The Guide to Understanding the Technologies Defining the Next Phase of Edge AI
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.
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
14 minutes read.
14 minutes read.
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New AI system lets robots work faster than their human teachers without sacrificing accuracy.
Nakahira received a Young Investigator Award from the Japan Science and Technology Agency for developing a machine that builds autonomous systems.
Princeton researchers have developed a new tool to speed the discovery of advanced materials known as metal organic frameworks, or MOFs.
EPFL roboticists have shown that when a modular robot shares power, sensing, and communication resources among its individual units, it is significantly more resistant to failure than traditional robotic systems, where the breakdown of one element often means a loss of functionality.
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
Matroid builds no-code computer-vision detectors that can spot everything from microscopic material defects to real-time safety hazards on a factory floor.
In large-scale warehousing and distribution operations, conveyor belts are an essential infrastructure that must operate with near-zero downtime to ensure the timely delivery of products. The presence of loose or foreign items on a conveyor belt can pose a serious risk to these operations.
In this post, we'll walk through how to evaluate that progress using the same metrics our platform provides automatically, so you can build detectors that get smarter, sharper, and more reliable over time.
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
Exploring the key concepts related to Unsupervised vs Supervised Learning, understanding the fundamental principles, major algorithms and their real-world applications, and practical distinctions between supervised and unsupervised learning.
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
Gain a comprehensive understanding of Edge AI by exploring the fundamental concepts, hardware components, software tools, and real-world applications.
Products referred to as "beauty tech" that utilize AI, IoT, and other technologies are breathing new life into the cosmetics industry. First, let's look at the background that led to the birth of beauty tech.
4 minutes read
Bert Moons, Director of System Architecture at AXELERA AI discusses bottlenecks in transformer inference for generative AI.
10 minutes read
Transforming manufacturing processes through advanced inspection
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?
The Challenges Ahead of Edge AI and How to Solve Them.
Inspiring Examples of Edge AI in Action.
