Model efficiency research is enhancing power efficiency and boosting AI performance.
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How on-device and cloud AI will foster the advancement and scalability of next-generation generative AI experiences
Qualcomm's Pioneering Approach to Hybrid AI: Merging Cloud Processing with On-Device Efficiency and Scale
Gesture recognition, leveraging the advanced capabilities of embedded devices and streamlined through specialized platforms is creating new means of human-machine interactions, paving the way for more intuitive and user-friendly device interfaces.
This is how Sevensense tests its curring-edge Visual SLAM technology to ensure robust performance.
Join us for the premier edge AI event, with presentations and demonstrations from top technology leaders and innovators.
Article #4 of Spotlight on Innovations in Edge Computing and Machine Learning: Discover the integration of TinyML and wearable tech as we delve into a project that detects falls in real-time, potentially saving lives in our aging population.
Seamless and intuitive user experiences using speech-recognition technology are enabling us to interact with a device simply through voice commands.
Edge AI platforms can assist engineers to monitor battery health systems.
Article #3 of Spotlight on Innovations in Edge Computing and Machine Learning: A computer vision system that detects and localizes the surface cracks in concrete structures for predictive maintenance.
16 minutes read
From sleep monitoring wearables to face detection models, tinyML is making a big impact on the way we can gather and apply data.
Highlights from the 3rd Annual tinyML EMEA Innovation Forum include exploring hardware developments, algorithm optimization, and deploying MLOps tools.
Article 6 of Bringing Intelligence to the Edge Series: The utilization of edge AI facilitates advanced system optimization, predictive maintenance, and improved anomaly detection, greatly advancing technological capabilities across varied fields.
Article 5 of Bringing Intelligence to the Edge Series: Integrating voice user interface technology into microcontroller units for offline, edge-based voice recognition is set to redefine the landscape of home automation and smart industrial applications.
Article 4 of Bringing Intelligence to the Edge Series: AI is proving to be a more precise and time-efficient tool in processing the big data crunch by recognizing patterns and noticing inconsistencies in real-time.
