues that ... » read more

Research Bits: April 30


Sound waves in optical neural networks Researchers from the Max Planck Institute for the Science of Light and Massachusetts Institute of Technology found a way to build reconfigurable recurrent operators based on sound waves for photonic machine learning. They used light to create temporary acoustic waves in an optical fiber, which manipulate subsequent computational steps of an optical rec... » read more

In-Memory Computing: Techniques for Error Detection and Correction


A new technical paper titled "Error Detection and Correction Codes for Safe In-Memory Computations" was published by researchers at Robert Bosch, Forschungszentrum Julich, and Newcastle University. Abstract "In-Memory Computing (IMC) introduces a new paradigm of computation that offers high efficiency in terms of latency and power consumption for AI accelerators. However, the non-idealities... » read more

Optimizing Event-Based Neural Network Processing For A Neuromorphic Architecture


A new technical paper titled "Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration" was published by imec, TU Delft and University of Twente. Abstract "Neuromorphic processors promise low-latency and energy-efficient processing by adopting novel brain-inspired design methodologies. Yet, current neuromorphic solutions still str... » read more

Research Bits: Feb. 6


Laser printer for photonic circuits Researchers from the University of Washington and University of Maryland propose a faster, cheaper way to fabricate and reconfigure photonic integrated circuits. The method uses a laser writer to write, erase, and modify circuits into a thin film of phase-change material similar to what is used for recordable CDs and DVDs. The researcher say the method co... » read more

Research Bits: Jan. 23


Memristor-based Bayesian neural network Researchers from CEA-Leti, CEA-List, and CNRS built a complete memristor-based Bayesian neural network implementation for classifying types of arrhythmia recordings with precise aleatoric and epistemic uncertainty. While Bayesian neural networks are useful for at sensory processing applications based on a small amount of noisy input data because they ... » read more

Novel Neuromorphic Artificial Neural Network Circuit Architecture


A technical paper titled “Mosaic: in-memory computing and routing for small-world spike-based neuromorphic systems” was published by researchers at CEA-LETI Université Grenoble Alpes, University of Zurich and ETH Zurich. Abstract: "The brain’s connectivity is locally dense and globally sparse, forming a small-world graph—a principle prevalent in the evolution of various species, sugg... » read more

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