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Intelligent power and sensing technology firm onsemi of Scottsdale, AZ, USA has signed a collaboration agreement with GlobalFoundries of Malta, NY (GF, the only US-based pure-play foundry with a global manufacturing footprint, including facilities in the USA, Europe and Singapore) to develop and manufacture gallium nitride (GaN) power products using GF’s 200mm eMode GaN-on-silicon process for critical markets, starting with 650V...

As we look ahead to 2026, we see intelligence increasingly being embedded within physical products and everyday interactions. This shift will be powered by rapid adoption of digital identity technologies such as near-field communication (NFC) alongside AI and agentic AI tools that automate workflows, improve efficiency, and accelerate innovation across the product lifecycle.

The sharp rise in NFC adoption—with 92% of brands already using or planning to use it in products in the next year—signals appetite to unlock the true value of the connected world. Enabling intelligence in new places gives brands the opportunity to bridge physical and digital experiences for positive social, commercial, and environmental outcomes.

Regulatory milestones, such as the phased rollout of the EU Digital Product Passport, along with sustainability pressures and the need to ensure transparency to drive trust will be key catalysts for edge and item-level AI.

In the year ahead, companies will unlock significant benefits in customer experience, sustainability, compliance, and supply chain efficiency by embedding intelligence from the edge to individual items and devices.

Let’s dig deeper into the technology trends shaping 2026.

1. Edge AI is the fastest growing frontier in semiconductors

Driven by the shift from pure inference to on-device training and continuous, adaptive learning, 2026 will see strong growth in edge AI demand. Specialized chips such as low-power machine learning accelerators, sensor-integrated chips, and memory-optimized chips will be used in consumer electronics, smart cities, and industrial IoT.

Next, new packaging approaches will become the proving ground for performance, cost efficiency, and miniaturization in intelligent edge devices.

2. Item-level intelligence is accelerating digital transformation

Intelligence will not stop at the device. Over the next 12 months, low-cost sensing, NFC, and edge AI will push computation down to individual items.

The capability to gather real-time data at item level in a move away from batch data, combined with AI, will enable personalized experiences, automation, and predictive analytics across smart packaging, healthcare and wellness products, retail, and logistics. Applications include real-time tracking, AI-driven personalization, automated supply chain optimization, predictive maintenance, and dynamic authentication.

This marks a fundamental shift as every item becomes a data node and source of intelligence.

3. Connected consumer experiences are driving breakthrough NFC adoption

NFC adoption is accelerating alongside the explosion of connected consumer experiences—from wearables and hearables to smart packaging, digital keys and wellness applications. NFC will become a central enabler of trust, personalization, and seamless connectivity.

Figure 1 NFC has become a key enabler in personalization-centric connectivity. Source: Pragmatic Semiconductor

As consumers increasingly expect intelligent product interaction, for example, to track provenance or engage with wellness apps to build a personalized profile and derive usable insights, the opportunity for NFC is clear. Brands will favor ultra-low-cost and thin NFC solutions—where flexible and ultra-thin semiconductors excel—to deliver frictionless, high-quality consumer experiences.

4. Heterogeneous integration will unlock design innovation

Heterogeneous integration through chiplets, interposers, and die stacking will become the preferred approach for achieving higher density and improved yields. This is a key enabler for miniaturization and differentiated form factors in facilitating customization for edge AI.

At the same time, the rise of agentic AI-driven EDA tools will lower design barriers and fuel cost-effective innovation through natural language tools. This will ignite startup growth and increase demand for agile, cost-effective foundry design services.

5. Compliance shifts from cost to competitive advantage

New regulatory frameworks such as Digital Product Passports, circularity, and Extended Producer Responsibility (EPR) will require authentication, traceability, and lifecycle visibility. Rather than a burden, this presents a strategic opportunity for competitive advantage and market expansion.

Embedded digital IDs with NFC capability allow businesses to secure product authentication, meet compliance and governance expectations, and unlock new value in consumer engagement. As compliance moves from paper systems to embedded intelligence, the opportunity will expand across consumer goods, industrial components, and supply chains.

6. Energy constraints are driving efficiencies in semiconductor manufacturing

As semiconductor manufacturing scales to serve AI demand, growing energy consumption in data centers is forcing industry to focus on power-efficient architectures. This is accelerating a shift away from centralized compute toward fully distributed sensing and intelligence at the edge. Edge AI architectures are designed to process data locally rather than transmit it upstream and will be essential to sustaining AI growth without compounding energy constraints.

Figure 2 Semiconductor manufacturing will increasingly adopt circular design principles such as reuse, recycling, and recoverability. Source: Pragmatic Semiconductor

The capability to establish and scale domestic manufacturing will also play a critical role in cutting embedded emissions and enabling more sustainable and efficient supply chains. Semiconductor manufacturing facilities, known as foundries, will be evaluated on their energy and material efficiency, supported by circular design principles such as reuse, recycling, and recoverability.

Companies that can demonstrate strong environmental commitments will gain long-term competitive advantage, attracting customers, partners, and skilled talent.

Intelligence right to the edge

These trends point toward a definitive shift as intelligence moves dynamically into the physical world. Compute will become increasingly distributed and identity embedded, unlocking efficiencies and delivering real-time insights into the fabric of products, infrastructure, and supply chains.

Semiconductor manufacturing will sit at the heart of the next phase of digital transformation. Flexible and ultra-thin chip technologies will enable new classes of innovations, from emerging form factors such as wearables and hearables to higher functional density in constrained spaces, alongside more carbon-efficient manufacturing models.

The implications for businesses are clear. Companies can accelerate innovation, deepen consumer engagement, and turn compliance into a source of competitive advantage. Those that embed connected technologies into their 2026 strategy will be those that are best positioned to take advantage of the digital transformation opportunities ahead.

Richard Price is co-founder and chief technology officer of Pragmatic Semiconductor.

 

 

Related Content

• AI at the edge: It’s just getting started
• The AI Future is Now All About the Edge
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• Powering E-Paper Displays with NFC Energy Harvesting
• Edge AI powers the next wave of industrial intelligence

The post Semiconductor technology trends and predictions for 2026 appeared first on EDN.

submitted by /u/SpaceRuthie [link] [comments]

WIP screenshots for some RP2040 based cyberpunk sunglasses I've been working on this year. Hopefully someone will one day create a kicad or easyeda extension that allows me to route at 30° / 60° angles, so I can make hexagonal traces submitted by /u/babel_infoc [link] [comments]

submitted by /u/aarontodd82 [link] [comments]

Third image is the first version. First and second images are improved based on feedback from my dad that has a lot more experience with electronics than me XD This was possibly the most fun school project I have worked on, even if it was slightly more programming than wiring it all up submitted by /u/__NORB__ [link] [comments]

submitted by /u/Green-Pie4963 [link] [comments]

After an unprecedented investment wave between 2019 and 2024, the power silicon carbide (SiC) industry is now entering a correction cycle, according to Yole Group’s report ‘Power SiC 2025 – Front-End Manufacturing Equipment’...

The complexity of vehicle hardware and software is rising at an unprecedented rate, so traditional development methodologies are no longer sufficient to manage system-level interdependencies among advanced driver assistance systems (ADAS), autonomous driving (AD), and in-vehicle infotainment (IVI) functions.

That calls for a new approach, the one that enables automotive OEMs and tier 1s to speed the development of software-defined vehicles (SDVs) with early full-system, virtual integration that mirrors real-world vehicle hardware. That will accelerate both application and low-level software development for ADAS, AD, and IVI and remove the need for design engineers to build their own digital twins before testing software.

It will also reduce time-to-market for critical applications from months to days. Siemens EDA has unveiled what it calls a virtual blueprint for digital twin development. PAVE360 Automotive, a digital twin software, is pre-integrated as an off-the-shelf offering to address the escalating complexity of automotive hardware and software integration.

While system-level digital twins for SDVs using existing technologies can be complex and time-consuming to create and validate, PAVE360 Automotive aims to deliver a fully integrated, system-level digital twin that can be deployed on day one. That reduces the time, effort, and cost required to build such environments from scratch.

Figure 1 PAVE360 Automotive is a cloud-based digital twin that accelerates system-level development for ADAS, autonomous driving, and infotainment. Source: Siemens EDA

“The automotive industry is at the forefront of the software-defined everything revolution, and Siemens is delivering the digital twin technologies needed to move beyond incremental innovation and embrace a holistic, software-defined approach to product development,” said Tony Hemmelgarn, president and CEO, Siemens Digital Industries Software.

Siemens EDA’s digital twin—a cloud-based off-the-shelf offering—allows design engineers to jumpstart vehicle systems development from the earliest phases with customizable virtual reference designs for ADAS, autonomous driving, and infotainment. Moreover, the cloud-based collaboration unifies development with a single digital twin for all design teams.

The Arm connection

Earlier, Siemens EDA joined hands with Arm to accelerate virtual environments for Arm Cortex-A720AE in 2024 and Arm Zena Compute Subsystems (CSS) in 2025. Now Siemens EDA is integrating Arm Zena CSS with PAVE360 Automotive to enable design engineers to start building on Arm-based designs faster and more seamlessly.

Figure 2 Here is how PAVE360’s digital twin works alongside the Arm Zena CSS platform for AI-defined vehicles. Source: Siemens EDA

On the other hand, access to Arm Zena CSS in a digital twin environment such as PAVE360 Automotive can accelerate software development by up to two years. “With Arm Zena CSS available inside Siemens’ pre-integrated PAVE360 Automotive environment, partners can not only customize their solutions leveraging the unique flexibility of the Arm architecture but also validate and iterate much earlier in the development cycle,” said Suraj Gajendra, VP of products and solutions for Physical AI Business Unit at Arm.

PAVE360 Automotive, now made available to key customers, is planned for general availability in February 2026. It will be demonstrated live at CES 2026 in the Auto Hall on 6–9 January 2026.

Related Content

• Why the Cloud Is Essential for SDV Development
• Unveiling the Transformation of Software-Defined Vehicles
• Software-defined vehicle (SDV): A technology to watch in 2025
• Architectural opportunities propel software-defined vehicles forward
• Digital Twins Power Rapid Software Deployment in Autonomous Vehicles

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