This guide outlines the key steps to designing, optimizing, and deploying AI at the edge, followed by a look at how purpose-built edge AI toolchains can support and streamline this process.
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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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The collaboration between AI and robotics enables robots to implement tasks more effectively and handle complications previously beyond their capacities.
To empower intelligence at the edge, smart and highly integrated driver solutions are required for electromechanical actuators.
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Wevolver spoke with John Weil, Vice President of IoT and Edge AI Processor Business at Synaptics, to understand the challenges of bringing AI to the edge, how the Synaptics Astra™AI Native platform enables cognitive computing in real-world devices, and what the future holds for edge intelligence.
Ambiq’s ultra-low-power edge AI technology is pushing health monitoring by enabling always-on, intelligent wearable devices that track vital signs in real time without relying on cloud connectivity.
Healthcare is facing a critical workforce shortage, with AI emerging as a key tool to support clinicians by improving diagnostics, treatment planning, and efficiency without replacing human expertise.
In the modern era of sport, results are often decided by ultra-fine margins like milliseconds or millimeters. Yet even precise metrics such as speed and distance are still quite rudimentary in nature.
4 minutes read
Deploying machine learning models at the edge is crucial for real-time data processing in industrial applications. This article explores how Docker simplifies Edge AI deployment on the Arduino Portenta X8, enabling scalable and secure AI implementations on embedded Linux systems.
3 minutes read
Event-based computing is transforming AI processing, delivering smarter, faster, and hyper-efficient solutions across industries like IoT, healthcare, and automotive.
The Edge AI industry is at a turning point with big shots investing heavily. Now is the time to define best practices, share experiences and crowdsource high quality data. Who will be taking the lead in guiding the industry forward?
2 minutes read
AI and ML-driven cashierless stores not only improve operational efficiency and customer personalization but are also expected to propel the global AI retail market to over $40 billion by 2030.
AI is transforming security through real-time threat detection and intelligent surveillance, with Axelera AI advancing this shift using its Metis AI Processing Unit (AIPU) to enhance proactive, adaptive, and sustainable security solutions.
