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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 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...

Across industries and use cases, computing capacity is shifting away from centralized servers and towards the edge. Whether in the form of autonomous vehicles, smart sensors, or other technological solutions, today's intelligent applications demand faster decision-making and increased autonomy. This shift is especially prevalent in the Industrial, defense, and aerospace industries. The unmanned aerial vehicles (UAVs) and drones used in defense applications rely heavily on edge intelligence to...

Our digital world is undergoing a profound transformation. Cloud computing, artificial intelligence (AI) and machine learning (ML) workloads, as well as the emergence of quantum computing capabilities, are reshaping how networks must be protected and secured. What’s more, these changes come amid evolving risks & regulations – from the prevalence of “harvest now; decrypt later” attacks, to updated standards like the Commercial National Security Algorithm Suite (CNSA) 2...

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...

Building and maintaining connected digital ecosystems that account for today’s evolving cyber threat landscape requires a degree of hardware-based trust, as software-only security approaches are no longer sufficient to protect complex, distributed systems Luckily, today’s developers can reference a foundational example of hardware-based security that has existed for decades: the Trusted Platform Module (TPM). With over four billion TPM units deployed globally across a wide range of u...

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...

Robots have rapidly evolved from science fiction into a cornerstone of modern industry. Today’s autonomous systems can execute complex tasks with minimal human oversight – transforming how we work, live, and move. But achieving this level of intelligence and reliability in real-world environments requires more than just advanced software. It demands robust hardware, deterministic processing, and scalable system architectures that can support safe, real-time decision-making under dema...