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Everyone, it seems, is now talking about how they’re planning to integrate AI into their devices, their factories, their workflows and, well, everything. But how they actually plan to make that happen isn’t always clear. Part of the challenge, of course, is that different workloads and different environments require different types of solutions. For those looking to integrate AI-powered capabilities into edge computing-based offerings, there are a relatively broad range of ways to ac...

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 ...

私は最近、15歳になる娘を初めての大きいコンサートに連れていきました。ロジャーウォーターズのツアーです。自動車技術のブログで何故ロジャーウォーターズの話をしているのかと不思議に思ったかもしれません。もう少しだけ付き合ってください。私と娘はそのコンサートがとても気に入ったのですが、コンサート会場までの行き帰りの運転で、渋滞や駐車場の出し入れに苦戦したのです。そのハイストレスの状況下で私は、送り迎えをしてくれ、リラックスしてる間に渋滞を抜けてくれる無人走行車を持っていたらどんなにすばらしいかと想像しました。

組込みビデオシステムの設計者にとって変化は常にやってきます。この数年間で、設計者はまったく新しいレベルの機能を備えたモバイルアプリケーションプロセッサを組み込んだシステム、元々モバイルコンシューマ市場向けに開発された新しいインタフェース規格の採用、および新世代の低コスト画像センサとディスプレイの導入を見てきました 。