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In this episode, we talk about a research study from MIT that estimates the carbon emissions associated with autonomous vehicles will match that currently produced by all of the data centers in the world along with how to address it.
EPFL researchers have combined low-power chip design, machine learning algorithms, and soft implantable electrodes to produce a neural interface that can identify and suppress symptoms of various neurological disorders.
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Trustworthy and reliable applications are fueling the worldwide IoT success story. This article explains why protecting IoT edge devices is crucial in an environment with threats on the rise.
Study shows that if autonomous vehicles are widely adopted, hardware efficiency will need to advance rapidly to keep computing-related emissions in check.
Case study
Fast localization and picking of multiple objects with Photoneo's Locator Studio for 3D picking in collision-free environments, PhoXi 3D Scanner, and a universal gripper.
A new method can produce a hundredfold increase in light emissions from a type of electron-photon coupling, which is key to electron microscopes and other technologies.
In this episode, we talk about about how an ant inspired robotics platform could be the future of swarm robotics due to its simple, affordable, flexible, and scalable nature.
The Industrial Revolution began in Britain sometime around 1760. It ushered in a period where coal-fired steam engines powered increased mechanization and productivity and transformed a largely agrarian society into a manufacturing one.
Deep-Learning technology helps industrial engineers with continuous improvement, line balancing, and optimizing manual labor.
Exploring a new way to teach robots, Princeton researchers have found that human-language descriptions of tools can accelerate the learning of a simulated robotic arm lifting and using a variety of tools.
#10 of our Voice of Innovation fireside chat series: Robotics and AI reporter Rachel Gordon speaks to Daniel Situnayake, a founder, engineer, and teacher, on what it means to run sophisticated machine learning algorithms on small devices at the edge of a network.
You've probably heard about the amazing capabilities of some recent AI models, such as GPT, AI21, or BLOOM. Perhaps you use one of these models yourself. Either directly, or through another product like Wordtune, YouWrite, Jasper – or ChatGPT. It turns out that while these models are trained on language data, they can be used for other applications as well. In my latest article, you can read more about applications in materials discovery, cybersecurity, and even building management.
EPFL researchers have teamed up with Dartfish and the Lausanne Hockey Club to push the boundaries of sports-performance analysis by applying computer vision and machine-learning technology to action on the ice.
