According to , the global AI robotics market will reach $17 billion in 2024 and will keep growing by 24% annually. Today, robots deliver packages, conduct geological surveys, and entertain visitors of parks and exhibitions – however, that’s not the limit of their abilities.
According to , the global AI robotics market will reach $17 billion in 2024 and will keep growing by 24% annually. Today, robots deliver packages, conduct geological surveys, and entertain visitors of parks and exhibitions – however, that’s not the limit of their abilities.
Join us for The Rise of Generative AI at the Edge: From Data Centers to Devices webinar on Wednesday, January 15th
Brain–machine interfaces (BMIs) have enabled a handful of test participants who are unable to move or speak to communicate simply by thinking.
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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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.
According to , the global AI robotics market will reach $17 billion in 2024 and will keep growing by 24% annually. Today, robots deliver packages, conduct geological surveys, and entertain visitors of parks and exhibitions – however, that’s not the limit of their abilities.
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Join us for The Rise of Generative AI at the Edge: From Data Centers to Devices webinar on Wednesday, January 15th
Brain–machine interfaces (BMIs) have enabled a handful of test participants who are unable to move or speak to communicate simply by thinking.
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Recently we launched new Edge Impulse functionality that shows just one of the powerful ways that LLMs can be utilized on the edge: using GPT-4o to train a 2,000,000x smaller model, that runs directly on device.
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This article examines gen AI’s impact on data center design and operations and explores the changes necessary to support its continued development.
A team of Caltech researchers has developed an analogous algorithm for autonomous robots—a planning and decision-making control system that helps freely moving robots determine the best movements to make as they navigate the real world.
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AI in the IoT also needs to be performed as close to the sensors as possible, all the way to the edge, on increasingly capable devices in terms of compute power.
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Creating realistic 3D models for applications like virtual reality, filmmaking, and engineering design can be a cumbersome process requiring lots of manual trial and error.
This new device uses light to perform the key operations of a deep neural network on a chip, opening the door to high-speed processors that can learn in real-time.
EPFL research investigating the potential impact on education of AI assistants has found that systems like GPT-4 can answer up to 85% of university assessment questions correctly.
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Edge AI Technology Report: Generative AI Edition Chapter 3. Advances in model optimization techniques like pruning, quantization, and knowledge distillation pave the way for more efficient deployment of generative AI at the edge.
Fine-tuning large language models adapts pre-trained models to specific tasks or domains using tailored datasets, while Retrieval-Augmented Generation (RAG) combines retrieval systems with generative models to dynamically incorporate external, up-to-date knowledge into outputs.
'Fashion tech' refers to the use of big data, AI, AR/VR, and IT in customer services; the development of products incorporating functional materials and wearable devices; and the application of electronics and digital technologies in manufacturing, processing, and distribution processes.
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Optical sensors are the “eyes” of industrial systems, relying on robust peripherals for reliable image processing. As sensors grow more powerful, challenges like data management, mechanical stress, and thermal issues in compact designs demand innovative solutions.
The method could help communities visualize and prepare for approaching storms.
