Lattice Blog

Lattice Semiconductor and Mistral Solutions have created a real-time data capture card compatible with Texas Instruments mmWave radar sensors.

Read the latest comms and computing news from Lattice: Low power wireless Heterogenous Networks development and upgrade security with Lattice’s MachXO3D FPGA.

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?

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 you’ve been given the responsibility to develop a new video bridging solution. Initially, you have a specific application in mind, but as cameras emerge in a growing number of intelligent applications, ranging from object recognition and depth perception to lane detection and collision avoidance, you know you will need prototypes for a wider variety of functions.