As demand for artificial intelligence at the edge continues to grow, it has become increasingly difficult for designers and developers to support. Constrained edge systems often lack the power, processing, and space required to run these high-performance workloads effectively.
In a recent webinar hosted by Embedded Computing Design, experts from the Lattice team discussed the growing role that flexible field-programmable gate arrays (FPGAs) play in the development and deployment of edge AI solu...
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Posted 04/16/2026 by Mamta Gupta, AVP, Strategic Business Development, Datacenter & Security
In early 2026, a quiet shift became impossible to ignore: artificial intelligence (AI) moved from helping defenders to operating like an attacker at scale. The cybersecurity community took notice when researchers revealed that an advanced AI system, known publicly as Claude Mythos Preview, was able to independently discover and exploit serious software vulnerabilities. Many of these weaknesses had existed for years in widely used operating systems and software, despite extensive testing and revi...
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As AI adoption accelerates, workloads are no longer confined to centralized datacenters. Instead, AI is scaling across cloud infrastructure, edge systems, industrial platforms, robotics, and physical AI devices. This shift is fundamentally changing how systems are designed. While CPUs, GPUs, and other accelerators continue to anchor AI performance, modern architectures are becoming more modular, more distributed, and far more dependent on the silicon that surrounds those primary compute engines....
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That question opens Lattice Semiconductor’s recent Security Seminar, and it becomes more urgent as humanoids move beyond research environments and begin operating around and interacting with people. Mechanical safeguards and functional safety standards address only part of the risk. When control systems, firmware updates, or data paths can be compromised, security directly determines physical safety.
In this seminar, experts from Lattice Semiconductor, SEALSQ, and Promwad examine the real...
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One of the year’s largest global trade shows,
embedded world
is a place for Lattice and its industry partners to gather and discuss the innovative solutions enabling engineers to deploy intelligent, scalable designs from cloud to sensor. If we missed you at the event, here’s a snapshot of our presence at embedded world 2026.
Showcasing Key Solutions for Tomorrow’s Embedded Challenges, Today
Over the course of the conference, the Lattice team had the opportunity to present...
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Supporting today’s growing landscape of distributed, autonomous devices is no simple feat. Whether it is industrial robots, autonomous drones, or in-vehicle safety systems, each of these increasingly intelligent solutions requires real-time processing capabilities to function.
Supporting these capabilities requires moving artificial intelligence (AI) and machine learning (ML) applications away from centralized cloud services and closer to the cameras, radar systems, and other sensors that...
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Posted 03/04/2026 by Jim Tavacoli, Sr. Director, Segment Marketing, Lattice Semiconductor
Modern defense platforms are caught in a familiar bind. Many of the mission computers still in service today were designed decades ago, and in many cases, they are doing exactly what they were built to do. They rely on interfaces like MIL-STD-1553 and ARINC 429 because those standards have proven reliable and predictable over time. They are deeply embedded across airborne, ground, and naval platforms, and replacing them is far from simple.
What has changed is everything around them. New sensors...
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The Industrial sector is in a moment of real transformation. While automated solutions like Industrial robotics have long been sources of speculation and hype, conversations are beginning to shift towards what’s realistically deployable in today’s factories and service environments.
In a recent webinar hosted by Embedded Computing Design, experts from Lattice, Advantech, and Renesas helped cut through the noise and explore the robotics applications Industrial customers expect, the ...
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Present-day edge AI systems rely heavily on multi-modal sensor fusion, such as camera, lidar, and radar, to enable accurate, real-time decision-making. Existing platforms, such as NVIDIA® Jetson Orin NX, are equipped to adequately support multi-camera use cases. To advance this further, NVIDIA’s latest Jetson Thor series modules have been combined with the Holoscan Sensor Bridge board – running on a Lattice FPGA – to address the increase in sensor counts and synchronization...
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The rapid expansion of connected, intelligent machinery is transforming Industrial infrastructure as we know it. As devices at the edge take on more responsibility, engineers and developers face rising pressure to enable connectivity while maintaining overall system effectiveness and security. Industrial organizations must keep pace with digital transformation and stay resilient against expanding and complex cyber threats.
To strike this balance, Industrial infrastructure must become more cyber...
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