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.
3 minutes read
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Study shows that if autonomous vehicles are widely adopted, hardware efficiency will need to advance rapidly to keep computing-related emissions in check.
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.
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.
4 minutes read
Deep-Learning technology helps industrial engineers with continuous improvement, line balancing, and optimizing manual labor.
2 minutes read
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.
5 minutes read
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.
3 minutes read
#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.
In this episode, we talk about how perfectly tuning the curiosity of an AI results in more efficient and robust models.
Datacation is a startup in a technology area so advanced it can't even be called 'next-generation'. Perhaps 'next next gen' because so far we don't know all the possible business applications of machine learning and AI, nor do we know the limits.
7 minutes read
Digital transformation and the Industrial Internet of Things (IIoT) continue to impact industry at all levels. While it's seen its earliest adoption in large-scale manufacturing and transport, it's spreading rapidly into other sectors.
Last year, MIT researchers announced that they had built “liquid” neural networks, inspired by the brains of small species: a class of flexible, robust machine learning models that learn on the job and can adapt to changing conditions, for real-world safety-critical tasks, like driving and flying.
Curiosity drives artificial intelligence to explore the world, now in boundless use cases — autonomous navigation, robotic decision-making, optimizing health outcomes, and more.
ML at the edge is the main target in many IoT applications today. Learn why it is important to build energy-efficient embedded devices, and how to achieve it using cutting-edge technologies.
