A deep dive into the convergence of generative AI and edge computing.
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A REVIEW OF PAST AND FUTURE CDFAM PRESENTATIONS
6 minutes read
Researchers at ETH Zurich have developed the first technology that is able to recognise biomarkers in menstrual blood – directly in sanitary towels. MenstruAI promises a simple, non-invasive method for recording health data in everyday life.
4 minutes read
This article explores the significant advancements in AI-driven MEMS sensors, focusing on STMicroelectronics' (ST) cutting-edge technologies, their applications, and the ecosystem supporting these innovations.
A Review of Presentations from CDFAM Computational Design Symposium Series, Past and Future
8 minutes read
Wevolver spoke with John Weil, Vice President of IoT and Edge AI Processor Business at Synaptics, to understand the challenges of bringing AI to the edge, how the Synaptics Astra™AI Native platform enables cognitive computing in real-world devices, and what the future holds for edge intelligence.
Generative artificial intelligence (GenAI) suffers from several types of biases that reflect human failings. How can we avoid being tricked?
4 minutes read
As seen at CDFAM Computational Design Symposium
4 minutes read
In addition to training future players, the technology could expand the capabilities of other humanoid robots, such as for search and rescue.
EPFL researchers have discovered key 'units' in large AI models that seem to be important for language, mirroring the brain's language system. When these specific units were turned off, the models got much worse at language tasks.
4 minutes read
New type of "state-space model" leverages principles of harmonic oscillators.
Explore how advanced computer vision technology transforms quality control in metal manufacturing and why it represents the industry's future.
"IntersectionZoo," a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.
A new method helps convey uncertainty more precisely, which could give researchers and medical clinicians better information to make decisions.
A new approach could enable intuitive robotic helpers for household, workplace, and warehouse settings.
The Fraunhofer Institute for Factory Operation and Automation IFF (Fraunhofer IFF) is working to overcome challenges to e-waste disposal.
