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.
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.
We all know how AI-based systems can be a real burden to your company’s energy bill and to reaching global climate goals. How about exploring AI’s capabilities to achieve the opposite? By deploying artificial intelligence to reduce your carbon footprint instead of enlarging it
Article #5 of the "Why Edge?" Series Moving Computer Vision to the Edge offers advantages in security and latency.
Artificial intelligence (AI) is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making
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eCozy 2.0 system addresses the limitations of traditional thermostats for water heating radiators, delivering efficiency, convenience and sustainability benefits to households
Protect the cloud by securing the edge with hardware-based security, TPMs, HSMs, and resilient edge computing architectures.
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.
EPFL researchers are developing AI models that could one day enable vision prosthetics able to restore meaningful, object-level sight for the blind.
A deep-dive listicle guiding controls, automation, and quality engineers toward the best vision systems for manufacturing applications in 2026.
Understanding industrial vision systems by examining their components, imaging fundamentals, AI integration since 2020, and how to choose the right solution for every application.
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
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.
We all know how AI-based systems can be a real burden to your company’s energy bill and to reaching global climate goals. How about exploring AI’s capabilities to achieve the opposite? By deploying artificial intelligence to reduce your carbon footprint instead of enlarging it
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Article #5 of the "Why Edge?" Series Moving Computer Vision to the Edge offers advantages in security and latency.
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Curiosity drives artificial intelligence to explore the world, now in boundless use cases — autonomous navigation, robotic decision-making, optimizing health outcomes, and more.
Matroid's deep-learning system comprising of 3D-CNN helps to automatically detect Glaucoma from a single raw Optical Coherence Tomography (OCT) scan. The results are close to human doctors across heterogeneous datasets and scanning environments.
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.
Newly developed method does it all with just a few pixels
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$1.2 million National Science Foundation grant funds project to use quantum AI to create effective pharmaceuticals faster and cheaper
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Using Artificial Intelligence (AI) to replace optical and mechanical components, researchers have designed a tiny spectrometer that breaks all current resolution records.
How do you help high-tech companies get the most out of AI? You should bring knowledge, new ecosystems, and cutting-edge technology together on ‘the smartest square kilometre’ in the world!
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Article #4 of the "Why Edge?" Series. A short guide to how Edge AI is enabling cutting-edge advances in the automotive industry.
Article #4 of the Enabling IoT Series. Industrial enterprises are moving to a new approach to asset management, namely predictive maintenance by leveraging powerful new sensors and data.
In this episode, we talk about how a machine learning algorithm that can predict what sequence of actions a volleyball player will take next is being used to create more effective human/machine interactions for safer autonomy in our lives.
