Article 3 of Bringing Intelligence to the Edge Series: Balancing the critical metrics of accuracy, power consumption, latency, and memory requirements is key to unlocking the potential of Tiny Machine Learning (TinyML) in low-power microcontrollers and edge computing.
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ORGANIZATIONS. SHAPING THE INDUSTRY.
Edge Impulse
Machine Learning
AI for any edge device from MCUs, NPUs, CPUs, GPUs, gateways, and beyond.
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Article 2 of Bringing Intelligence to the Edge Series: Advancements in AI and embedded vision technologies are revolutionizing various industries, enabling real-time decision-making, enhancing security, and facilitating automation in various applications.
Article 1 of Bringing Intelligence to the Edge Series: With the introduction of AI, IoT devices can become more intelligent and less reliant on external systems— but not without trade-offs in performance and cost. Understanding how to make that decision is key.
Introducing the Bringing Intelligence to the Edge Series: Exploring how Artificial Intelligence is moving to embedded systems, transforming technology across various applications.
Exploring the integration and impact of microcontrollers and Edge AI across various industries.
Article #2 of Spotlight on Innovations in Edge Computing and Machine Learning: Edge AI techniques such as Keyword Spotting can turn an ordinary device into a smart appliance.
13 minutes read
Bert Moons, Director of System Architecture at AXELERA AI discusses bottlenecks in transformer inference for generative AI.
10 minutes read
In this article, we will look at the challenges that engineers encounter when deploying a predictive maintenance system and how edge AI platforms like Edge Impulse can help factories optimize and deploy predictive maintenance models on industrial edge devices.
Introducing a brand new series featuring innovative projects related to edge computing and machine learning. The first article presents a predictive maintenance solution utilizing the Nordic Thingy:91, monitoring machine health through anomaly detection with a TinyML model.
What’s Next for Artificial Intelligence and Edge Computing?
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Inspiring Examples of Edge AI in Action.
How Edge AI Senses the World for Situational Awareness.
What to Consider When Selecting Your Edge AI Hardware and Software.
A Deep Dive Into Edge AI in Energy-Constrained Environments
