Many people have begun experimenting with using machine learning in embedded systems as the two technologies have become more prominent in today’s society. That approach allows for overcoming many of ...

Intel wrote a white paper in collaboration with Daedalean, a startup working on machine-learned solutions in the aviation space. Published this week, the report features a reference design for an AI ...

Machine vision and embedded vision systems both fulfill important roles in industry, especially in process control and automation. The difference between the two lies primarily in image processing ...

In fact, he says, such efforts can be faster because they need dramatically shorter testing and debugging periods. However, for developers accustomed to working with large, full-blown computer systems ...

Machine learning is starting to come online in all kinds of arenas lately, and the trend is likely to continue for the forseeable future. What was once only available for operators of supercomputers ...

AI models have demonstrated impressive results in experiments, but deploying them in real-world applications requires combining neural networks with pre- and post-processing steps. Thus the need for ...

Why it’s important not to over-engineer. Equipped with suitable hardware, IDEs, development tools and kits, frameworks, datasets, and open-source models, engineers can develop ML/AI-enabled, ...

Most motion systems have at least some embedded control. Now evermore-powerful data processing and chip manufacturing is being leveraged — so increasingly sophisticated firm and hardware is being ...