Lattice Blog

The importance of AI and ML, the rise of edge computing, and the need for flexible programming in AI. Artificial Intelligence (AI) is one of the biggest buzzwords in the technology industry today and is often thought of in broad terms to describe connected “smart” technology. However, when you think about all the different features enabled by AI and the outcomes AI solutions are designed to deliver, it becomes clear that the AI landscape and AI development is incredibly complex. The ...

The AI/ML revolution continues to gain traction across multiple applications, particularly Edge applications. Edge devices like security cameras, robots, industrial equipment, Client PCs, and even toys can now support AI/ML capabilities that provide users with new capabilities and experiences. According to industry analyst firm ABI Research, the Edge AI chipset market “has experienced strong growth in the past and is expected to continue to grow to US$71 billion by 2024, with a CAGR of 31%...

We’ve published a couple blog posts exploring how support for AI-powered imaging systems in embedded devices operating at the network edge can benefit specific applications in smart factories and smart homes. But embedded vision can also benefit the retail customer experience.

It may seem obvious but safer factories are not only a better work environment, they are also more productive. And some of the machine vision techniques that are now being employed to ensure worker safety are also applicable to aid production processes.

Over recent decades system design has evolved from one processing topology to another, from centralized to distributed architectures and back again in a constant search for the ideal solution.

New Technology Promises to Accelerate Deployment of Machine Learning Inferencing Across Mass Market, Low-power IoT Applications

Imagine private security systems that can differentiate between an intruder and your neighbor’s dog, smart TVs that can scan the room and automatically turn off when no one is present, and cameras that can perform forensic analysis and identify suspicious behavior before a crime occurs. The applications for deploying artificial neural networks at the edge are endless. Coming up with ideas is easy, but getting to the implementation is not that simple.

What excites me about technology is its prospects for making human life better. Artificial Intelligence (AI), Machine Learning and Deep Learning hold a lot of promise to do just that, if done in a sensible way.