Lattice Blog

The highly anticipated Lattice Developers Conference is right around the corner, and we just announced our full agenda, including an incredible lineup of keynote speakers, technical breakout sessions with notable industry experts, and a robust demo showcase running from December 5 to 7. During the 3-day virtual event, attendees will gain valuable insights, advance their skills, and hear directly from technology leaders across multiple industries about the latest trends, opportunities, and ...

Designing and implementing a complex solution on an FPGA can be tricky. The learning curve for first-time FPGA users can be steep and advancing deeper into FPGA design techniques require time and effort. At Lattice Semiconductor, we want to make your journey of learning and designing with FPGAs a seamless and gratifying experience. Lattice Insights, the official training academy for Lattice Semiconductor, is created to enable that experience - to empower FPGA developers to fully utilize Lattice...

The increasingly autonomous nature of vehicles is a major trending topic in the Automotive industry and, despite the challenges the industry faced during the pandemic, the disruptive technologies behind autonomous features have advanced dramatically in recent years. Earlier this year, McKinsey & Company issued a report on how advanced autonomous features in vehicles brings enormous growth potential not just for consumers or the manufacturers, but also to transform transportation and society ...

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.

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?

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.