Lattice Blog

Consumer News from Lattice

Latest Consumer News from Lattice

Posted 11/01/2019 by Lattice Semiconductor

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

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Microsoft Hackathon 2019

sensAI Empowers AI Innovation at Microsoft Hackathon 2019

Posted 09/11/2019 by Abdullah Raouf

Lattice Semiconductor sponsored the Microsoft Sensors Hack, part of the larger 2019 Hackathon event, where Microsoft teams used the Lattice sensAI solutions stack for smart vision systems to create potential use cases for AI and sensors.

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Consumer News from Lattice

Latest Consumer News from Lattice

Posted 07/31/2019 by Lattice Semiconductor

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

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Watch the Lattice sensAI Solutions Stack Deliver Low Power Smart Vision to the Edge

Watch the Lattice sensAI Solutions Stack Deliver Low Power Smart Vision to the Edge

Posted 07/10/2019 by Hussein Osman

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

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sensAI 2.0 Blog

Lattice sensAI Delivers 10x Performance Boost for AI on Edge Devices

Posted 05/20/2019 by Hussein Osman

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?

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Architecting Low Power AI

System Architecture Options for On-Device AI

Posted 11/14/2018 by Deepak Boppana

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.

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Home is where AI is

Home is where AI is

Posted 09/04/2018 by Hussein Osman

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...

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Mobile-Influenced FPGAs Going Broad

Mobile-Influenced FPGAs Going Broad

Posted 04/17/2018 by Hussein Osman

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.

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Form Follows Function – Selecting the Best Lattice FPGA

Form Follows Function – Selecting the Best Lattice FPGA

Posted 04/03/2018 by Gordon Hands

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.

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Implementation of Artificial Neural Networks at the Edge

Implementation of Artificial Neural Networks at the Edge

Posted 07/05/2017 by Hussein Osman

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.

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