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.
This article explores TPU vs GPU differences in architecture, performance, energy efficiency, cost, and practical implementation, helping engineers and designers choose the right accelerator for AI workloads today!
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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.
Training AI models is costly, forcing a trade-off between compressing large models or accepting weaker performance from smaller ones trained from scratch.
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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.
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.
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.
MotionCam-3D by Photoneo enables 3D scanning & handling of objects that are moving on an overhead conveyor without interruption. The camera provides high-quality 3D data even while the objects are moving, swinging, or slightly rotating.
ETH researchers led by Marco Hutter developed a new control approach that enables a legged robot, called ANYmal, to move quickly and robustly over difficult terrain. Thanks to machine learning, the robot can combine its visual perception of the environment with its sense of touch for the first time.
3 minutes read
Real-time occupancy monitoring of the comings and goings inside a warehouse, conference room, or corridor yields valuable data.
3 minutes read
In this article, we take a look at two tinyML projects related to healthcare. The first project helps gather Mean Radiant Temperature data outdoors to protect people from extreme heat, and the other one is a solution for affordable, accurate, & rapid detection of pneumonia.
Wearable sensors plus computer vision could reduce the likelihood of degenerative joint disease.
3 minutes read
