A deep dive into the convergence of generative AI and edge computing.
Category
A.I.
Latest Posts
Electronic Technology Supporting the Evolution of “Next Tech”
6 minutes read
Seamless and intuitive user experiences using speech-recognition technology are enabling us to interact with a device simply through voice commands.
The tinyML Foundation, Sony Semiconductor, and the City of San José are teaming up to use Machine Learning in improving pedestrian safety
There is a talent shortage in the Netherlands that is expected to persist until 2050. So concludes Ton Wilthagen, professor of Labor Market at Tilburg University, in the new High Tech Campus documentary The Talent Game: "Even if we attract more international knowledge workers, work more hours and involve people from the sidelines in the labor market, the talent shortage will remain."
2 minutes read
In this episode, we discuss a joint effort between the Laboratory for Information and Decisions Systems and the Institute for Data, Systems, and Society at MIT to tackle the trust issue with autonomous vehicles.
17 minutes read
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.
In both analytics and machine learning (ML), the value of data cannot be overstated. Understanding its importance is essential for unlocking its full potential and driving informed decision-making, enhancing business processes, and exploring new opportunities across various industry sectors.
Understanding What is Unsupervised Learning, the Mechanisms, Types, and Applications of Various Algorithms and Challenges it presents in Machine Learning
Qube was designing IoT devices that needed to be deployed in remote environments and required very little maintenance. They needed a platform that offered low power, was affordable, and that could scale across the world.
10 minutes read
