Lattice Blog

Human-machine interfaces (HMIs) are rapidly evolving, driven by trends such as Automotive personalization, sustainable always-on interfaces, hygienic touchless user interfaces (UI), consistent user experience (UX) across platforms, voice activation, and Industrial automation for labor and safety needs. Regardless of their specific drivers and/or use cases, modern HMIs must be smarter and more dynamic – shifting from command-based to context-aware systems that bridge the human-machine...

Edge AI is reshaping how machines interact with the world, bringing intelligence closer to the data source and enabling real-time, context-aware decision-making. In Automotive and Industrial environments, this shift is driving smarter sensors, automation, and enhanced Human-Machine Interfaces (HMI). But deploying AI at the edge comes with constraints: limited computing capacity, strict power budgets, and compact hardware footprints. In our latest LinkedIn Live panel discussion, Lattice expert...

In the past, Human Machine Interface (HMI) were relatively simple, consisting of buttons, knobs, levers, and static displays designed to control basic functions. Today, HMIs have evolved into sophisticated, context-aware systems that serve as the primary bridge between users and increasingly intelligent machines. Whether embedded in vehicles, Industrial equipment, consumer electronics, or smart infrastructure, modern HMIs must manage a growing array of tasks. These include real-time data vi...

Edge AI — implementing AI models on Edge devices to process algorithms locally rather than in a centralized computing location, like the cloud — has garnered significant attention as one of the fastest developing areas of artificial intelligence. Calculated at roughly $21 billion USD in 2024, the Edge AI market is expected to reach over $143 billion by 2034. This signals a sustained focus across industries on the development of AI-powered Edge systems. New opportunities for Edge AI ...

Every year, PC manufacturers introduce an array of new laptops packed with the latest technologies and features, all designed to deliver great user experiences. Historically, these came in the form of form factor innovations, screen enhancements, and user interface improvements. However, the growing popularity of AI (artificial intelligence) and ML (machine learning) has opened a new world of possibilities and PC manufacturers and ecosystem giants are all looking for ways to add these advance ne...

The importance of AI and ML, the rise of edge computing, and the need for flexible programming in AI. Artificial Intelligence (AI) is one of the biggest buzzwords in the technology industry today and is often thought of in broad terms to describe connected “smart” technology. However, when you think about all the different features enabled by AI and the outcomes AI solutions are designed to deliver, it becomes clear that the AI landscape and AI development is incredibly complex. The ...

The global smart toy market is projected to grow to nearly $70 billion by 2026, per Transparency Market Research. Smart toys take a variety of shapes, like electronic pets, robots, smart train kits, and more. When you hear the word toy, you likely automatically think these are for kids, however some are developed specifically targeting older generations. The current senior toy marketplace contains products that range in utility from providing companionship to increasing cognitive skills to facil...

One of the most exciting topics in the tech world is Artificial Intelligence, or AI. From its science-fiction like promise of intelligent machines to its more practical implementations as additional smarts in connected devices, AI is one of the most powerful technologies now available. But, as the well-known Peter Parker principle dictates, “With great power comes great responsibility” and so it is with AI. Companies building AI-enabled products and services, in particular, have star...

The AI/ML revolution continues to gain traction across multiple applications, particularly Edge applications. Edge devices like security cameras, robots, industrial equipment, Client PCs, and even toys can now support AI/ML capabilities that provide users with new capabilities and experiences. According to industry analyst firm ABI Research, the Edge AI chipset market “has experienced strong growth in the past and is expected to continue to grow to US$71 billion by 2024, with a CAGR of 31%...

The Lattice sensAI solution stack for always-on Edge AI applications is available on the Lattice CrossLink-NX family of FPGAs to enable fast and easy development of low power, smart visions systems for the industrial, automotive, and IoT markets.

At Linley Fall Processor Conference, Lattice shared latest updates to Lattice sensAI™, a solution stack for next-generation smart devices with extremely low power consumption.

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

Read the latest industrial and automotive news from Lattice: Enhanced sensAI stack packs 10X performance boost, Integrate AI into smart applications, CrossLink FPGA simplifies use of embedded vision, Lattice showcases sensAI at Microsoft Hackathon.

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.

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

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...

Over recent decades system design has evolved from one processing topology to another, from centralized to distributed architectures and back again in a constant search for the ideal solution.