Achieving Greater Accuracy In Real-Time Vision Processing With Transformers


Transformers, first proposed in a Google research paper in 2017, were initially designed for natural language processing (NLP) tasks. Recently, researchers applied transformers to vision applications and got interesting results. While previously, vision tasks had been dominated by convolutional neural networks (CNNs), transformers have proven surprisingly adaptable to vision tasks like image cl... » read more

Using Silicon Photonics To Reduce Latency On Edge Devices


A new technical paper titled "Delocalized photonic deep learning on the internet’s edge" was published by researchers at MIT and Nokia Corporation. “Every time you want to run a neural network, you have to run the program, and how fast you can run the program depends on how fast you can pipe the program in from memory. Our pipe is massive — it corresponds to sending a full feature-leng... » read more

Power/Performance Bits: July 23


Image-recognizing glass Engineers at the University of Wisconsin-Madison, MIT, and Columbia University developed a way to create 'smart' glass capable of performing image recognition tasks without the need for electronics or power. "We're using optics to condense the normal setup of cameras, sensors and deep neural networks into a single piece of thin glass," said Zongfu Yu, electrical and ... » read more

Building AI SoCs


Ron Lowman, strategic marketing manager at Synopsys, looks at where AI is being used and how to develop chips when the algorithms are in a state of almost constant change. That includes what moves to the edge versus the data center, how algorithms are being compressed, and what techniques are being used to speed up these chips and reduce power. https://youtu.be/d32jtdFwpcE    ... » read more

Planes, Birdhouses And Image Recognition


My recent blog post on the limits of neuromorphic computing took an optimistic view: even neuromorphic systems that are relatively crude by the standards of biological brains can still find commercially important applications. A few days after I finished it, I was reminded that the pessimists are not wrong when a friend of mine shared this image. Fig. 1: Trover Gourds in purple martin nest... » read more

Convolutional Neural Networks Power Ahead


While the term may not be immediately recognizable, convolutional neural networks (CNNs) are already part of our daily lives—and they are expected to become even more significant in the near future. [getkc id="261" kc_name="Convolutional neural networks"] are a form of machine learning modeled on the way the brain's visual cortex distinguishes one object from another. That helps explain wh... » read more