Lattice Blog

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?

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.

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...

The complexity of implementing intelligent Edge solutions is causing many issues for designers, including accommodating devices with new and legacy interfaces in a variety of applications. Some of these applications also require compute engines capable of processing data collected at low power and cost.

You may be asking yourself, “What does a nineteenth century architect have to do with FPGAs?” A key decision facing many system architects is which FPGA families to use in their next project. Lattice currently offers four classes of FPGAs: iCE, ECP, Mach and CrossLink. It is often tempting to think of FPGAs as just a blank canvas, ready to be filled with digital logic.

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.

It’s tough being a mobile designer. Whenever new and exciting functionalities are identified, it is up to them to figure out how to implement those new elements into an already “crowded” design. Take a smartphone and new always-on monitoring functionality, for example. Every sensor the designer adds to support always-on monitoring and context awareness must continuously send data to the applications processor (AP).

Celebrating its 50th birthday, CES 2017 did not disappoint. Hundreds of thousands of people gathered in Las Vegas to get a first look at the latest technology for the upcoming year. During the 4 days, the biggest names in consumer electronics and startups alike wowed us with products and technologies that promise to make our lives easier and more efficient. Here are some of the trends we saw at the event and how we can support them.

Increasingly lower cost sensors, the migration to higher performance I/O interfaces, and the demand for “always-on, always-aware” functionality all present new challenges for designers of battery-powered mobile devices. Engineers building everything from phones and drones to wearables and industrial equipment are facing the same problem. 

Many of today’s most extraordinary inventions have been developed by independent makers, inventors, designers and tinkerers, who used collaborative tools and knowledge to create exciting, new products.

For many consumers, smart speakers are the gateway device to smart home management. Using these elegant devices, users can control their music, quickly order staple items online, and get answers to burning questions through the power of the Internet.