By reconfiguring neural networks in artificial intelligence (AI) devices, a multi-institute team that included Penn State researchers facilitated AI systems to continually learn and adapt new data and tasks in ways that were not possible or practical before.
By reconfiguring neural networks in artificial intelligence (AI) devices, a multi-institute team that included Penn State researchers facilitated AI systems to continually learn and adapt new data and tasks in ways that were not possible or practical before.
The CyberSpec framework is designed to detect anomalous behavior linked to cyber-attacks against crowd-sensing spectrum sensors, even when said sensors are running on lightweight resource-constrained hardware like a Raspberry Pi.
Developed at Google Research, HyperTransformer decouples the task space and individual task complexity to generate all model weights in just one pass — while also offering support for unlabeled sample ingestion.
Artificial intelligence (AI) is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making
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Understanding industrial vision systems by examining their components, imaging fundamentals, AI integration since 2020, and how to choose the right solution for every application.
Explore the rise of intelligent EV hardware and how real-time processing, ML acceleration, and hardware virtualization are enabling safer, smarter, software-defined electric vehicles.
A detailed engineering reference on performance, signaling, and power differences in current graphics memory standards.
EPFL researchers are developing AI models that could one day enable vision prosthetics able to restore meaningful, object-level sight for the blind.
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Understanding industrial vision systems by examining their components, imaging fundamentals, AI integration since 2020, and how to choose the right solution for every application.
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
By reconfiguring neural networks in artificial intelligence (AI) devices, a multi-institute team that included Penn State researchers facilitated AI systems to continually learn and adapt new data and tasks in ways that were not possible or practical before.
4 minutes read
The CyberSpec framework is designed to detect anomalous behavior linked to cyber-attacks against crowd-sensing spectrum sensors, even when said sensors are running on lightweight resource-constrained hardware like a Raspberry Pi.
Developed at Google Research, HyperTransformer decouples the task space and individual task complexity to generate all model weights in just one pass — while also offering support for unlabeled sample ingestion.
FaceBit aims to be low-cost, energy-efficient, and easy-to-integrate hardware with rich sensing functionalities– monitors physiological signals
Hardware and software engineers will be the lifeblood of tomorrow's connected world. Academia is working hard to ensure a steady supply, in part by adapting engineering education to train the next generation of IoT innovators.
3 minutes read
Designed to dramatically reduce the amount of training data needed for an image recognition system, this one-shot approach "inspired by nativism" takes a leaf from humans' ability to intuit and abstract.
ML can be deployed on Embedded Sensors to unleash the full power of Industry 4.0.
Advances in software allow a customized car to perform controlled, autonomous drifting to enhance active safety and to give drivers the skills of professional racers.
With the help of new technologies, artificial intelligence, and digital monitoring, more healthcare will be provided in patients’ homes.
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BottleFit framework applied DNN models in image classification achieves 77.1% data compression with up to 0.6% accuracy loss on the ImageNet dataset.
In this article, we look at two tinyML projects for education. We show how Backyard Brains uses low-cost experiment kits to make neuroscience education more accessible. We also introduce our readers to a specialisation offered by Harvard & Google to help students learn tinyML like never before.
Considered obsolete since the introduction of vision transformers, ConvNeXt proves there's life in convolution yet — outperforming its rivals by adopting some of their own tricks.
A holistic open-source framework to improve the performance of multiple modalities and outperform the existing single-modality algorithms.
#6 of our 'Voice of Innovation' fireside chat series: Robotics and AI reporter Rachel Gordon speaks to IoT networking savant Wienke Giezeman.
Soon, internet users will be able to meet each other in cyberspace as animated 3D avatars. Researchers at ETH Zurich have developed new algorithms for creating virtual humans much more easily.
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