Artificial Intelligence
Artificial intelligence has been called the greatest disruptive technology in history. Here you will find all the content from Mouser Electronics related to AI with subjects ranging from the newest programming techniques to thought provoking articles on the ethical issues surrounding artificial intelligence to examples of new ways AI is being used by industries across the globe.
Jump into Machine Learning with NXP
Edge-based machine learning (edge ML) stands out as a transformative technology, redefining how we process and analyze data in real time.
Edge Impulse Fundamentals: Part Seven
We explore how the live classification tool ensures the model is ready for real-world deployment.
Edge Impulse Fundamentals: Part Six
We finish exploring the tools Edge Impulse provides to analyze ML model performance and investigate ways to mitigate the effects of overfitting and underfitting.
Intel Programmable Acceleration Card with Arria® 10 GX
Learn MoreEdge Impulse Fundamentals: Part Five
We look at the processes and tools Edge Impulse provides to analyze ML model performance.
Implementing TinyML: Introduction to Libraries, Platforms, and Workflows
Discover three Machine Learning (ML) libraries and platforms suitable for the rapid development and deployment of edge-based TinyML applications.
Give AI Tools, Get Better Results
Overcome limitations and supercharge large language models like GPT-4 by giving them access to software-based tools.
NXP Semiconductor i.MX RT1060 Crossover Processor
Learn MoreEdge Impulse Fundamentals: Part Four
We look at the learning and output blocks that create the impulse workflow.
Edge Impulse Fundamentals: Part Three
We focus on the pre-processing pipeline in impulse design.
Edge Impulse Fundamentals: Part Two
We take a practical look at the overall Edge Impulse workflow, from data collection and training to firmware deployment on targeted edge devices.
Edge Impulse Fundamentals: Part One
In part one of the Edge Impulse Fundamentals series, we focus on capturing the data that drives machine learning models.
An Engineer's Primer: Designing AI Systems
(Source: Alexander – stock.adobe.com) Artificial intelligence (AI) is infiltrating nearly every industry and discipline. From applications we use like Google Maps to factory automation, and...
AI Can Code Now
AI can code now, and it performs well enough to help experienced programmers code better and non-coders access the power of software.
Creating Programs That Learn
For adding intelligence to applications, developers take advantage of neural networks and a number of other machine-learning algorithms.
Machine-Learning Software Simplifies Development
AI programming requires relatively few software packages to get started but may need more specialized software to create efficient applications.
Xilinx Zynq® UltraScale+™ MPSoC ZCU102 Evaluation Kit
Learn MoreMachine Learning Requires Multiple Steps
From idea to solution, the steps involved in machine learning deployment.
Data in Action: Capturing It, Structuring It, Modeling It, and Putting Data to Work for You
Aggregating data from sources is prologue to building data models. Discover the hierarchy of building a data model and advantages to modeling and simulation.
Artificial Intelligence and the Data that Drives It
Data is a valued commodity sought throughout the world. As AI use increases, the data that drives it will continue to be a prominent part of our conversation about technology and the role it plays
Micron 9300 NVMe™ SSD
Learn MoreAI Meets Open Source
How does the open source movement impact AI applications? These platforms, data, frameworks, and models are being used in AI development to improve and enhance projects. Let’s explore.
How AI Helps Coders
In modern business environments, competitive advantage rides on high-quality software. The pressure is on to innovate. Enter: AI