Today's autonomous robots are being tasked with increasingly important and dynamic roles across industries. From the autonomous mobile robots (AMRs) that move goods around warehouses to the drones that handle last-mile delivery, these devices are trusted to operate at the edge with little direct human oversight or handling. These robots rely heavily on the sensors that enable them to perceive, understand, and interact with the world around them. As edge AI models are brought in to support more ...
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...
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...
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....
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...
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...
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 ...
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...
FPGA development moves fast, and your verification flow and simulations need to keep up. Long compile times, manual setup steps, and constant design changes can easily slow momentum when you are trying to iterate fast. Before a design ever reaches hardware, you need absolute confidence that it behaves exactly as intended. Lattice Radiant® Software, paired with Siemens QuestaSim Lattice FPGA Edition simulator, delivers powerful functional verification capabilities, but the reality is familiar...
人形机器人市场正快速从概念走向商业化现实。得益于传感、驱动及边缘智能领域的重大突破，曾经只存在于研究实验室的成果，如今已逐步出现在工厂、仓库和服务环境中。 随着这些系统承担越来越复杂的工作负载，开发者必须在严苛的功耗与散热限制下，实现密集的传感器数据融合、亚微秒级电机控制回路以及实时感知处理。核心问题已不再是"能否造出人形机器人"，而是"能否信任它们安全、自主地运行"。 Lattice FPGA 在这一转型中发挥着关键作用——通过紧邻电机和传感器的低功耗、高确定性处理，驱动感知与灵巧动作的实现。结合TPM锚定安全机制与硬件信任根（HRoT）架构，这些器件还可帮助团队强化机器人各分布式节点的系统完整性。 近期，我们与Lattice安全事业部副总裁Eric Sivertson进行了深度对话，探讨如何借助TPM锚定型FPGA、确定性控制及量产路径，保障人形机器人的安全。 问：您如何看待当前人形机器人市场的成熟度？ 答： 市场仍处于早期阶段，但发展势头迅猛。我们正在见证人形机器人从研究和试点阶段向早期商业化部署转变。人形机器人代表着"具身智能"的终极形态，但市场尚未成熟...
When it comes to making predictions, sometimes you really have to go out on a limb and sometimes, well, it’s pretty easy. In 2026, there’s zero doubt that AI, generative AI, and agentic AI will continue to be the key buzzwords driving the tech industry forward. Perhaps a bit less obvious is this year should also mark the beginnings of a growing opportunity in Edge AI, where AI-focused workloads can run in disconnected environments and/or locally on client type devices. The combinati...
The continued evolution of AI is reshaping the foundation of datacenter design and development. As workloads grow more complex and resource-intensive, operators face mounting challenges related to datacenter performance, reliability, and security. If workload demands can’t be consistently met, infrastructure will be unable to scale without disruption. In our latest LinkedIn Live panel discussion , Lattice experts and Bob O’Donnell from TECHnalysis Research explored the increasingly c...
The transition to post-quantum cryptography (PQC) is not a theoretical future event. It is the largest cryptographic migration in modern history, already shaping product roadmaps, standards bodies, and infrastructure planning across servers, AI datacenters, telecom, industrial automation, and critical systems. In this interview, we sat down with Mamta Gupta, a leader driving Lattice’s quantum-safe security strategy, to discuss Quantum Day (Q-Day) readiness, crypto-agility, Security Proto...
Artificial intelligence (AI) is rapidly moving out of the datacenter and into the real world, powering everything from industrial robots to autonomous vehicles and smart infrastructure. Edge devices have become the new frontier for AI, driving smarter factories, safer vehicles, and more responsive cities. Meeting the needs of edge applications involves using AI that is efficient, adaptable, and scalable, since these scenarios often involve unique technical constraints and possibilities. As AI ...
The Lattice Mach™ brand of FPGAs has long set the standard for performance, flexibility, and efficiency in board control and security applications. With the launch of the new Lattice MachXO4™ FPGA family, Lattice is redefining what’s possible for control and connectivity in next-generation systems, delivering competitive power efficiency, robust reliability, and design flexibility for a wide range of applications in the Compute, Industrial, Automotive, Consumer, and Communicati...
Interest in edge computing has surged as organizations across industries seek smarter ways to automate processes, enhance productivity, and optimize labor. By processing data closer to its source, edge systems can provide benefits like reduced transmission and storage costs and strengthened security. They can also enable the development of advanced machines and devices, from autonomous mobile robots (AMRs) and humanoids to smart medical devices, which can operate with precision and speed. Thes...
Planning and execution are two very different beasts. A project may appear straightforward on paper, staying within budget, on schedule, and technically sound, only to hit roadblocks in the real world. However, turning ideas into reality isn’t always smooth, and success depends on how well we anticipate and navigate the unknowns. This gap between concept and execution is especially pronounced in the fast-growing realm of edge artificial intelligence (AI). In a recent roundtable discussion...
One of the more exciting developments now happening in the high-tech world is the work being done to enable quantum computing. After decades of theoretical discussion and development, the last few years have shown tangible progress in this radically different (and enormously complex) new method of computing. Quantum computers essentially perform calculations by flipping the electrical charge of individual atoms and allowing them to simultaneously exist in more than one state through a process ca...
Quantum computing is no longer just a concept confined to research labs. Thanks to rapid progress in both hardware and algorithms, the risk to today’s cryptographic systems is steadily increasing. In 2025, Google’s 105-qubit Willow chip and Microsoft’s Majorana 1 processor demonstrated that scalable quantum systems are moving closer to practical reality. Industry experts now predict that quantum computers capable of breaking RSA-2048 encryption could arrive as early as 2030 to ...
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...