Consumer

Read the latest consumer news from Lattice: Enhanced sensAI Stack Enables More Accurate, Lower Power Edge Solutions, Free Webinar Explores Low Power AI Design, CrossLink FPGAs Simplify Use of Embedded Vision

If you’re looking at ways to implement Edge AI, be sure to read about the use cases for the Lattice sensAI solution stack for always-on Edge devices covered at the end of our white paper.

Read the latest consumer news from Lattice: Lattice sensAI brings more performance to the edge, Radiant IP and reference design, demo videos from Embedded Vision Summit, industry award and press coverage for sensAI

If you missed the 2019 Embedded Vision Summit, check out the latest sensAI demos from Lattice to and see what smart vision can enable in Edge devices

A year ago we launched the Lattice sensAI solutions stack. Since then, the need for AI at the Edge has continued to grow. Consider this statistic from Tractica: by 2025 the market for Edge-based AI chipsets is forecasted to hit $51.6 billion (that’s over three times their forecasted revenues for cloud-based AI chips). Why all the interest in chips that support AI at the Edge?

Last week at Embedded World, the Nürnberg Exhibition Center was abuzz with conversations about today’s hottest tech topic, artificial intelligence (AI), as embedded engineers prowled the show floor looking for ways to quickly and easily add AI support to future products. Lucky for them, Lattice Semiconductor had the solutions they were looking for.

With the evolution of SMART cities, homes and factories, there is a multitude of situations that demand accurate proof of the presence of a person…and perhaps his or her positioning and actions. In a modern factory using Industrial IoT (IIoT)/ Industry 4.0 practices, safety must not be left behind.

How often is low power the determining factor for success? Certainly when designing solutions for AI inferencing in always-on edge devices, the power consumption must be measurable in milliwatts. Think about it: AI at the edge solves real world problems, and is – or very soon will be – everywhere.

A new generation of AI-based edge computing applications demand a wide range of performance requirements. But how can developers build edge solutions that consume little power and occupy minimal footprint at low cost without compromising performance?

Very soon most homes will have Siri, Alexa, Google Home or similar. Many already have all three. The acceptance of such sophisticated AI systems as an everyday, normal addition to the living room says much about the human condition to imagine, conceptualize, innovate, experiment with...