5 Questions to Ask Before Getting Started with Data Annotation:
What is data annotation? Why is it essential? What are common label types for models? How do AI-powered data annotation tools help with the computer vision labeling process? What’s the best way to get started?
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.
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!
A team that included Chongzie Zhang from McKelvey Engineering developed a method that allows robots to teach other robots with different features to perform the same task.
5 Questions to Ask Before Getting Started with Data Annotation:
What is data annotation? Why is it essential? What are common label types for models? How do AI-powered data annotation tools help with the computer vision labeling process? What’s the best way to get started?
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.
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.
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.
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.
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.